Umapped is a collaborative B2B2C trip management platform that helps travel companies and professionals engage with their customers throughout the entire travel lifecycle

Umapped

umapped

How to Use Terraform to Configure AWS Verified Access With an OIDC Google Provider

Hi All! Here is my weekly wrap up email. If you love this content (please share it), but also… Check out my , connect with me on / , and Podcast YouTube Twitter Subscribe to my weekly newsletter Join our free slack community What’s in today’s newsletter? The Map Is Not the Territory Idea: Intelligence vs. Wisdom Question: Useful Learning Quote: Liz Elting, Bob Meers, Chris Smith, Why AI Can’t Replace You Podcast: How I Got Into And Managed to Walk Away from Burnout Article: Idea: The Map Is Not the Territory Ever tried navigating a bustling city with a map from the 1980s? Turns out, the city is the same, but the map has changed. , a bustling locale in New York, changed hands three times in a decade. On paper, every owner was a savvy entrepreneur. Yet, two of them failed, one succeeded wildly. The difference? Their perception of the territory. John’s Coffee Shop : Every business operates with models. Forecasts. Predictions. Templates. Maps. But, as Alfred Korzybski reminded us, "the map is not the territory." Fact John's first owner, a techie, automated everything. He trusted algorithms to dictate coffee preferences, manage inventory, and even select music. : technology-driven efficiency equals success. His map The second owner went retro. Vintage furniture. Manual registers. A return to the "good old days." : people long for nostalgia. His map The third, a young barista-turned-owner, constantly interacted with customers. She tweaked the menu based on conversations, adjusted seating arrangements from observations, and kept a flexible approach. : listen, adapt, and evolve. Her map Two static maps. One dynamic terrain. Guess who thrived? Our businesses, like cities, are dynamic, ever-changing. But we, time and again, clutch outdated maps thinking they'll guide us. didn’t dominate by following the traditional auto industry's map. They redrew it. Tesla didn’t rise by mimicking Blockbuster. They envisioned a new landscape. Netflix Yet, countless businesses cling to their maps. After all, it's reassuring to follow a blueprint. But what if that blueprint is outdated or just plain wrong? Best nautical map of its time. Top-notch navigation tools. But, it wasn’t the map that failed; it was the iceberg not on it. A dynamic, unforeseen component of the territory. Consider the Titanic. So, how do we operate in a world where our business maps might be leading us astray? : Every map has blind spots. Anticipate them. Embrace Uncertainty : The world changes. Regularly revisit and revise your maps. Stay Curious : Get out there. Feel the ground. Talk to people. Real-time feedback trumps theoretical models. Interact with the Terrain They had a map. A good one. But when the terrain changed with the rise of digital streaming, their map became obsolete. Remember Blockbuster’s decline? Conversely, , under Jobs, was known to pivot on a dime. iPod's success? iPhone’s creation? Responses to a changing territory. Apple Lastly, a nod to , the author who’s talked extensively about "Black Swan" events. Events so rare, so unpredictable, they’re not on anyone’s map. Yet, they shape terrains. Nassim Taleb Businesses that thrive, Taleb argues, aren’t those with the best maps, but those most adaptable when off the map. So, as you chart your business journey, remember: Your map is a guide, not gospel. The real magic happens when you dare to traverse the unmapped, the unpredictable, the unknown. Because in the end, it's not about having the best map, but being the best explorer. Question: Intelligence vs. Wisdom What Is The Difference Between Intelligence & Wisdom? It is often measured by tests, such as , that assess logical, verbal, and mathematical skills. Intelligence can help you solve problems, learn new things, and perform tasks. Intelligence is the ability to acquire, process, and apply information. IQ It is often gained by observation, reflection, and practice. Wisdom can help you understand yourself, others, and the world. Wisdom is the ability to use knowledge and experience to make sound judgments. A few places to start. Intelligence is based on the functions of the brain, such as memory, reasoning, and perception. Wisdom, on the other hand, is based on the insights of the mind, such as . The Cognitive Perspective. intuition, empathy, and morality Intelligence is influenced by the genes, environment, and education of the individual. Wisdom is influenced by the age, culture, and values of the individual. The Developmental Perspective. Intelligence is useful for achieving goals, creating innovations, and advancing knowledge. Wisdom is useful for avoiding mistakes, making decisions, and finding meaning. The Practical Perspective. It's in the balance where you really thrive. They can support each other and enhance each other's value. Intelligence and wisdom are not mutually exclusive. So, don't just be smart. Because Be wise. intelligence without wisdom can be dangerous. Quote: Useful Learning - Dr. Barbara Oakley “It’s not what you know that matters. What matters is how well you can use what you know when you need it. In other words, it’s not the knowledge you have crammed into your head that’s important; it’s the knowledge that you can access and use when you need it.” It’s not what you know. It’s what you do with that knowledge. Seek growth & continual learning, not perfection (because perfection doesn’t exist). Take knowledge, make it relevant, make it applicable. Do something with it. ( ) Share On Twitter Podcast: Liz Elting, Bob Meers, Chris Smith, Why AI Can’t Replace You 1. Liz Elting - CEO at Elizabeth Elting Foundation | | YouTube Spotify Apple Liz Elting is a distinguished entrepreneur, philanthropist, and business leader, known for her remarkable journey that spans five countries. In 1992, she founded TransPerfect from an NYU dorm room, growing it into the world's largest language solutions company with over $1.1 billion in revenue and a presence in 100+ cities. She is a celebrated advocate for women's empowerment and a sought-after speaker, with her book, "Dream Big and Win: Translating Passion into Purpose and Creating a Billion-Dollar Business," poised to inspire others to follow in her footsteps. Recognized as one of Forbes' Richest Self-Made Women, Liz Elting continues to shape the business landscape with her passion and dedication. 2. Bob Meers - Ex-CEO at Reebok & LuLulemon, CEO at Better for All | | YouTube Spotify Apple Bob Meers is a highly accomplished CEO with a history of leading several prominent companies (LuLulemon, Reebok). Currently at the helm of Better for All, a unique line of PHBH home compostable bioplastic cups championing environmental sustainability, Bob brings a wealth of leadership experience to the organization. Previously, Meers served as CEO of Lululemon Athletica, Inc., from December 2005 to June 2008, taking a small yoga apparel business to a billion-dollar international public enterprise. Before that, Meers served as President & CEO of Reebok. During Meers’ 15-year tenure at Reebok, the company grew from $13 million to $3.5 billion in sales. 3. Chris Smith - Co-Founder of Curaytor | The Conversion Code | | YouTube Spotify Apple Chris Smith is the Co-Founder of Curaytor (an Inc. 500 fastest-growing business) and he was named top 4 best marketers under 40, according to the American Marketing Association. His book, The Conversion Code, is taught at colleges like Johns Hopkins University and he has been a guest lecturer at NYU. Chris used the blueprint in this book to quickly grow his company to eight figures in annual recurring revenue, without raising any venture capital. His work has been featured in AdWeek, Forbes, Fortune, and many other publications. 4. Why AI Can't Replace You | | YouTube Spotify Apple In this Lessons episode, we explore the unique value of human creativity and how to cultivate and maintain it in the age of rapid AI advancement. I'll discuss how the world is rapidly evolving, with AI taking over roles traditionally held by humans. But where does human ingenuity fit in this landscape? I’ll also discuss the unique attributes humans possess - our capacity to empathize, innovate, and imagine, which even the most advanced AI cannot replicate. How I Got Into And Managed to Walk Away from Burnout Article: Everyone is an advocate of not over-working. But we all fall into burnout. How does this happen? What do we do to get out of it? Well, here’s an article that gives us an answer. Read it here. My Links Success Story (Top 10 Business Podcast) Newsletter (321k Subs) Social Media Also published . here

It's Not About Having the Best Map, but Being the Best Explorer

এটি সেরা মানচিত্র থাকার বিষয়ে নয়, সেরা এক্সপ্লোরার হওয়ার বিষয়ে

Es geht nicht darum, die beste Karte zu haben, sondern darum, der beste Entdecker zu sein

No se trata de tener el mejor mapa, sino de ser el mejor explorador

Il ne s'agit pas d'avoir la meilleure carte, mais d'être le meilleur explorateur

यह सर्वश्रेष्ठ मानचित्र होने के बारे में नहीं है, बल्कि सर्वश्रेष्ठ एक्सप्लोरर होने के बारे में है

重要なのは最高の地図を持っていることではなく、最高の探検家であることです

최고의 지도를 갖는 것이 아니라 최고의 탐험가가 되는 것

Não se trata de ter o melhor mapa, mas de ser o melhor explorador

Дело не в лучшей карте, а в том, чтобы быть лучшим исследователем

Önemli olan En İyi Haritaya Sahip Olmak Değil, En İyi Kaşif Olmaktır

Vấn đề không phải là có bản đồ tốt nhất mà là trở thành nhà thám hiểm giỏi nhất

不是拥有最好的地图，而是成为最好的探险家

The Corner Pub.

