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THE PILGRIMS.

Table of contents Here are some examples of "as const" : Enum Types Tuple Types Function Return Types Object Properties Conclusion✨ Happy Coding 😊 you ever worked with types in and found yourself wanting more control over how those types behave? Well, there's a handy little feature called that can help with that. Have TypeScript as const is a way to make type checks stricter by preventing certain operations on a value. For example, let's say we have an array: as const const fruits = ['apple', 'banana', 'orange']; By default, TypeScript sees this as an array that can contain any string. But what if we wanted TypeScript to know that this array will ? only ever contain these three specific string values That's where comes in. By adding it, we make TypeScript treat the array in a more "specific" way: as const const fruits = ['apple', 'banana', 'orange'] as const; Now, instead of just being a , fruits are seen as the specific tuple type . string[] ['apple', 'banana', 'orange'] This means TypeScript will give us errors if we try to add or remove items from the array. It knows the values are "locked in". works on other types too. as const For example, you could mark an object as constant to prevent adding or removing properties: interface Cat {
  name: string;
  age: number;
}

const garfield = {
  name: 'Garfield', 
  age: 10
} as const; Now Garfield is seen as an object with very specific fields, rather than a loose Cat interface. Here are some examples of "as const" in action Here are some more examples of how can be used in TypeScript: as const Enum Types You can make an enum to remove the implicit number types: as const enum Colors {
  Red,
  Green,
  Blue
}

let c = Colors.Green; // number

enum ColorsAsConst {
  Red, 
  Green,
  Blue
} as const;

let c = ColorsAsConst.Green; // ColorsAsConst.Green Tuple Types Mark a tuple to make its types very specific: as const let tuple = [1, 'two'] as const;

tuple[0].toFixed(); // OK
tuple[1].toLowerCase(); // OK Function Return Types Mark a function return value to narrow its type: as const function createError() {
  return {message: 'an error'} as const;
}

const err = createError();
err.message = 'something else'; // Error Object Properties Objects marked prevent adding/removing properties: as const interface Point {
  x: number;
  y: number;
}

const p = {x: 0, y: 0} as const; 

p.z = 0; // Error So in summary, brings immutability and more precise types to enums, tuples, return values, objects, and more! as const Conclusion✨ In summary, const proves to be a clever tool for enforcing stricter and more specific types in TypeScript. It serves as a clear communication of your intent when you require values to remain immutable. Don't hesitate to implement it in your upcoming projects! Thank you for Reading this article💖 Also published here.