Tarzan the Terrible by Edgar Rice Burroughs, is part of the HackerNoon Books Series. You can jump to any chapter in this book here . Home Home Within an hour of the fall of Lu-don and Mo-sar, the chiefs and principal warriors of Pal-ul-don gathered in the great throneroom of the palace at A-lur upon the steps of the lofty pyramid and placing Ja-don at the apex proclaimed him king. Upon one side of the old chieftain stood Tarzan of the Apes, and upon the other Korak, the Killer, worthy son of the mighty ape-man. And when the brief ceremony was over and the warriors with upraised clubs had sworn fealty to their new ruler, Ja-don dispatched a trusted company to fetch O-lo-a and Pan-at-lee and the women of his own household from Ja-lur. And then the warriors discussed the future of Pal-ul-don and the question arose as to the administration of the temples and the fate of the priests, who practically without exception had been disloyal to the government of the king, seeking always only their own power and comfort and aggrandizement. And then it was that Ja-don turned to Tarzan. "Let the Dor-ul-Otho transmit to his people the wishes of his father," he said. "Your problem is a simple one," said the ape-man, "if you but wish to do that which shall be pleasing in the eyes of God. Your priests, to increase their power, have taught you that Jad-ben-Otho is a cruel god, that his eyes love to dwell upon blood and upon suffering. But the falsity of their teachings has been demonstrated to you today in the utter defeat of the priesthood. "Take then the temples from the men and give them instead to the women that they may be administered in kindness and charity and love. Wash the blood from your eastern altar and drain forever the water from the western. "Once I gave Lu-don the opportunity to do these things but he ignored my commands, and again is the corridor of sacrifice filled with its victims. Liberate these from every temple in Pal-ul-don. Bring offerings of such gifts as your people like and place them upon the altars of your god. And there he will bless them and the priestesses of Jad-ben-Otho can distribute them among those who need them most." As he ceased speaking a murmur of evident approval ran through the throng. Long had they been weary of the avarice and cruelty of the priests and now that authority had come from a high source with a feasible plan for ridding themselves of the old religious order without necessitating any change in the faith of the people they welcomed it. "And the priests," cried one. "We shall put them to death upon their own altars if it pleases the Dor-ul-Otho to give the word." "No," cried Tarzan. "Let no more blood be spilled. Give them their freedom and the right to take up such occupations as they choose." That night a great feast was spread in the pal-e-don-so and for the first time in the history of ancient Pal-ul-don black warriors sat in peace and friendship with white. And a pact was sealed between Ja-don and Om-at that would ever make his tribe and the Ho-don allies and friends. It was here that Tarzan learned the cause of Ta-den's failure to attack at the stipulated time. A messenger had come from Ja-don carrying instructions to delay the attack until noon, nor had they discovered until almost too late that the messenger was a disguised priest of Lu-don. And they had put him to death and scaled the walls and come to the inner temple court with not a moment to spare. The following day O-lo-a and Pan-at-lee and the women of Ja-don's family arrived at the palace at A-lur and in the great throneroom Ta-den and O-lo-a were wed, and Om-at and Pan-at-lee. For a week Tarzan and Jane and Korak remained the guests of Ja-don, as did Om-at and his black warriors. And then the ape-man announced that he would depart from Pal-ul-don. Hazy in the minds of their hosts was the location of heaven and equally so the means by which the gods traveled between their celestial homes and the haunts of men and so no questionings arose when it was found that the Dor-ul-Otho with his mate and son would travel overland across the mountains and out of Pal-ul-don toward the north. They went by way of the Kor-ul-JA accompanied by the warriors of that tribe and a great contingent of Ho-don warriors under Ta-den. The king and many warriors and a multitude of people accompanied them beyond the limits of A-lur and after they had bid them good-bye and Tarzan had invoked the blessings of God upon them the three Europeans saw their simple, loyal friends prostrate in the dust behind them until the cavalcade had wound out of the city and disappeared among the trees of the nearby forest. They rested for a day among the Kor-ul-JA while Jane investigated the ancient caves of these strange people and then they moved on, avoiding the rugged shoulder of Pastar-ul-ved and winding down the opposite slope toward the great morass. They moved in comfort and in safety, surrounded by their escort of Ho-don and Waz-don. In the minds of many there was doubtless a question as to how the three would cross the great morass but least of all was Tarzan worried by the problem. In the course of his life he had been confronted by many obstacles only to learn that he who will may always pass. In his mind lurked an easy solution of the passage but it was one which depended wholly upon chance. It was the morning of the last day that, as they were breaking camp to take up the march, a deep bellow thundered from a nearby grove. The ape-man smiled. The chance had come. Fittingly then would the Dor-ul-Otho and his mate and their son depart from unmapped Pal-ul-don. He still carried the spear that Jane had made, which he had prized so highly because it was her handiwork that he had caused a search to be made for it through the temple in A-lur after his release, and it had been found and brought to him. He had told her laughingly that it should have the place of honor above their hearth as the ancient flintlock of her Puritan grandsire had held a similar place of honor above the fireplace of Professor Porter, her father. At the sound of the bellowing the Ho-don warriors, some of whom had accompanied Tarzan from Ja-don's camp to Ja-lur, looked questioningly at the ape-man while Om-at's Waz-don looked for trees, since the GRYF was the one creature of Pal-ul-don which might not be safely encountered even by a great multitude of warriors. Its tough, armored hide was impregnable to their knife thrusts while their thrown clubs rattled from it as futilely as if hurled at the rocky shoulder of Pastar-ul-ved. "Wait," said the ape-man, and with his spear in hand he advanced toward the GRYF, voicing the weird cry of the Tor-o-don. The bellowing ceased and turned to low rumblings and presently the huge beast appeared. What followed was but a repetition of the ape-man's previous experience with these huge and ferocious creatures. And so it was that Jane and Korak and Tarzan rode through the morass that hems Pal-ul-don, upon the back of a prehistoric triceratops while the lesser reptiles of the swamp fled hissing in terror. Upon the opposite shore they turned and called back their farewells to Ta-den and Om-at and the brave warriors they had learned to admire and respect. And then Tarzan urged their titanic mount onward toward the north, abandoning him only when he was assured that the Waz-don and the Ho-don had had time to reach a point of comparative safety among the craggy ravines of the foothills. Turning the beast's head again toward Pal-ul-don the three dismounted and a sharp blow upon the thick hide sent the creature lumbering majestically back in the direction of its native haunts. For a time they stood looking back upon the land they had just quit—the land of Tor-o-don and GRYF; of JA and JATO; of Waz-don and Ho-don; a primitive land of terror and sudden death and peace and beauty; a land that they all had learned to love. And then they turned once more toward the north and with light hearts and brave hearts took up their long journey toward the land that is best of all—home. About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books. This book is part of the public domain. Edgar Rice Burroughs (2020). Tarzan the Terrible. Urbana, Illinois: Project Gutenberg. Retrieved October 2022 https://www.gutenberg.org/cache/epub/2020/pg2020-images.html This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever. You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at www.gutenberg.org , located at https://www.gutenberg.org/policy/license.html .

The chiefs and principal warriors of Pal-ul-don gathered in the great throneroom

With DevOps and Continuous Delivery gaining traction, one might ask whether the principles behind Lean and Agile are still relevant. How do they compare to the 5 Continuous Delivery principles, and what do any differences mean for software development teams? The beginnings of lightweight software delivery Throughout the 1990s, a revolution was brewing in the software development industry. The early phased models divided the delivery process into skill-based steps, with designs and documents used to run approval processes to control a project. The process for delivering software was heavyweight and slow, with little indication that the overheads reduced the risks they tried to mitigate. A collection of lightweight methods emerged, designed to generate fast feedback and iteratively adapt the plan based on new information. Rather than controls and approvals, developers used small batches to manage the risk and provide frequent opportunities to change direction. The Agile Manifesto emerged from this adaptive and lightweight methods community in 2001, with Lean Software Development arriving a couple of years later. Agile and Lean provided a -based approach to software development. You could test whether an approach was Agile or Lean by testing it against a set of core statements defining each method's philosophy. values and principles Continuous Delivery emerged from the Lean and Agile communities, providing the most concrete practices and capabilities to achieve frequent and safe software delivery. Apart from Extreme Programming, most software development methods deal with requirements management and communication structures. Continuous Delivery takes on the rest of the value stream and provides a pathway to an efficient and reliable delivery pipeline. InfoQ publishes an annual report on software development culture and methods. They style the report after Geoffrey Moore's concept. Moore famously visualizes a technology adoption lifecycle as a bell curve spread across 3 standard deviations. Crossing the Chasm The chart is divided into 5 groups with different attitudes to new technology: Innovators (-3) Early adopters (-2) Early majority (-1) Late majority (+1) Laggards (+3) The early majority and late majority represent two-thirds of the adoption lifecycle. Still, for new technology (or, in the case of InfoQ, a new idea) to move into the majority, it must cross the chasm from the early adopters to the mainstream majorities. While adaptive modes of software delivery are embedded in the late majority, the capabilities needed for continuous modes of delivery are still making their way across the chasm. Some practices (such as DevSecOps) have made the leap, while other key elements, like team topologies and empowered teams, remain at the early adopter stage. So, with DevOps and Continuous Delivery gaining traction, it's a great time to compare the 5 principles of Continuous Delivery with the 12 Agile principles and the 7 Lean principles. Comparing Agile, Lean, and Continuous Delivery principles Agile, Lean, and Continuous Delivery each provide a set of principles. This helps us compare their fundamental structures. There are other techniques and capabilities in Lean and Continuous Delivery that don't have comparable elements in Agile. The Agile Manifesto was intended to be a broad litmus test of the agility of other specific methods, such as Extreme Programming, Scrum, and Disciplined Agile, so it didn't define further details. Lean expands on its principles by describing techniques covering the whole software development process with advice on planning, design, testing, and maintenance. Continuous Delivery uses the deployment pipeline to focus efforts on improving the flow of change, from the code commit to the software running in production. Specific technical capabilities are described in detail to enable the . early and continuous delivery of valuable software The principles are the only directly comparable elements of these 3 approaches. Continuous Delivery principles There are 5 principles of Continuous Delivery: Build quality in Work in small batches Computers perform repetitive tasks, and people solve problems Relentlessly pursue continuous improvement Everyone is responsible The principles can be arranged into a reinforcing relationship, where the first 3 principles act as drivers of continuous improvement, for which everyone involved is responsible. Agile principles comparison In general, Continuous Delivery principles are consistent with . The Agile Manifesto For example, working in small batches is widely understood to help achieve several of the Agile principles: Our highest priority is to satisfy the customer through early and continuous delivery of valuable software. Welcome changing requirements, even late in development. Agile processes harness change for the customer's competitive advantage. Deliver working software frequently, from a couple of weeks to a couple of months, with a preference to the shorter timescale. Working software is the primary measure of progress. Agile processes promote sustainable development. The sponsors, developers, and users should be able to maintain a constant pace indefinitely. Simplicity - the art of maximizing the amount of work not done - is essential. The phrasing of the principle "work in small batches" is concise and easy to follow in practice. This Continuous Delivery principle contributes to the attainment of half of the Agile principles. There is also an amplification effect when you combine the 5 principles. To "deliver working software frequently", you need to work in small batches, increase automation, and build quality in. Two Agile principles are not covered by Continuous Delivery: Business people and developers must work together daily throughout the project. The most efficient and effective method of conveying information to and within a development team is face-to-face conversation. Continuous Delivery is centered on the delivery pipeline, which means the process of identification, inception, and initiation aren't a direct concern of Continuous Delivery. Additionally, in the front matter of the book, the authors highlight that the book was created according to the ideas it contained. The contributors and editors worked using different tools and from separate locations. They used version control and automated builds to form a delivery pipeline for the book. They didn't work together daily or convey information face-to-face. Continuous Delivery As an industry, many organizations that hadn't attempted to work remotely are now ready to experiment with distributed working. This will further challenge the need for real-time face-to-face coordination as asynchronous communication becomes more common and familiar. Regarding word counts, Continuous Delivery principles are conveyed in 21 words, rather than 180 words for Agile principles. A combination of hindsight and incisive editing has given us a compass to check our direction, with the detail provided in the specific practices of Continuous Delivery. It's easy to get bogged down in the details of implementing Continuous Delivery — tools, architecture, practices, politics — if you find yourself lost, try revisiting these principles and you may find it helps you re-focus on what's important." — Jez Humble You don't have to throw out The Agile Manifesto to move forwards; it's part of the geography that Continuous Delivery and DevOps are building on. The industry will continue to discover new and better ways of developing software. It's increasingly evident that technical practices and cultural capabilities are vital. Lean principles comparison The Lean principles are already brief and actionable. There's complete alignment between Lean and Continuous Delivery, with no unmapped areas. With Agile, Continuous Delivery offered a concise alternative to 10 Agile principles. In the case of Lean, Continuous Delivery aligns entirely with the principles. Each approach provides a different perspective that applies to various organization segments. In an organization that has fully adopted both Lean and Continuous Delivery, the respective principles are helpful to different groups. Lean principles and techniques are leadership tools, while Continuous Delivery provides an approach specific to the individual contributors' delivery efforts. For example, automation is a practical attack vector for eliminating waste, delivering quickly, and building integrity into the system with Continuous Delivery. Conclusion Continuous Delivery provides a concise set of principles that align with 10 of the 12 Agile principles and complement Lean, providing a different perspective on achieving similar goals. All 3 sets of principles are consistent with modern management philosophy and provide different ways to review and re-focus your software delivery efforts. You can use the Continuous Delivery principles to guide your software delivery efforts and refer back to Agile and Lean principles to find further inspiration for your improvement efforts. Also published here.

A Comparison of Agile, Lean, and Continuous Delivery

When you run any C-program, its executable image loaded into RAM of computer in an organized manner which known as process address space or memory layout of C program. Here I have tried to show you the same thing in two parts . /!\: Originally published @ . www.vishalchovatiya.com In the Part 1 i.e. "Overview", we will see segment-wise overview & in Part 2  i.e. "Example", we'll see How C program stored in RAM memory? with example. Part 1: Overview The memory layout of C program organized in the following fashion: Text segment Data segment Heap segment Stack segment Note: It’s not just these 4 segments, there are a lot more but these 4 are the core to understand the working of C program at the machine level. HIGHER  ADDRESS                                                                                                        
   +------------------------+                                                                             
   |  Unmapped or reserved  | Command-line argument & Environment variables                                                                          
   |------------------------|------------------------                                                                          
   |     Stack segment      | |                                                                                                
   |           |            | | Stack frame                                                                                    
   |           v            | v                                                                                                
   |                        |                                                                                                  
   |           ^            | ^                                                                                                
   |           |            | | Dynamic memory                                                                                 
   |     Heap segment       | |                                                                                                
   |------------------------|------------------------                                                                          
   |   Uninitialized data   |                                                                                                  
   |------------------------| Data segment                                                                                     
   |    Initialized data    |                                                                                                  
   |------------------------|------------------------                                                                          
   |                        |                                                                                                  
   |      Text segment      | Executable code                                                                                  
   |                        |                                                                                                  
   +------------------------+                                                                                                  
         LOWER  ADDRESS Text segment Text segment contains executable instructions of your C program, its also called code segment also. This includes all functions making up the program( too), both user-defined and system. main() The text segment is sharable so that only a single copy needs to be in memory for different executing programs, such as text editors, shells, and so on. Usually, the text segment is read-only, to prevent a program from accidentally modifying its instructions. Data segment There are two subsections of this segment 1. Initialized data It contains both static and global data that initialized with non-zero values. This segment can be further classified into the read-only area and read-write area. For example, The global string defined by and a statement like an outside the (i.e. global) would be stored in initialized read-write area. char string[ ] = "hello world" int count=1 main And a global statement like ; makes the variable read-only and to be stored in initialized read-only area. const int A=3 A 2. Uninitialized data (BSS segment) An uninitialized data segment also called the BSS( ‘Block Started by Symbol’ ) segment. Which contains all global and static variables that initialized to zero or do not have explicit initialization in source code. For example, The global variable declared as would be stored in the uninitialized data segment. A statement like static will also be stored in this segment cause it initialized with zero. int A int X=0 If you do not initialize a global variable, by default value is zero. This flushing memory content is usually done by program loader(i.e. ) /lib/ld-linux.so.2 Heap segment The heap segment is an area where dynamically allocated memory (allocated by , , and for C++) resides. malloc() calloc() realloc() new When we allocate memory through dynamic allocation techniques(in other words, run-time memory allocation), program acquire space from OS and process address space grows. We can free dynamically allocated memory space (by using or ). Freed memory goes back to the heap but doesn’t have to be returned to OS (it doesn’t have to be returned at all), so unordered / eventually, cause heap fragmentation. You can learn more about . free() delete malloc free how malloc works here When we use dynamic allocation to acquire memory space we must keep track of allocated memory by using its address. Stack segment The stack segment is an area where local variables stored. By saying local variable means that all those variables which are declared in every function including in your C program. I have written a detailed article about the . main() function stack frame here When we call any function, the stack frame created and when a function returns, the stack frame destroyed/rewind including all local variables of that particular function. A stack frame contains some data like return address, arguments passed to it, local variables, and any other information needed by the invoked function. A stack pointer(SP) which is a special function register of CPU keeps track of stack by each push & pop operation onto it, by adjusted stack pointer to next or previous address. The direction of the stack & heap growth completely depends on the compiler, ABI, OS and hardware. Part 2: Example We have taken a simple example as shown in tittle along with its memory layout. As we discussed in the previous part(i.e. Overview) how executable image of our program divided into the different segment and stored in memory(RAM). Now we understand those blocks by using our example code presented above. Loader A loader is not a segment but kind of program interpreter which reads a different segment from the binary & copy it in RAM in proper fashion. There is a binary utility command by which you can see different segments & path of the loader in binary as follows: $ readelf --segments ./a.out 
Elf file type is EXEC (Executable file)
Entry point 0x8048300
There are 9 program headers, starting at offset 52
Program Headers:
  Type           Offset   VirtAddr   PhysAddr   FileSiz MemSiz  Flg Align
  PHDR           0x000034 0x08048034 0x08048034 0x00120 0x00120 R E 0x4
  INTERP         0x000154 0x08048154 0x08048154 0x00013 0x00013 R   0x1
      [Requesting program interpreter: /lib/ld-linux.so.2]
  LOAD           0x000000 0x08048000 0x08048000 0x00608 0x00608 R E 0x1000
  LOAD           0x000f08 0x08049f08 0x08049f08 0x00118 0x00124 RW  0x1000
  DYNAMIC        0x000f14 0x08049f14 0x08049f14 0x000e8 0x000e8 RW  0x4
  NOTE           0x000168 0x08048168 0x08048168 0x00020 0x00020 R   0x4
  GNU_EH_FRAME   0x0004c4 0x080484c4 0x080484c4 0x00044 0x00044 R   0x4
  GNU_STACK      0x000000 0x00000000 0x00000000 0x00000 0x00000 RW  0x10
  GNU_RELRO      0x000f08 0x08049f08 0x08049f08 0x000f8 0x000f8 R   0x1
 Section to Segment mapping:
  Segment Sections...
   00     
   01     .interp 
   02     .interp .note.ABI-tag .hash .dynsym .dynstr .gnu.version .gnu.version_r .rel.dyn .rel.plt .init .plt .plt.got .text .fini .rodata .eh_frame_hdr .eh_frame 
   03     .init_array .fini_array .jcr .dynamic .got .got.plt .data .bss 
   04     .dynamic 
   05     .note.ABI-tag 
   06     .eh_frame_hdr 
   07     
   08     .init_array .fini_array .jcr .dynamic .got As I have mentioned earlier, there is not only 4 segment as you can see above, but there are a lot of segments which usually depends on compiler & . ABI Above you can see, , , , etc. segments are there. But a stack segment is not shown as its created at a run time & decided by OS(precisely loader & kernel). .data .bss .text in the program header defines the name & path of loader which going to load the current binary image into the RAM by reading these segments. Here it is INTERP /lib/ld-linux.so.2. You can read more about binary . file format ELF here Text segment When you compile C code, you get executable image(which may be in any form like , , , or no extension etc). This executable image contains text segment which you see by Binutils command and it looks like follows: .bin .exe .hex .out $ objdump -d <binary_name> .....
080483f1 <main>:
 80483f1:  8d 4c 24 04            lea    0x4(%esp),%ecx
 80483f5:  83 e4 f0               and    $0xfffffff0,%esp
 80483f8:  ff 71 fc               pushl  -0x4(%ecx)
..... This is executable instructions stored in the text segment as a read-only section and shared by the processes if requires. These instructions read by CPU using program counter and stack frame created in the stack at the time of execution. Program-counter points to the address of the instruction to executed which lies in the text segment. Data segment Initialized Data segment A ; stored in the read-only area. So you can not modify it accidentally. const int x = 1 While a string & stored in the read-write area because we don’t use a keyword like const which makes variable read-only. char str[] = "Hi!"; static int var = 0; Uninitialized Data segment In our program, declared global goes to this area of storage because it is not initialized or initialized to zero by default. int i Heap segment When you compile your program, memory space allocated by you i.e. all locals, static & global variables fixed at compile-time. But when code needs memory at run-time, it approach OS by calling functions like , , etc. malloc() calloc() When OS provides dynamic memory to process it shrinks stack limit pointer which initially points to uninitialized data segment start(the technical word is “program break”, read about it ). here As a result heap segment grows. That’s why there is no line between heap & stack segment. An arrow indicates its growth of direction. In the example code, we allocate 1-byte dynamic memory using function and stored its address in pointer to keep track of that memory or to access it. malloc() ptr This is a local variable of main hence it’s in main’s stack frame, but memory pointed by it is in a heap which I have shown by . ptr *ptr Stack segment The usual starting point(not entry point which is different) of any program is , which is also a function hence, stack frame is created for it while execution. Although there are many functions called before main which I have discussed . main() here As you can see in image, stack frame of is created before function as we called it nested. main() func() As the execution overs its local variable a and its stack frame will destroy(rewind is a precise word here), same goes for function also. func( ) main() And this is how stack grows & shrinks. Intuitive FAQs Q. How do you determine the stack growth direction ? Simple…! by comparing the address of two different function’s local variables. A. *main_ptr = ; *func_ptr = ; { a; func_ptr = &a; } { a; main_ptr = &a;
    func();
    (main_ptr > func_ptr) ? ( ) : ( ); ;
} int NULL int NULL void func () int int main () int printf "DOWN\n" printf "UP\n" return 0 Q. How do you corrupt stack deliberately ? Corrupt the SFR values stored in the stack frame. A. { a; (&a, , ); } {
    func(); ;
} void func () int memset 0 100 // Corrupt SFR values stored in stack frame int main () return 0 Q. How you can increase stack frame size ? alloca() is the answer. Google about it or see . A. this