"as const" — Typescript's Unsung Hero for Strongly Typed Variables 

It’s no secret that location technology is a key driver for business success. After all, it helps optimize operations, generate insights, drive revenue, and much more. Everybody knows the big hitters — routing, navigation, tracking, etc. But there is a lesser-known location technology that does its crucial work behind the scenes where end consumers can’t see it: the clustering API. The clustering API is a powerful tool that intelligently groups similar data points, such as geographic locations, based on specified properties. This article aims to bring the API its due recognition by exploring its use cases and benefits, applications across industries, and role in solving complex location problems. Understanding the Clustering API The clustering API is designed to simplify data organization and analysis. Its primary function is to group similar data points based on user-defined properties, and it does so by employing sophisticated clustering algorithms like k-means, DBSCAN, and hierarchical clustering. These algorithms analyze the proximity and similarity of data points, considering various attributes and properties to determine their suitability for clustering. Such intelligent grouping enables businesses to uncover meaningful insights from location data. Once clusters are identified, the API selects appropriate geolocations to represent each cluster, acting as central points for visualization and analysis. The selection process considers factors like cluster data point density and distribution to ensure accurate representation. A core objective of the clustering API is to optimize logistics by minimizing the distance or duration required to service each cluster. Strategic grouping helps organizations better allocate resources, plan routes and streamline operations, leading to reduced travel times, lower fuel consumption, and enhanced operational efficiency. Even when central locations are not explicitly specified, the API automatically identifies appropriate central locations based on the input problem's constraints and requirements. Use Cases of Clustering API The potential applications of the clustering API are vast, with numerous use cases across various industries. In industries like e-commerce, food delivery, or transportation, where efficient delivery is critical, the clustering API can be employed to group orders or delivery locations based on proximity. Streamlining Logistics: Consolidating orders into clusters helps businesses optimize routes and enhance operational efficiency, empowering them to handle larger orders while minimizing costs and improving customer satisfaction. In supply chain management, the clustering API is crucial for analyzing relationships between product demand and the locations of manufacturing facilities and distribution centers. Optimizing Supply Chains: By intelligently clustering high-demand locations, manufacturing facilities, and distribution centers, organizations can identify optimal warehouse locations, plan better routes and allocate inventory effectively. This reduces inventory holding costs while enhancing order fulfillment and customer experience. Industries like field services, emergency response, and ride-sharing rely on effective resource allocation, which is greatly simplified by grouping tasks or service requests by geographical proximity. Improving Resource Allocation and Routing: Clustering service locations helps businesses assign resources strategically, minimize travel time and ensure prompt service delivery, leading to improved resource utilization and customer satisfaction. Efficiency is paramount in the delivery and service industries. Enhancing Service Efficiency: By intelligently grouping customer locations based on proximity and service requirements, businesses can optimize their routes to reduce travel distance, improve overall efficiency, hasten response times, and lower operational costs. Benefits of Clustering API Leveraging the clustering API offers numerous organizational benefits. The API reduces inefficiencies by grouping similar data points into clusters and optimizing routes, resulting in faster turnaround times, improved productivity, and operational excellence. Increased Operational Efficiency: The ability to handle larger volumes of data and tasks results in enhanced scalability and responsiveness, driving business growth. By identifying optimal central locations and grouping data points, companies can allocate resources such as vehicles, personnel, or inventory more effectively, minimizing unnecessary travel and lowering maintenance costs. Cost Reduction Through Optimized Resource Allocation: Optimized routes and resource allocation reduce waiting periods and enhance service quality. Enhanced Customer Experience and Satisfaction: By analyzing customer data using clustering techniques, organizations can tailor marketing strategies and provide more personalized offerings and customer experiences. Clustering provides valuable data-driven insights. Analyzing clustered data points provides a deeper understanding of patterns, trends, and correlations within location data, enabling companies to identify market opportunities, optimize business strategies and make data-backed decisions that drive success. Improved Data-Driven Decision Making: Clearly, the benefits of the clustering API extend beyond just operational efficiencies and cost reductions. By harnessing data-driven insights, organizations can optimize operations, elevate customer satisfaction and make strategic moves that lead to long-term success. Real-World Applications of Clustering API The following real-world examples demonstrate how businesses utilize the clustering API in various industries. E-commerce and last-mile delivery companies optimize operations and improve delivery efficiency by clustering customer addresses based on proximity. This results in faster deliveries, improved customer satisfaction, and more cost-effective logistics. E-Commerce and Last-Mile Delivery: Ride-sharing and food delivery platforms optimize services and enhance customer experiences by clustering pick-up/drop-off and delivery locations. Ride-Sharing and Food Delivery: This enables better resource allocation, reduced wait times, improved surge pricing management, and real-time balancing of supply and demand. Field service management companies optimize technician routing and resource allocation by clustering service requests based on geographical proximity. This results in faster and more effective service delivery, boosting customer satisfaction. Field Service Management: Retail companies with multiple physical store locations optimize their network with the help of the clustering API. Retail Stores : By clustering customer data and analyzing demographics, retailers identify optimal locations for new store openings or relocations, maximizing foot traffic and sales potential. The clustering API is a powerful tool for organizations looking to stay ahead of the competition by leveraging their location data’s full potential. Clustering techniques enable companies to optimize operations, enhance customer experiences and gain competitive advantages. The API makes it easier for routing and dispatch algorithms to do their jobs effectively and helps unlock efficiency, improve service quality, and enable data-driven decisions that propel businesses forward. Wouldn’t you say that’s worthy of a hero’s praise?