How C program stored in RAM memory

2018 was a big year for ethics and rights, as new forms of technology and media clashed with what we consider acceptable behaviour in a human society. Now, with companies like building that are ever more personal, we need to continue to develop our notion of what it means to do the right thing. ours digital tools We believe that a key component of the coming generation of AI-powered technology will be . By plugging our physiological and behavioural data into smart systems, they will be able to understand our moods and learn to respond appropriately. We can look forward to this empathic technology bringing us richer, more rewarding human-machine interaction. But it also gives us plenty to be concerned about. digital empathy Below are some of the main issues that my team and I are considering a lot these days, as our species ventures into an unmapped landscape of increasingly smart, connected technology. Legislation vs Innovation: finding the right level of governance. Social Heuristics: doing ‘the right thing’ by default. Personal Data: new models for ownership & control. Transhumanism: extending rights beyond the flesh. The Business Dilemma: ethically profiting with other people’s data. Addressing each in turn then… 1. Legislation vs Innovation The one thing we know about the future is that we don’t know anything. Nobody can tell you exactly what flavours of human-machine interaction will materialise over the coming years or where exactly to draw the ethical line on them. No doubt our world will eventually be furnished with appropriate legislation, guidance and norms but they will probably follow some early mistakes, not preempt them. A recent example is , which launched here in Europe this year, in response to years of questionable treatment of users’ personal data. A measure like GDPR is important but it is also a relatively small step, following behind the huge technological and social lunges we have been taking as a species. Formal policy is often outdated by the time it is released. GDPR It’s not just that legislation often comes around too late. It may also be useful, even necessary, for the law to stay out of the way in the early stages of disruptive innovation. We’ve seen this with the extent to which the internet has maintained a Wild West-style freedom of access. This may have led to pains like fake news and industry-crushing data piracy, but it has also united, educated and entertained the world like nothing before it. Hence the current stink about preserving , as the world wrestles for a settled position in the long term. net neutrality 2. Social Heuristics I suspect we will see a similar evolution unfold for the kind of empathic technology that my peers and I are developing, which is currently just entering the initial lift in the . A few disparate services have emerged and people are starting to find out what works for them and what doesn’t. Over the next handful of years, riding the coattails of the AI explosion, companies like ours are venturing on empathic tech becoming ubiquitous, bundled as part of bigger packages like smart vehicles, smartphones, smartwatches, smart homes… ‘smart’ anything. During that transitional phase we can’t expect government and law to help keep us on the right path, and perhaps we shouldn’t. Instead, we need to lean on the fuzzier framework of social norms and heuristics. You know, good ol’ human relationships. innovation-adoption curve I fear it would be a waste of energy to lobby people not to use services that they don’t entirely trust from the outset, even though such behaviour should be a given. I know I’m guilty of it. We’ve seen how easily people give up their data in return for entertaining or useful services, especially if they get them cheaper. We saw this with social networks, which are traded for free against our provision of personal data, and now we have to deal with shit like the . Okay, so users should be discerning, but on the flip-side organisations can’t dodge responsibility by punting the bullshit line that their users don’t mind sacrificing a little freedom and privacy to get stuff for free. Cambridge Analytica scandal Now mechanisms like GDPR are standing up to personal data abuse but people have still been burned along the way. Organisations can’t wait for legislation before taking responsibility on their own initiatives to mitigate such invasive incidents. It feels like a total cop-out to say this, but organisations (public and private) who adopt intimate behaviour like physiological or psychological data analysis simply need to . They need to avoid exploiting their users. And us users need to keep our eyes open for the signs of such exploitation, rather than blindly adopting the next shiny feature offered to us. do the right thing 3. Personal Data Some of the principles behind GDPR might provide a good kick-off for the steps we should take towards the next generation of digital rights, rules and ethics. Underlying GDPR is increased empowerment and ownership for the user, with respect to their data. To the individual user, GDPR aims to provide rights over their data, such as to be informed, gain access, and erase it. That’s a good start but what if we extrapolate it further? With a little imagination, perhaps we could work towards a more sweeping regulation framework for our digital lives. Ultimately, every individual user should own their personal data wherever it travels, globally, and have the power to govern how it is used. Of course there are massive practicality issues with this notion of global data ownership. It would not only require huge community support but also some changes to the fundamental architecture of digital services. But technologies like the blockchain are already promising potential solutions, such as digital self-sovereign identity ( ). as neatly explained here 4. Transhumanism 2018 marked the 70th anniversary of the . Things have changed since then. Universal Declaration of Human Rights Just six days before the UDHR was issued, George Orwell submitted his final manuscript for , describing a dystopian future of universal surveillance that has continued to feel more pertinent with each passing decade. In the same year, Manchester University, . It consisted of seventeen instructions. How differently do we need to think about rights now, when each of us carries an incomprehensibly powerful computer in our pocket? What will constitute appropriate behaviour when technology can think for itself? Nineteen Eighty-Four fired up the world’s first electronic stored-program computer It is not so much that we are marching blindly into an age of AI-enabled technology, that the tech is rising up to enshroud us where we stand. Doing nothing won’t keep you away from increasingly smart, complex and pervasive digital systems. Accordingly, any provisions to protect and empower us must be as wide-reaching as the innovation. Perhaps a new declaration of universal rights is needed for the generations that will live with AI and IoT. If so, these rights may need to apply beyond what most people would currently consider ‘human’. Our species has a long history of self-modification, augmenting our natural abilities with technology, from fire and clothing to hearing aids and smartphones. It is easy to promote a different set of ethics for ‘them’ machines as for ‘us’ humans, while we continue to blur the lines between the two. At the same time, with every data-point we generate through our online activities, we sculpt ever more detailed digital versions of ourselves. Thus, with the continued blending of human, cyborg, AI and digital self, we may have to devise a set of ethics that applies to the whole continuum — perhaps eliciting a . Universal Declaration of Transhuman Rights 5. The Business Dilemma We’re a startup, still glaring through rosy lenses at the digital utopia we imagine building for future generations. It’s easy for us to preach and prophesy at this early stage, while technology like empathic artificial intelligence is still nascent. We are only starting to stake out our ethical position on this new ground. But already we face commercially driven challenges to the kind of company we want to be. It’s not easy to say no to clients and projects that could secure your business for the next few months. We’ve done it a few times but it’s financially painful. Additionally, when we publicly define our ethical standpoint in an inherently unknowable future — claims that could affect our reputation or limit our addressable market — we feel vulnerable, exposed. But we’re not alone. Anyone building a business model that is significantly reliant on the storage, analysis or transaction of personal user data, or any other intimate human-machine interaction, cannot ignore the ethical implications of their work. They must draw a line and stay behind it. As scary as it might be to do this, it’s not courageous, it’s just the right thing to do. But take heart, we’ve found that our clients and customers, which are typically huge global brands, appreciate it. They’re run by humans too. And given the choice, many of them prefer the responsible path. Doing the right thing is often good for business. New Society in the Digital Human Age Back in May, our CEO & Co-Founder Gawain Morrison sat on some of the panels at , where members of a global community were gathered to discuss a wide range of issues about rights in the digital age. A few days later, GDPR kicked in. Positive activities like these are playing out against a backdrop of some hugely contentious events like the Facebook scandal and the net neutrality debate. There’s something in the air right now. RightsCon This piece is only intended to be a broad kick-off exercise to extend a conversation to a wider audience. Much more needs to be said, and done. Details need to be fleshed out. Solutions need to be tested, selected and implemented. But we don’t want to leave it any longer. As we continue to expose our machines to increasingly intimate and accurate data about our bodies, minds and actions, our machines are simultaneously creeping further towards our position on the spectrum of human identity. We are plugging ourselves into the Internet of Just-About-Everything, which is making our digital selves smarter, more pervasive and more capable by the day. Our digital selves need our love, and we need to figure out a new paradigm of ethics and rights for our digital future. Further Reading A couple of related stories from us: How to Engineer Trust in the Age of Autonomy Alexa, Hug Me: Exploring Human-Machine Emotional Relations

Digital Humans need Digital Ethics

Hey there, setting up an Ingress Controller on your Kubernetes cluster? After reading through many articles and the official docs, I was still having a hard time setting up Ingress. But after numerous attempts I managed to setup an to forward outside traffic to my in-cluster services, handling HTTP and HTTPS. This writeup is a step by step guide to do this. nginx-ingress-controller Pssst… incase you are a newbie to Kubernetes like me, here is a nice writeup that explains Ingresses. _A lot of people seem confused about how Ingress works in Kubernetes and questions come up almost daily in Slack. It’s…_medium.com Kubernetes Ingress The Scene We will setup a simple “hello-world” api and expose the api using the on a local cluster using . nginx-ingress-controller Minikube TL;DR — is a boilerplate that reflects what is explained. Here Steps Step 1: Creating the service to be exposed Assuming that you already have Kubectl and Minikube setup, let’s deploy our api and expose it within our cluster as a . We will be using a simple api for the purpose of the demo. The source code can be found . hello-world NodePort Service here The config file consists of the deployment and the service. Normally we separate them into individual files. kubectl create -f hello-world.yaml Now you should be able to see the created resources when you run kubectl get all | grep hello-world Step 2: Creating a default backend to be used by the nginx-ingress-controller We need to provide a default backend for the ingress-controller. The is the default service that Nginx falls backs to if it cannot route a request successfully. The needs to satisfy the following two requirements : default backend default backend serves a 404 page at / serves 200 on a /healthz The nginx-ingress-controller project has an example default backend. kubectl create -f default-backend.yaml Step 3: Creating secrets to specify the SSL certificate for Nginx . The specified while generating the SSL certificate should be used as the in your ingress config. We create secrets for the given key, certificate and dhparam files. Use corresponding file names for the key, certificate and dhparam. Create a self-signed certificate using OpenSSL common name host kubectl create secret tls tls-certificate --key <key-file>.key --cert <certificate-file>.crt kubectl create secret generic tls-dhparam --from-file=<dhparam-file>.pem Step 4: Enable ingress on Minikube Minikube versions > ships with Nginx ingress setup as an add-on. It can be enabled by simply running: v0.14.0 minikube addons enable ingress Enabling the add-on provisions the following: a for the Nginx loadbalancer. configMap the . nginx- ingress-controller a that exposes a default Nginx backend pod for handling unmapped requests. service Step 5: Setting up the nginx-ingress-controller Now we create a service for the controller. The service is of type so that it is exposed outside the cluster. LoadBalancer The config consists of the deployment and service for the nginx-ingress. The following can be observed from the config : The secret for the and are passed as args. default SSL certificate default-backend-service The image is used. I have tried the later beta releases. This seems to be a more stable for our usecase. nginx-ingress-controller:0.9.0-beta.5 The secret is mounted on a volume to be used by the controller. tls-dhparam Create the controller by running: kubectl create -f nginx-controller.yaml We should be able to see the created resources with the exposed IP address after a few seconds. To get the IP on Minikube run. minikube service nginx-ingress --url Running a request to the exposed endpoint should give us a response from the as we still haven’t configured our ingress to point to our hello-world api. Curl default-backend curl <port> http://<nginx-service-IP>: default backend - 404% Step 6: Configure Ingress rules Coming to the part where we will be spending most of our time. We provide the forwarding rules to the ingress. We use annotations here to pass configuration params to the underlying ingress-controller, Nginx in our case. You can find more about annotations . here nginx.org/ssl-services is used to specify the service that is to be load balanced using HTTPS We specify the hosts, paths and their corresponding service handlers. kubectl create -f ingress.yaml We now have an Nginx web server configured that routes traffic for to our configured . It falls back to the for unhandled requests. api.sample.com hello-world-svc default-backend service Also you might want to update file to resolve your host to your minikube IP. Assuming your Minikube IP is Your entry should look like. /etc/hosts 192.168.99.101 192.168.99.101 api.sample.com You should be able to access the exposed endpoints via https. GET api.sample.com/:namePOST api.sample.com/:namePUT api.sample.com/:name Adding the annotation to the config enables traffic through HTTP and HTTPS. ingress.kubernetes.io/ssl-redirect: “true” ingress.yaml Conclusion Ingress does allow you to configure multiple Virtual Hosts, Sticky sessions, Path rewrites and also custom configs, providing a powerful, flexible routing mechanism for Kubernetes. For more info on nginx-ingress-controller visit https://github.com/nginxinc/kubernetes-ingress A similar procedure can be used to deploy to AWS, GKE instead of Minikube. Kubernetes and Ingress in particular is constantly evolving I will try my best to keep this updated. Boy Scout Oath. Good Reads https://medium.com/@Oskarr3/setting-up-ingress-on-minikube-6ae825e98f82 http://danielfm.me/posts/painless-nginx-ingress.html https://daemonza.github.io/2017/02/13/kubernetes-nginx-ingress-controller/ Hope you enjoyed reading this as much as I enjoyed writing it. If you think this will be of help to someone? Do not hesitate to share. If you liked it, tap the clap below so other people will see this here on Medium. Don’t forget to show some love by following the blog! Added RBAC in the example setup. Thanks to for his contribution. *Update on 11 November 2018* Jens Madsen

Setting up Nginx Ingress on Kubernetes

The main aim of this piece is to grasp the workings of mapped types in and explore various typical scenarios. I frequently come across mapped types in my work. In this guide, I'll explain how mapped types can be utilized and the assistance provided by utility types. TypeScript Let’s say, that you have an object, that describes some entity, like a person. interface Person {
	name: string;
	secondName: string;
	age: number;
    description: string;
	email: string;
    id: number;
} And you want to have a , that stores what component to render for each field when rendering Person on a page. For that, we might use something called a mapped type. hashmap type PersonInputType = {
  [key in keyof Person]: () => React.JSX.Element;
} Here, returns the union type of all the keys in interface. keyof Person What that means is, that type looks like this: PersonInputType type PersonInputType = 'name' | 'secondName' | 'age' | 'description' | 'email'; Now, suppose that you don’t have components mapped out for each property from Person. For example, there is probably no component should be rendered for the id key. One thing you can do is, add an optional parameter. type PersonInputType = {
  [key in keyof Person]?: React.Component;
} But what if you want everything to be mapped out except for ID. One way to go about that is to use Pick from Typescript to list all the keys from the object we need. type PersonInputType = {
  [key in keyof Pick<Person, 'name' | 'secondName'>]: () => React.JSX.Element;
} But it would be annoying to list all the needed keys just so one element would be excluded. For that, we can use Omit. type PersonInputType = {
  [key in keyof Omit<Person, 'id'>]: () => React.JSX.Element;
} Now, that looks better. Let’s continue with utility types. I’ve demonstrated that you can make properties from the original type by using ‘?’ at the end. Also, you can use a Partial utility type. For example: type PersonInputType = {
  [key in keyof Partial<Person>]: React.Component;
} Partial makes every key from that object optional. Now what if, the situation was reversed? Some of the Person properties would be optional, but in the mapped type, you need all types to be required and defined. Then we can use Required. type PersonInputType = {
  [key in keyof Required<Person>]: React.Component;
} Let’s also consider . As the name suggests typeof returns the type of an object. When it might be useful to use both keyof and typeof? For example, you have an enum, describing app states. typeof enum AppStates {
  'READY' = 'READY',
  'LOADING' = 'LOADING',
  'ERROR' = 'ERROR'
} And now you need a hashmap to specify text messages for each state. How to use these keys from the enum? You can do the following type AppStatesInfo = {
  [key in keyof typeof AppStates]: string;
} Here, here returns the typeof an object, and we already discussed and now we can combine both. You can also avoid using keyof and typeof in this case and just write it shorter: typeof keyof type AppStatesInfo = {
  [key in AppStates]: string;
} Does the same thing. The one problem here might be, that enums a lot of times are capitalized, no specific reason, just sort of a convention. But keys in a hashmap aren’t. We can again come back to utility types, and make keys lowercase. type AppStatesInfo = {
  [key in Lowercase<AppStates>]: string;
} I think this might cover a lot of everyday cases. Mapped types help you derive types from interfaces, objects, and enum you have in your application to connect one type to others.

Working With Mapped Types in TypeScript

TypeScript first appeared in October 2012, and it was one of those tools that at first I didn’t like. Mapped types first version arrived in TypeScript 2.1, which was released nearly four years after the first release. Looking at Google Trends, we can see how interest started to grow in 2015 (Visual Studio Code release date) and then really took off in 2016. Mapped types and Angular 2 were released in 2016, which should account for that growth. The Basics What are mapped types anyway? They are just a way to avoid defining interfaces over and over. You can base the type you need on another type or another interface and save yourself a lot of manual work. You can use the TypeScript Playground app below to run all the snippets included in this article. It’s definitely a playful tool where you can practice and improve your TypeScript skills. Let’s start seeing some TypeScript in action. Point {
  x: ;
  y: ;
} interface number number If you want to extend this interface, you can do the following. Point3D Point {
  z: ;
} interface extends number But you can use mapped types as well: Point3D = Point & { z: }; type number Cool, isn’t it? Although in this scenario we are not really showing anything that can’t be done with interfaces, are we? We are just getting started, though. That being said, it’s preferable to use interfaces in this particular scenario. This is just a showcase so you can see its versatility. You can easily combine two types, as follows: A {
  a: ;
} B {
  b: ;
} AB = A & B; interface string interface string type Here is where it really starts to shine. We can see how easy to do and readable this becomes. Before diving a bit deeper, let’s look at the primitive introduced in version 2.1. It looks scary at first, but it’s super intuitive: It will just expose the keys of any given interface/type through a union. Those are known as Typescript Union Types. keyof Book {
  author: ;
  numPages: ;
  price: ;
} BookKeys = keyof Book; interface string number number type // 'author' | 'numPages' | 'price'; Built-In Utility Types TypeScript does ship with a lot of utility types, so you don’t have to rewrite those in each project. Let’s look at some of the most common: Book {
  author: | ;
  numPages: ;
  price: ;
} Article = Omit<Book, >; BookModel = Readonly<Book>; book: BookModel = { author: , numPages: , price: };

book.author = interface string null number number // Article is a Book without a Page type 'numPages' // When it's using functional programming to use immutable objects type const 'Jose Granja' 2 0 'Robert Smith' // this will raise an error since all the properties are readonly — those are the most common. Omit, Partial, Readonly, Exclude, Extract, NonNullable, ReturnType You can check out all of them in more detail . here You are not limited to using only one at a time but can combine them as much as you need, and this is where the fun really starts. AuthoredBook = Omit<Book, >
  & NonNullable<Pick<Book, >>; type 'author' 'author' // this result in a type with a "author: string" type. Author is not nullable anymore Build Your Own Utility Types Let’s look first at how TypeScript does its utilities. We’ve used Omit, which was introduced in TypeScript 3.5. It’s a combination of two other utilities. Before starting, let’s cover how to access interface/type properties. Omit<T, K keyof T> = Pick<T, Exclude<keyof T, K>>; Exclude<T, U> = T U ? never : T; Pick<T, K keyof T> = { [P K]: T[P]; }; // definition of Omit type extends //definition of Exclude type extends //definition of Pick type extends in Pretty easy when you break it down into small units, isn’t it? does play a big role here since it will be making sure that the properties we wanted to omit to belong to the type/interface we want to be omitted. keyof Let’s create our first custom utility. Let’s say we want to define an object where all key values are from a particular type. GenericString = { [key: ]: } type string string Pretty easy, right? Let’s use Generics and make the string type configurable. GenericObject<T> = { [key: ]: T } type string Let’s make that key type configurable: GenericKeyObject<K keyof , T> = {
  [P K]?: T;
}; type extends any in Let’s see that in action. BooleanList = GenericKeyObject< , >; countriesVisited: BooleanList = {
  France: ,
  Italy: }; VisitableCountries = | | ; CountriesChecklist = GenericKeyObject<VisitableCountries, >; countriesVisitedCurrentYear: CountriesChecklist = {
  France: ,
  Hungary: }; countriesVisitedLastYear: CountriesChecklist = {
  France: ,
  Belgium: }; type string boolean const true true // let's take it a step further type 'Hungary' 'France' 'Germany' type boolean const true true const true true // this fails at compile time since Belgium is no in the list of visitable countries. What works for me when building complex mapped types is starting simple and then incrementally adding complexity. You might find that starting too complex is frustrating. Level-Up Your Utility Types and Usage It’s easy to build a very simple and trivial example with mapped types. Let’s now dig a bit deeper. Let’s check out the never primitive first, though. It was introduced in version 2.0. It indicates that the value will never occur. HttpResponse<T, V> {
  data: T;
  included: V;
} StringHttpResponse = HttpResponse< , never>; interface // let's use never type string // What you are here doing is banning StringHttpResponse consumers     from using the included property as even in other usages of HttpResponse it might be populated it is not in this particular response. You are communicating that this property must be ignored Let’s now check out the primitive added on version 2.8. infer As you know, TypeScript relies heavily on type inference. You can refresh your memory . here What this primitive does is it empowers your mapped types with inference. Now you can extract and infer a type inside a conditional type. infer What is a conditional type? It’s just an expression for selecting one of two possible types based on a condition expressed as a type relationship. T U ? X : Y extends Let’s put all that into play. ResponseData {
  data: [];
  hasMoreItems: ;
} getData = (): <ResponseData> => { data = {
    data: [ , , , ],
    hasMoreItems: } .resolve(data);
} interface string boolean const Promise const 'one' 'two' 'three' 'four' false return Promise What if you wanted to unpack the type from the returned by ? Simple: Create your own utility using . Promise getData infer Unpacked<T> = T (infer U)[]
  ? U
  : T (...args: []) => infer U
  ? U
  : T <infer U>
  ? U :
  T; PromiseResult = Unpacked<ReturnType< getData>>; FunctionResult = Unpacked< >; type extends extends any extends Promise type typeof // PromiseResult = ResponseData type => () string // FunctionResult = string What’s happening there? You are just inferring the type if T extends a or a ; otherwise, you are just returning the given type . Promise Function T Let’s do one last one as a bonus. Let’s do an interface that will return if the object is empty and if the type has some properties. Yes, we can do crazy stuff like that in TypeScript. true false Empty<T {}> = {} Required<T> ? : ; isEmpty = Empty<{}>; isNotEmpty = Empty<{ name: }>; type extends extends true false type // true type string // false Why is that useful? You can combine the mapped type Empty with any conditional infer/mapped type to create more custom types. So we just created a tool that will help us create more mapped types. HttpDataReponse<T> = Empty<T> ? never
  : T; ClassReponse = HttpDataReponse<{}>; BookReponse = HttpDataReponse<{ author: }>; type extends true type // result be never type string // result be { author: string } Pretty crazy what you can achieve, isn’t it? The limit is your imagination. TypeScript Tuples One of the last additions and improvements was Tuples. Tuples are arrays where the number of elements is fixed. Their type is known and they are not necessarily the same type. arrayOptions: [ , , ];

arrayOptions = [ , , ]; arrayOptions = [ , , ]; { .log(data);
}

printConfig(arrayOptions[ ]); let string boolean boolean 'config' true true // works true 'config' true // does not work ( ) function printConfig data: string console 0 is very useful. There’s one scenario where it’s very common to find it nowadays: React Hooks. The Hooks implementation normally returns an array with the result plus functions, and having that array typed is indeed very handy. Tuple Wrap Up And just like that, we are done. We started with some basic mapping and ended up with some Typescript advanced types. Mapped types are by far the most fun feature in TypeScript. They serve as a good showcase of how powerful and dynamic TypeScript can be. If you were hesitant to try TypeScript, I hope my article gave you that very last push you needed. Even if you are not planning to use it now, it is wise to know what’s out there in case it comes in handy in the near future. For those heavy TypeScript users, I hope you can agree on how much fun mapped types are once you get the hang of them. More TypeScript content will be coming in the future — Cheers! Also published at https://medium.com/better-programming/mastering-typescripts-mapped-types-5fa5700385eb