The Clustering API: An Unsung Location Tech Hero That Drives Business Success

La API de agrupamiento: un héroe tecnológico anónimo de ubicación que impulsa el éxito comercial

L'API de clustering : un héros technologique de localisation méconnu qui stimule le succès de l'entreprise

क्लस्टरिंग एपीआई: एक गुमनाम लोकेशन टेक हीरो जो व्यावसायिक सफलता को प्रेरित करता है

クラスタリング API: ビジネスの成功を促進する隠れたロケーション テクノロジーの英雄

A API de clustering: um herói tecnológico local desconhecido que impulsiona o sucesso dos negócios

API phân cụm: Người hùng công nghệ vị trí vô danh thúc đẩy thành công trong kinh doanh

集群 API：推动业务成功的无名位置技术英雄

According to the by Product Plan, communication is ranked as the most essential skill for Product Management. Fifth Annual product management report Mastering this soft skill is an important key to success! Acting as a Product Manager requires cross-communication with many teams. Therefore, the Product Manager spends a significant amount of time communicating ideas, plans, designs, and assigning tasks to the teams, which involves sending many emails and having daily meetings. Effective communication is important for understanding who your consumer is and what they need or want. Every step of the way, whether you're managing stakeholders or just want to get a project out the door, good communication is essential to creating great products. Having Effective Communication Communication is not a skill that everyone is born with. Still, with a few simple tips, Product Managers can better get their messages across and make others feel understood. 1. Show Empathy The best communicators can put themselves in other people's shoes to understand their situation from the other person's perspective. By walking a mile in somebody else's shoes, Product Managers can practice empathy and build trust for their products. 2. Define your Message Clearly Product Managers need to be sure and know what they want to say and be respectful and consider different points of view when developing an understanding of the goals of the entire product cycle. 3. Be patient and don't assume anything. While communicating with other people, Product Managers need to keep people in the loop by asking questions as often as possible to ensure they continue to understand what the manager is saying. 4. Be clear with your intent. The manager's tone of voice and gestures should focus on making their point rather than bragging or putting somebody down. Why is communication vital for Product Managers? As Product Managers, you spend a significant amount of time communicating. It is hard to prove the value generated while speaking. The quality of the job is not measured by the number of stories done during a specific sprint. Instead, it is to make the team ship the right product at the right time, ultimately making the users succeed. Three streams of communications PM communicates through various streams depending on the people's positions with whom they share. And all the interactions are different. However, the majority of professional communications fall into three categories. 1. Horizontal Communication streams As a Product Manager, horizontal communication is the lifeblood you need to function. Being a Product Manager, you spend most of your time communicating with those involved in implementation and execution, including cross-functional team members. Therefore, you have to know what needs to be done to produce an effective project. 2. Vertical Communication Streams As a Product Manager, you reside in an unusual strata within the organization. You need to communicate with the top-level executives to follow up on the plans and strategies. You also need to communicate with low-level executives to bring out the products per company requirements. 3. External Communications streams Finally, sometimes you might find yourself communicating outside the company as a product manager. You'll be speaking with your customer base, potential users, partners, media, and analysts about what's happening behind your project's scenes. These people have different interests, shifting from internal to external concerns as they move from working on specific features to launching the application after developing it. Consumers' primary concern is simply what's in store for them regarding your project and when they can get their hands on it. Three Principles for effective communication for Product Managers Just communicating is never enough. Product Managers need to have effective and efficient communication. To do that, you should follow the three principles of effective communication. - Communication is a reciprocal process. Product Managers need to reciprocate and form back-and-forth communication between both parties. You need to ensure dialogue and not just one-way communication. This leads to the enhancement of ideas and better creativity among the executives and product developers. 1. Reciprocity - Product Managers must ensure that the message and communication are not lost during the transmission. Many of the mediums the teams communicate are fraught with opportunities for confusion. As a Product Manager, you need to create a bridge to fill the gaps with technologies and better communication channels. 2. Medium - Context is another critical factor that needs to be considered once the product manager initiates the communication. Product managers need to have empathy for the current political, social, and company environment and should encourage effective communication. 3. Context How to deliver a significant impact while communicating? Communicating without adding value or delivering a significant impact is of no use. Product Managers have to make the most of the communications they undergo. You must provide a big impact while communicating, and you can follow the following tips to have effective communication. Create a meeting agenda and stick to it Meetings are an endless component of Product Manager life all around the world. Product Managers worldwide can control how effective their meetings will be through a clear agenda. A clear plan helps guide and even push forward your teams. In this way, you can save time from your busy days and remind everyone what the important points of any meeting should be in order not to get distracted or sidetracked from the most significant impact. Use road mapping software For Product Managers, knowing how to communicate their strategy is quite important. As a Product Manager, you must be able to state the process clearly. Furthermore, it's vital to have the right tools, like dedicated Product Road Mapping tools. Road Mapping software (like zeda.io) is crucial for the project over tools like Microsoft products (Powerpoint, Excel), which are more used for business presentations and data-sharing than the needs of product teams and their unique challenges. Click here to join the waitlist for this product which is, to date, one of the best road mapping tools in the market. Communication: the savior for product managers A good conversation can be the best way to learn something new. So effective communication is vital when building a process that gets everyone on the same page and ensures everyone is working toward a similar goal. Knowing your audience through communicating with them will ensure that you have the right people taking care of different aspects of your project; for example, send surveys, get feedback and adjust your roadmap accordingly.

The Unsung Superpower for Product Managers in 2022

Preamble I was on my own doing my usual chores of learning new technologies when "peer to peer code reviews" suddenly occupied my conscience. This conscience morphed into what I write here. I believe peer-to-peer reviews serve several purposes like employee performance evaluation and the like. However, the focus of this piece is to highlight its use in teaching the best coding principles. Before enrolling in Microverse, a remote software development school, I did not know peer-to-peer code reviews do a great job enforcing and teaching standards. So, the content herein is derived from my personal Microverse experience. Well, anyone that has a few minutes on their hands can read on. Early warning! I will not talk about the shortfall of doing a peer-to-peer review because I don't know. (I have not paid attention enough on the wrong side of it). Definition of Peer-to-Peer Reviews From experience, I will say that peer-to-peer review is an activity conducted between a group of 2 or more like-minded individuals where one member presents their most recent work(code commits in my case) and the rest of the team members suggest improvements. Peer-to-Peer Ways Let's say members can also commend the presenter for the excellent work. That said, at Microverse, peer to peer reviews explicitly exist in two ways which are: Through standup teams. Through pull request code reviews. Through Standup Teams Standup teams at Microverse are small groups of at most six global software developers who meet every morning and evening to share their development experiences. Through Pull Request Code Reviews The setup here is that software developers who have been at Microverse longer get to review pull requests opened by newer ones at Microverse to suggest better ways to improve their code and documentation. This arrangement is so because Microverse continuously does industry research and puts together up-to-date industry standards. Therefore, those who have been longer with Microverse comprehend these standards over time and pass them on to newer ones through Github pull request reviews. Benefits of Peer-to-Peer Reviews In my opinion, the benefits of peer-to-peer reviews accrue to both the organization and the individuals. However, I will focus on the benefits to an individual. Below, I will list some of the ways I have benefited from the peer-to-peer code review process at Microverse. You are free to disagree as these are from personal experience and not engraved in stone. Learning from peers. Peer-to-peer reviews have blessed me with exposure to programming tricks and best problem approaches. Peer-to-peer reviews provide an avenue to practice and review previously used and learned concepts. When my peers present something that I have used in the past, it has always been a great review of those concepts leading to better comprehension. Solutions to blockers. Most of the technical blockers I face faced get resolved through peer-to-peer code reviews. Best-practice socializing. Peer-to-peer reviews are channels for sharing best practices through suggestions made on the presenter's work. Fulfillment from helping someone else get unstuck. Accruing from peer-to-peer reviews is contentment and a confidence boost when one's suggestion or reference becomes a solution to a peer's challenge. Building rapport with global software developers. This is as clear as day light in that great friendships, collaborations, and even revolutionary projects are bound to come out of peer-to-peer reviews. I have interacted with experienced software developers. Draw inspiration and motivation from other peers. Having accountability partners. One remains focused because one tends to mind what they present to their peers. One aims to showcase something that will inspire, educate or even fortify their credibility with their peers. Improve soft skills like presenting your thought process in real-time. It is a guarantee that the longer you engage in peer-to-peer reviews, the better presenter you become. Cross-culture communication. Since peer-to-peer reviews happen between individuals from different backgrounds, one is bound to get good at relating with people that are different from self. Conclusion That is it for now, and I am not entirely responsible if you are still unconvinced about peer-to-peer reviews. The onus is on you to dig deeper into the subject matter. That said, peer to peer review is a great activity and can effectively be used to achieve high results on any project work.