Exploring TypeScript Mapped Types Together

Android, as we all know is based, on top of Linux. Whenever you install an Android app, you are asked to grant certain permissions, ranging from access to gallery, contacts, call logs, camera, location, microphone to body sensors etc. However, have you wondered how these permissions are actually understood and enforced at the system's level? Every app has it's own set of requested permissions so how are these permissions assigned to the app. In Android, app is nothing but a process. According to Linux world definition: "A is a program in execution, and each process has its own address space, which comprises the memory locations that the process is allowed to access. A process has one or more of execution, which are sequences of executable instructions: a process has just one thread, whereas a process has more than one thread. process threads single-threaded multi-threaded Threads within a process share various resources, in particular, address space. Accordingly, threads within a process can communicate straightforwardly through shared memory. Of interest here is that different processes, by default, do share memory." not (Source: ) https://opensource.com/article/19/4/interprocess-communication-linux-storage This implies that whenever an app is launched, a process should be forked (from Zygote) with a certain set of permissions and the same shall be abided through while communicating to other apps (processes) through Inter Process Communication (IPC, which is facilitated through Binder in Android, more about it in some other post). Makes sense? Now having set this intent, let's reverse our point of view and see what happens when the app gets installed first. Heard of Package Manager? As per official Android documentation, "It is a class for retrieving various kinds of information related to the application packages that are currently installed on the device." Whenever you install an app, Package Manager parse the package(APK) file and display confirmation dialog box. When user press OK button, Package Manager call method named "installPackage" Somewhat like this happens,  in Package Manager Service. Add a package to the queue for the installation process Determine the appropriate location of the package installation Determine installation Install / Update new A copy of the apk file to a given directory Determine the UID of the app Request to installd daemon process Create the application directory and set permissions Extraction of dex code to the cache directory To reflect and packages.list / system / data / packages.xml the latest status Broadcast to the system along with the name of the effect of the installation is complete package  Intent.ACTION_PACKAGE_ADDED: If the new ( Intent.ACTION_PACKAGE_REPLACED): the case of an update Permissions are assigned to each application (as identified by a unique ) at install time by the system service. The package manager maintains a central database of installed packages, both preinstalled and user-installed, with information about the install path, version, signing certificate, and assigned permissions of each package, as well as a list of all permissions defined on a device. package name package manager This package database is stored in the XML file , which is updated each time an application is installed, updated, or uninstalled. /data/system/packages.xml Whether a permission is granted or not depends on its protection level which ranges from normal, dangerous, signature, signatureOrSystem. Permissions are enforced at various layers in Android. Higher-level components such as applications and system services query the package manager to determine which permissions have been assigned to an application and decide whether to grant access. Lower-level components like native daemons typically do not have access to the package manager and rely on the UID, GID, and supplementary GIDs assigned to a process in order to determine which privileges to grant it. Access to system resources like device files, Unix domain sockets (local sockets), and network sockets is regulated by the kernel based on the owner and access mode of the target resource and the UID and GIDs of the accessing process. Remember GIDs from Linux world? Here's a summary: Every file in Unix has the following attributes − − The owner's permissions determine what actions the owner of the file can perform on the file. Owner permissions − The group's permissions determine what actions a user, who is a member of the group that a file belongs to, can perform on the file. [GIDs] Group permissions − The permissions for others indicate what action all other users can perform on the file. Other (world) permissions More here: https://www.digitalocean.com/community/tutorials/an-introduction-to-linux-permissions When the application is started, the process’s UID and GID are set to the application UID assigned by the installer (the package manager service). If additional permissions have been assigned to the application, they are mapped to GIDs and assigned as supplementary GIDs to the process.Permission to GID mappings for built-in permissions are defined in the file. /etc/permission/ platform.xml Tadaaaaa, here it is: There's another interesting file which is android_filesystem_config.h Android does not have an file, so the mapping from group names to GIDs is static and defined in this header file. It defines the owner, access mode, and associated capabilities (for executables) of core Android system directories and files. (We should dig into this file separately someday) /etc/group So so so, we know what happens when an app is installed, where are the permissions saved and how are they mapped to specific GIDs (in case of predefined permissions), but how are they enforced? What actually happens when you launch the app i.e a process gets spawned? Have a look at this code snippet: As shown here, the child process first sets its supplementary GIDs (corresponding to permissions) using setgroups(), called by setgroupsIntarray() at ➊. Next, it sets resource limits using setrlimit(), called by setrlimitsFromArray() at ➋, then sets the real, effective, and saved user and group IDs using setresgid() ➌ and setresuid() ➍ The child process is able to change its resource limits and all process attributes because it initially executes as root, just like its parent process, . zygote After the new process attributes are set, the child process executes with the assigned UIDs and GIDs and cannot go back to executing as root because the saved user ID is not 0. After setting the UIDs and GIDs, the process sets its capabilities using capset(), called from setCapabilities() ➎. Then, it sets its scheduling policy by adding itself to one of the predefined control groups ➏. Hence, the kernel and system daemons use these process identifiers to decide whether to grant access to a particular system resource or function. Access to regular files, device nodes, and local sockets is regulated just as it is in any Linux system. One Android-specific addition is requiring processes that want to create network sockets to belong to the group is an explicit permission in Android, remember?) inet (INTERNET While Binder is the preferred IPC mechanism in Android, lower-level native daemons often use Unix domain sockets (local sockets) for IPC. Because Unix domain sockets are represented as nodes on the filesystem, standard filesystem permission can be used to control access. References Android Security Internals by Nikolay Elenkov For more such discussions let's connect on Twitter @4ditiBhatnagar Previously published at https://www.digitised.in/post/how-are-android-permissions-mapped-at-kernel-s-level

How Android Permissions Mapped at Kernel's Level

React-SASS-PM2-EC2-Production-App mapped with a custom domain and secured with SSL layer.

is a popular technology for efficient and scalable data storage and retrieval. However, maintaining its performance and data integrity requires a crucial practice called reindexing. Indexing is the initial process of adding data to Elasticsearch, while reindexing is essential for maintaining data accuracy and optimizing search performance. Elasticsearch Whether you're a seasoned Elasticsearch user or just beginning your journey, understanding reindexing is important for maintaining an efficient Elasticsearch cluster. In this article, we'll delve into the essentials of Elasticsearch reindexing, answering when it's necessary, how to trigger it, and the best practices to get the most out of your Elasticsearch cluster. Understanding Elasticsearch Reindexing In Elasticsearch, reindexing helps maintain data integrity and increase performance. Put simply, it's the process of copying data from one index to another. While this might sound straightforward, if not done correctly it can cause issues such as slow data retrieval or even incorrect results Imagine your Elasticsearch indices as well-organized libraries. Over time, books might need to be updated, rearranged, or even replaced. Reindexing is akin to rearranging the library shelves or updating the books to keep everything in order. Without it, your library can become disorganized, leading to slower searches and potential inaccuracies in your data. This analogy underscores the importance of understanding reindexing in Elasticsearch. It's not just about copying data; it's about maintaining the integrity of your "library" for efficient searching and retrieval. Let’s take a look at and how to keep on top of it. when reindexing is required When is Reindexing Necessary? Reindexing becomes essential when changes occur in your Elasticsearch data models or mappings, or when you're seeking performance enhancements. In this section, we’ll look into these scenarios in more detail to understand the nuances around why reindexing is required. Structural Changes in Data Models Structural changes in data models refer to modifications in how data is structured within Elasticsearch. These changes can include things like adding or removing new fields or altering data types of existing fields. Introducing new fields often requires a reindex to ensure Elasticsearch knows how to efficiently search for data stored in that field. Modifying data types requires a new index altogether as you cannot change data types in place. Once the new mapping has been created for the modified data type then the data needs reindexing. These structural changes require reindexing due to Elasticsearch's schema-on-write approach. Elasticsearch indexes data as it is ingested, and any changes to the data structure can lead to inconsistencies between existing data and data written with the new schema. As a result, without reindexing, search queries may yield unexpected or inaccurate results due to the schema mismatch of data items. This can have an impact on both data accuracy and search performance. Mapping Updates or Changes Mappings serve as the blueprint for how data is indexed and queried in Elasticsearch. When these mappings are modified then reindexing is usually required. Mappings define the data types and properties of fields within Elasticsearch. Any change to these mappings affects how data is indexed, stored, and retrieved. For instance, altering a text field to a date field fundamentally changes how data is processed and queried. Elasticsearch enforces data consistency based on mapping definitions. Changes to mappings can lead to inconsistencies between existing data and the updated schema if the data is not reindexed. When mappings are modified, particularly if it involves changing data types or field properties, backfilling also becomes important. Backfilling is the process of retroactively populating or updating existing data to align it with a new schema or data structure. This means that the existing data can still be queried efficiently and accurately after the mapping change. Performance Enhancements and Index Optimizations Reindexing isn't just a routine maintenance task, it's a powerful tool for optimizing search performance within Elasticsearch. For example, reindexing allows you to modify the number of shards in an index. Adjusting the shard count, or resharding, can distribute data more evenly, preventing uneven workloads on specific nodes to improve search performance. Reindexing can also be used to consolidate indices together. Let's say you have multiple small indices that share the same data structure and are frequently queried together. Reindexing can consolidate them into a single, larger index. This reduces the overhead of managing numerous small indices which can in turn enhance search speed. Finally, reindexing can be used to improve routing. By reindexing and applying routing strategies effectively, you can route queries to specific shards, minimizing the number of shards that need to be searched. This targeted approach can significantly speed up search queries if your data is frequently searched by specific keys such as a user ID. Upgrading Your Cluster When upgrading from Elasticsearch version 6.X to 8.0 (current major version) and beyond, you may need to reindex any indices that were created in version 6. Elasticsearch's data structures and underlying mechanisms changed significantly between these versions requiring reindexing for compatibility and optimal performance. The reindexing process ensures that data aligns with the updated structure and new functionality to ensure you can migrate seamlessly from old to new. Elasticsearch recommends using their upgrade assistant to help with this process. How to Trigger a Reindexing Operation Reindexing in Elasticsearch is made possible through the Elasticsearch Reindex API. The Reindex API serves as the bridge between your existing index and the new index you want to create or modify. Its primary purpose is to enable the efficient transfer of data from one index to another, on top of this, you can also: Selectively copy documents from the source index to the target index. Apply complex data transformations, such as field renaming or type conversions. Filter data based on specific criteria. Control the indexing process with options like throttling and refresh intervals. Before using the Reindex API, ensure that the target index, where you want to move or transform your data, is created and properly configured. To trigger reindexing, you then need to formulate a POST request to the endpoint, specifying the source and target indices, as well as any desired transformations or filters. An example reindex POST request could look as follows. _reindex POST /_reindex
{
  "source": {
    "index": "source_index"
  },
  "dest": {
    "index": "target_index"
  },
  "script": {
    "source": "ctx._source.new_field = 'transformed value'"
  },
  "query": {
    "term": {
      "category.keyword": "example"
    }
  }
} Once your request is built you can send the request to Elasticsearch, initiating the reindexing process. Elasticsearch will start copying data from the source index to the target index, following your defined instructions. Once the reindexing is complete, thoroughly test the data in the target index to ensure it aligns with your expectations. For example, you can compare the field mappings between the source and target indices to confirm that fields were mapped correctly during reindexing. You could also retrieve a sample of documents from both the source and target indices and compare them to verify the data was reindexed accurately. Best Practices for Reindexing When reindexing within Elasticsearch, you should look to follow these best practices to ensure the reindexing procedure is smooth with no data loss and little impact on existing cluster operations. Prioritize Data Backup Before initiating any reindexing activity, it is important to back up your cluster. This precautionary step acts as a safety net, offering a way to revert to the original state should any unexpected issues arise during the reindexing process. The source index should still exist after reindexing, however, it's a fundamental principle to always have a reliable copy of your data before making significant changes. Conduct Reindexing in a Controlled Environment First To mitigate potential risks and challenges during reindexing, it is advisable to perform the operation in a pre-production environment first. By doing so, you can identify and address any unforeseen issues without affecting the production system. Once the procedure has been completed and verified in the pre-production environment, it can then safely be run in production. Monitor Resource Usage It is important to monitor system resources during reindexing to prevent strain on your infrastructure. Reindexing can be resource-intensive, especially for larger datasets. Keeping a close eye on CPU, memory, disk usage, and network activity can help optimize resource allocation, ensuring the process runs efficiently without causing performance bottlenecks. To check resource usage you can use the node stats API. GET /_nodes/stats This will return a response that looks as follows. {
  "_nodes": {
    "total": 2,
    "successful": 2,
    "failed": 0
  },
  "cluster_name": "my_cluster",
  "nodes": {
    "node_id1": {
      "name": "node_name1",
      "process": {
        "cpu": {
          "percent": 30,
        }
      },
      "jvm": {
        "mem": {
          "heap_used_percent": 40.3,
          "heap_used_in_bytes": 123456789,
          "heap_max_in_bytes": 256000000
        }
      }
    },
    "node_id2": {
      "name": "node_name2",
      "process": {
        "cpu": {
          "percent": 50,
        }
      },
      "jvm": {
        "mem": {
          "heap_used_percent": 60.8,
          "heap_used_in_bytes": 210987654,
          "heap_max_in_bytes": 256000000
        }
      }
    }
  }
} If you find reindexing is too intensive, you can throttle the process by setting the parameter when submitting the reindex request. This will add a sleep between batches for the number of seconds set by the parameter, to provide a cooldown period between batches. requests_per_second Verify and Validate Results Once the reindexing is complete you should verify the data in the target index to ensure it looks as expected. This validation process should encompass a variety of tests including document counts, field mappings, and search queries. Alternative Solutions Elasticsearch has undoubtedly established itself as a prominent solution in the NoSQL search and analytics space. However, it's worth exploring alternative solutions that offer unique approaches to data indexing and querying, particularly one like Rockset. Rockset is a to Elasticsearch and offers a different perspective on indexing and querying data. Unlike Elasticsearch's schema-on-write approach, Rockset allows schemaless ingestion. Data can be ingested and queried without the need for upfront schema definition, offering more flexibility in handling ever-evolving datasets without the need for reindexing. cloud-native alternative In the area of index management, Rockset benefits from its model where a row index, a column index, and a search index are all created automatically for the data as it is ingested. This contrasts with Elasticsearch, where indexes are created by users and structural changes often necessitate time-consuming reindexing procedures. converged indexing While Elasticsearch remains a robust solution for various use cases, exploring alternatives like Rockset may be useful, especially if you find reindexing in Elasticsearch becoming a frequent activity. Conclusion Reindexing is a fundamental process in Elasticsearch and is important for maintaining the efficiency and accuracy of search results as data structures evolve. If you find that reindexing is becoming a constant time burden for your team it might be worth exploring alternative solutions like Rockset. Rockset offers a more streamlined index management process that enables developers to concentrate on more value-add activities.

Understanding Elasticsearch Reindexing: When to Reindex, Best Practices and Alternatives

ইলাস্টিকসার্চ রিইন্ডেক্সিং বোঝা: কখন পুনঃসূচীকরণ করতে হবে, সর্বোত্তম অনুশীলন এবং বিকল্প

Neuindizierung von Elasticsearch verstehen: Wann eine Neuindizierung erfolgen sollte, Best Practices und Alternativen

Comprensión de la reindexación de Elasticsearch: cuándo reindexar, mejores prácticas y alternativas

Comprendre la réindexation Elasticsearch : quand réindexer, bonnes pratiques et alternatives

इलास्टिकसर्च रीइंडेक्सिंग को समझना: कब रीइंडेक्स करना है, सर्वोत्तम अभ्यास और विकल्प

Elasticsearch の再インデックスを理解する: 再インデックスを行うタイミング、ベストプラクティス、代替手段

Elasticsearch 재인덱싱 이해: 재인덱싱 시기, 모범 사례 및 대안

Compreendendo a reindexação do Elasticsearch: quando reindexar, práticas recomendadas e alternativas

Понимание переиндексации Elasticsearch: когда проводить переиндексацию, лучшие практики и альтернативы

Elasticsearch Yeniden İndekslemeyi Anlamak: Ne Zaman Yeniden İndekslenmeli, En İyi Uygulamalar ve Alternatifler

Tìm hiểu về lập chỉ mục lại Elaticsearch: Khi nào nên lập chỉ mục lại, các phương pháp hay nhất và giải pháp thay thế

了解 Elasticsearch 重新索引：何时重新索引、最佳实践和替代方案

Human Augmentation in Meme Analysis: Learnings and Challenges

4 Case Studies in UX Audit: Insights and Best Practices for Improving User Experience

Authors:
(1) Yelena Mejova, ISI Foundation, Italy;
(2) Arthur Capozzi, Università degli Studi di Torino, Italy;
(3) Corrado Monti, CENTAI, Italy;
(4) Gianmarco De Francisci Morales, CENTAI, Italy. Table of Links Introduction Background and Related Work Methods Results Discussion and References 3 METHODS 3.1 Data collection To examine the use of memetic engagement by Ukraine during the first 8 months of the 2022 conflict, we begin with a large collection of tweets matching war-related keywords (see Appendix A) spanning from 27 February 2022 to 12 October 2022. By examining this collection, we identify three prominent accounts: (1) @Ukraine: self-described as “the official Twitter account of Ukraine”, this verified account is labeled as an “Ukraine government organization” by Twitter. It posts war-related and political updates about Ukraine. (2) @uamemesforces: self-described as the “Source of the best Ukrainian memes”, this unverified account states as its goal ”to convey the truth about what is happening now in Ukraine with the help of memes”.[8] (3) @DefenceU: or “Defense of Ukraine”, is the “Official page of the Ministry of Defense of Ukraine”. Like @Ukraine, this verified account is described by Twitter as a “Ukraine government organization”. Its posts concern battlefield updates and news. We select the accounts @Ukraine and @DefenceU because of their large following (at the end of the collection period), because they are official accounts not associated with individuals or specific media outlets, and because of the focus on the conflict (many popular Ukrainian accounts are by non-relevant celebrities). Additionally, we select @uamemesforces, the most popular Ukrainian unofficial account that posts memes about the conflict. Note that we are limited in the number of accounts we can study due to the labor-intensive labeling process. We retrieve all of the posts for these accounts via Twitter Timeline API. We treat each post with media content as a potential meme, no matter the format. To ensure preserving content posted by these accounts, we also download the images associated with the posts and the users who retweeted or liked the post (see Table 1 for summary statistics). We associate each user with a country in the GeoNames database via their location field (a free-text field optionally filled by the user). Considering only tweets with media, out of 586 042 users, 44% are successfully mapped to a country. We retain only countries with at least 1000 geolocated retweeting users for geographic analysis. In order to explore the relationship between Ukrainian memes and each country’s actions towards the conflict, we use the Ukraine Support Tracker data from the Kiel Institute for the World Economy (downloaded on 20 June 2023), which “quantifies military, financial, and humanitarian aid transferred by governments to Ukraine since the end of diplomatic relations between Russia and Ukraine on January 24, 2022”.[9] The dataset provides a quantitative measure of a country’s aid to Ukraine. Finally, to examine the attitude of each country’s population towards Ukraine, we use the Eurobarometer STD98 survey which took place in winter 2022-2023 in 30 European countries [22]. Specifically, we use use QE2, answer 6: “To what extent do you agree or disagree with: providing financial support to Ukraine.” 3.2 Annotation To understand the visual and narrative attributes of the captured data, all authors perform a manual annotation of a random selection of the tweets. We use all of @Ukraine tweets and a random sample of roughly 40% of those from the other two accounts are selected for analysis, for a total of 1063 tweets (last column of Table 1). We remove self-replies (an account replying to its own post) which have no retweets of their own. Guided by previous literature, we compose a codebook to capture visual and narrative aspects of the content. First, we adopt the significant features of the content characterization framework proposed by Ling et al. [41], which is used to model the virality of political memes. These attributes include: (1) Number of panels: multiple or single; (2) Type of image: photo, screenshot, or illustration; (3) Scale: close-up, medium shot, long shot, other; (4) Type of subject: object, character, scene, creature, text, other; (5) Main attribute of the subject (if character): facial expression, posture, poster (6) Character emotion (if character): positive, negative, or neutral; (7) Contains words: whether image itself (not tweet caption) contains words. Second, we employ the narrative framework by Karpman [35] later extended by de Saint Laurent et al. [18]. It defines two key dimensions to characterize a narrative: moral quality (benevolent or malevolent) and power (strong or weak), thus resulting in four character archetypes: heroes (benevolent, strong), victims (benevolent, weak), villains (malevolent, strong), and fools (malevolent, weak). We also label the actors mentioned in these narratives (as an open category, guided by an initial set of main actors in the conflict, such as Zelensky and Putin). We further contextualize the narratives by their emotional appeal [8], in particular humor, pride, fear, outrage, and compassion (the label was originally open, but the labelers coalesced on this set). Finally, we record whether there is a specific intent in terms of a call to action or information sharing. Note that, as much as possible, we try to label the narratives as intended from the point of view of the posting account (although some biases may creep in, as we discuss in Section 5). Appendix B reports the full codebook. Using this literature-driven codebook, all authors of this manuscript perform a deductive coding of the selected posts (for more on such process see Linneberg and Korsgaard [42]). We rely on Google Translate to translate non-English language content. All coders first annotated a selection of 50 posts, discussed insights and disagreements, and came up with standard labels for emotional appeal, intent, and actor (though the label remained open). Subsequently, the rest of the posts are annotated by one author each, with uncertain cases discussed collectively. Appendix C reports the inter-annotator agreement on a selection of 48 posts (sampled from each account). On average, the agreement is 0.750 for @Ukraine, 0.604 for @uamemesforces, and 0.667 for @DefenceU (with a Krippendorff’s alpha of around 0.65 for all accounts and tasks), which is high considering the subjective nature of the tasks, and that some features were open and could have multiple labels. The annotated dataset is available at https://github.com/corradomonti/ukranian-tweets. 3.3 Popularity model Using the data collected and annotated as per the previous sections, we construct models to find whether there are trends in (𝑖) what kind of content becomes more popular, and (𝑖𝑖) who it reaches. Specifically, we use linear regression to model the log-transformed number of retweets with the content variables outlined above as independent variables. As the three accounts have posted a vastly different number of tweets, we weigh the data points (tweets) inverseproportionally to their representation in the dataset, so that each account weighs equally on the outcomes. We build several versions of the model to ascertain the benefit of each class of variables: visual [41], actor, emotion, intent, and narrative. A baseline model simply uses the identity of the author (i.e., group fixed effects), the number of followers of that account (log transformed) as a proxy for the potential audience, and the number of days from the invasion to account for changing interest in the topic over time. We then choose the best model by the Bayesian Information Criterion (BIC)—a model selection metric that captures both unexplained variation in the dependent variable and the number of explanatory variables. The coefficients of this model reveal the associations between these variables and the virality of the content. Next, we group retweets by the country of the user (those who can be geolocated) to understand the preferences of users who spread these messages. We enrich our characterization of the relationships between each country and Ukraine by considering the amount of financial assistance the country provides to Ukraine (normalized by the country’s GDP) or by their opinion on this topic (via the Eurobarometer survey). As mentioned above, we consider these measures as different proxies of support for Ukraine’s military efforts. First, we examine the retweeting rate (normalized by population). Then, we compare the narrative preferences to the amount of support for Ukraine: are there narratives associated with increased support for Ukraine? We operationalize this preference as the log odds of users from a country retweeting content having a specific narrative. Finally, we examine the geographical distribution of the retweeting rate and narrative preferences across Europe by plotting these on choropleth maps. [8] https://www.patreon.com/uamemesforces [9] https://www.ifw-kiel.de/topics/war-against-ukraine/ukraine-support-tracker This paper is available on arxiv under CC 4.0 license. Authors: (1) Yelena Mejova, ISI Foundation, Italy; (2) Arthur Capozzi, Università degli Studi di Torino, Italy; (3) Corrado Monti, CENTAI, Italy; (4) Gianmarco De Francisci Morales, CENTAI, Italy. Authors: (1) Yelena Mejova, ISI Foundation, Italy; (2) Arthur Capozzi, Università degli Studi di Torino, Italy; (3) Corrado Monti, CENTAI, Italy; (4) Gianmarco De Francisci Morales, CENTAI, Italy. Table of Links Introduction Introduction Background and Related Work Background and Related Work Methods Methods Results Results Discussion and References Discussion and References 3 METHODS 3.1 Data collection To examine the use of memetic engagement by Ukraine during the first 8 months of the 2022 conflict, we begin with a large collection of tweets matching war-related keywords (see Appendix A) spanning from 27 February 2022 to 12 October 2022. By examining this collection, we identify three prominent accounts: (1) @Ukraine: self-described as “the official Twitter account of Ukraine”, this verified account is labeled as an “Ukraine government organization” by Twitter. It posts war-related and political updates about Ukraine. @Ukraine: (2) @uamemesforces: self-described as the “Source of the best Ukrainian memes”, this unverified account states as its goal ”to convey the truth about what is happening now in Ukraine with the help of memes”.[8] @uamemesforces: (3) @DefenceU: or “Defense of Ukraine”, is the “Official page of the Ministry of Defense of Ukraine”. Like @Ukraine, this verified account is described by Twitter as a “Ukraine government organization”. Its posts concern battlefield updates and news. @DefenceU: We select the accounts @Ukraine and @DefenceU because of their large following (at the end of the collection period), because they are official accounts not associated with individuals or specific media outlets, and because of the focus on the conflict (many popular Ukrainian accounts are by non-relevant celebrities). Additionally, we select @uamemesforces, the most popular Ukrainian unofficial account that posts memes about the conflict. Note that we are limited in the number of accounts we can study due to the labor-intensive labeling process. We retrieve all of the posts for these accounts via Twitter Timeline API. We treat each post with media content as a potential meme, no matter the format. To ensure preserving content posted by these accounts, we also download the images associated with the posts and the users who retweeted or liked the post (see Table 1 for summary statistics). We associate each user with a country in the GeoNames database via their location field (a free-text field optionally filled by the user). Considering only tweets with media, out of 586 042 users, 44% are successfully mapped to a country. We retain only countries with at least 1000 geolocated retweeting users for geographic analysis. In order to explore the relationship between Ukrainian memes and each country’s actions towards the conflict, we use the Ukraine Support Tracker data from the Kiel Institute for the World Economy (downloaded on 20 June 2023), which “quantifies military, financial, and humanitarian aid transferred by governments to Ukraine since the end of diplomatic relations between Russia and Ukraine on January 24, 2022”.[9] The dataset provides a quantitative measure of a country’s aid to Ukraine. Finally, to examine the attitude of each country’s population towards Ukraine, we use the Eurobarometer STD98 survey which took place in winter 2022-2023 in 30 European countries [22]. Specifically, we use use QE2, answer 6: “To what extent do you agree or disagree with: providing financial support to Ukraine.” 3.2 Annotation To understand the visual and narrative attributes of the captured data, all authors perform a manual annotation of a random selection of the tweets. We use all of @Ukraine tweets and a random sample of roughly 40% of those from the other two accounts are selected for analysis, for a total of 1063 tweets (last column of Table 1). We remove self-replies (an account replying to its own post) which have no retweets of their own. Guided by previous literature, we compose a codebook to capture visual and narrative aspects of the content. First, we adopt the significant features of the content characterization framework proposed by Ling et al. [41], which is used to model the virality of political memes. These attributes include: (1) Number of panels: multiple or single; (2) Type of image: photo, screenshot, or illustration; (3) Scale: close-up, medium shot, long shot, other; (4) Type of subject: object, character, scene, creature, text, other; (5) Main attribute of the subject (if character): facial expression, posture, poster (6) Character emotion (if character): positive, negative, or neutral; (7) Contains words: whether image itself (not tweet caption) contains words. Second, we employ the narrative framework by Karpman [35] later extended by de Saint Laurent et al. [18]. It defines two key dimensions to characterize a narrative: moral quality (benevolent or malevolent) and power (strong or weak), thus resulting in four character archetypes: heroes (benevolent, strong), victims (benevolent, weak), villains (malevolent, strong), and fools (malevolent, weak). We also label the actors mentioned in these narratives (as an open category, guided by an initial set of main actors in the conflict, such as Zelensky and Putin). We further contextualize the narratives by their emotional appeal [8], in particular humor, pride, fear, outrage, and compassion (the label was originally open, but the labelers coalesced on this set). Finally, we record whether there is a specific intent in terms of a call to action or information sharing. Note that, as much as possible, we try to label the narratives as intended from the point of view of the posting account (although some biases may creep in, as we discuss in Section 5). Appendix B reports the full codebook. Using this literature-driven codebook, all authors of this manuscript perform a deductive coding of the selected posts (for more on such process see Linneberg and Korsgaard [42]). We rely on Google Translate to translate non-English language content. All coders first annotated a selection of 50 posts, discussed insights and disagreements, and came up with standard labels for emotional appeal, intent, and actor (though the label remained open). Subsequently, the rest of the posts are annotated by one author each, with uncertain cases discussed collectively. Appendix C reports the inter-annotator agreement on a selection of 48 posts (sampled from each account). On average, the agreement is 0.750 for @Ukraine, 0.604 for @uamemesforces, and 0.667 for @DefenceU (with a Krippendorff’s alpha of around 0.65 for all accounts and tasks), which is high considering the subjective nature of the tasks, and that some features were open and could have multiple labels. The annotated dataset is available at https://github.com/corradomonti/ukranian-tweets. 3.3 Popularity model Using the data collected and annotated as per the previous sections, we construct models to find whether there are trends in (𝑖) what kind of content becomes more popular, and (𝑖𝑖) who it reaches. Specifically, we use linear regression to model the log-transformed number of retweets with the content variables outlined above as independent variables. As the three accounts have posted a vastly different number of tweets, we weigh the data points (tweets) inverseproportionally to their representation in the dataset, so that each account weighs equally on the outcomes. We build several versions of the model to ascertain the benefit of each class of variables: visual [41], actor, emotion, intent, and narrative. A baseline model simply uses the identity of the author (i.e., group fixed effects), the number of followers of that account (log transformed) as a proxy for the potential audience, and the number of days from the invasion to account for changing interest in the topic over time. We then choose the best model by the Bayesian Information Criterion (BIC)—a model selection metric that captures both unexplained variation in the dependent variable and the number of explanatory variables. The coefficients of this model reveal the associations between these variables and the virality of the content. Next, we group retweets by the country of the user (those who can be geolocated) to understand the preferences of users who spread these messages. We enrich our characterization of the relationships between each country and Ukraine by considering the amount of financial assistance the country provides to Ukraine (normalized by the country’s GDP) or by their opinion on this topic (via the Eurobarometer survey). As mentioned above, we consider these measures as different proxies of support for Ukraine’s military efforts. First, we examine the retweeting rate (normalized by population). Then, we compare the narrative preferences to the amount of support for Ukraine: are there narratives associated with increased support for Ukraine? We operationalize this preference as the log odds of users from a country retweeting content having a specific narrative. Finally, we examine the geographical distribution of the retweeting rate and narrative preferences across Europe by plotting these on choropleth maps. [8] https://www.patreon.com/uamemesforces [9] https://www.ifw-kiel.de/topics/war-against-ukraine/ukraine-support-tracker This paper is available on arxiv under CC 4.0 license. This paper is available on arxiv under CC 4.0 license. available on arxiv

Understanding Memetic Warfare Tactics: Social Media Tactics in the Russo-Ukrainian War

Transcendence Book 9: Far-skies

How to Master .NET 8 Web API: From Setup to Security - The Best 50 Tips

কিভাবে .NET 8 ওয়েব এপিআই আয়ত্ত করবেন: সেটআপ থেকে নিরাপত্তা - সেরা 50 টি টিপস

.NET 8 Web API meistern: Von der Einrichtung bis zur Sicherheit – Die 50 besten Tipps

Cómo dominar la API web .NET 8: de la configuración a la seguridad: los 50 mejores consejos

Comment maîtriser l'API Web .NET 8 : de la configuration à la sécurité - Les 50 meilleurs conseils

.NET 8 वेब एपीआई में महारत कैसे हासिल करें: सेटअप से सुरक्षा तक - सर्वोत्तम 50 युक्तियाँ

.NET 8 Web API をマスターする方法: セットアップからセキュリティまで - ベスト 50 のヒント

.NET 8 Web API를 마스터하는 방법: 설정부터 보안까지 - 최고의 50가지 팁

Como dominar a API da Web .NET 8: da configuração à segurança - as 50 melhores dicas

Как освоить веб-API .NET 8: от настройки до безопасности — 50 лучших советов

.NET 8 Web API'sinde Uzmanlaşma: Kurulumdan Güvenliğe - En İyi 50 İpucu

Cách làm chủ API Web .NET 8: Từ thiết lập đến bảo mật - 50 mẹo hay nhất

如何掌握 .NET 8 Web API：从设置到安全 - 50 个最佳技巧

Stories, News & Mentions about UMAPPED

Umapped’s Stories on HackerNoon