The Unsung Peer-to-Peer Review

What are batch transfers, why they matter, and how they can help spur adoption. Most of the media focusing on blockchain and cryptocurrency these days focuses on institutional players entering the space; whether it be through the upcoming launch of Bakkt or companies like Fidelity opening up digital asset management branches. An often overlooked area of development is the B2B landscape. Basically, what tools are being created to help developers and business owners in the space. Bakkt is an incredibly exciting development, don’t get me wrong. However when we’re thinking about blockchain mass adoption, it’s infrastructure that’s needed to help move it along. infrastructure developments quietly help give the people in the industry the tools they need to bring the to where it needs to be for mainstream success. Bakkt helps bring digital assets as to the forefront of mainstream media, a new asset class technology Something you’re probably familiar with if you’ve dabbled in cryptocurrency is airdrops. Airdrops are like mass email blasts for tokens. Essentially, they are when a cryptocurrency distributes token by collecting Ethereum addresses from people interested in your coin — and mass sending them tokens to create a market for said coin. It’s impossible to ensure the success of a token, but not getting it into the hands of as many people as possible is a great way to ensure it doesn’t succeed. Distributing your token is one of the most important aspects of the token generation process. Airdrops are technically referred to as batch transfers. Batch transfers are used to save time and eliminate errors when performing a number of functions. We use batch transfers to facilitate airdrops, distribute bounties from successful bounty campaigns, token giveaways, and even to distribute coins after an ICO or Security Token Offering. Batch transfers are an example of a process that isn’t really sexy. They aren’t anything that will get a huge amount of attention, no one is really clamoring to find out the hottest new dApp to seamlessly transfer large amounts of tokens — for the people in the industry. The ones actually pushing it forward. except Proof of Lack of Sexiness We often discuss how user-friendliness and ease of access are going to be large hurdles for this industry to overcome if we’re going to achieve mass adoption. We’re making strides as an industry towards creating this ease of access, both for consumers and producers. Technology advances when new technologies are created to help people do their jobs easier. Think about what Facebook ads did for marketers, or how much more difficult eCommerce companies would be to manage without the advent of things like Google Analytics. Entrepreneurs are what drive industries forward, and the infrastructure in an industry is the road they drive on. Right now the blockchain industries road needs a little work. We have our share of potholes, and the drive isn’t that smooth, but we’re working on it. Let’s take a dive into , how they can be , some of your , and a few of the unsung heroes of the industry making strides towards easy to use B2B solutions for blockchain companies. what airdrops are used to help your blockchain business options for running an airdrop The Original AirDrop PART 1: THE BASICS What are Batch transfers used for? Due to the design of Ethereum, batching transactions (outside of state channels) is more about saving time and eliminating error than saving fees on gas. A batch transaction tool is helpful for any general transaction that require sending tokens to multiple addresses. It is most often used to conduct: Bounty Campaigns Airdrop Campaigns *Airdrop campaigns are often used to giveaway large sums of a specific token, often towards to goal of marketing the coin and growing its’ community. ICO/STO Distribution Token Giveaways (Marketing Utility) How do I do a Batch Transfer? While it’s hard for the everyday user or crypto trader to know what is happening inside the development of the Ethereum protocol, dApps have been steadily moving in the right direction as far as user experience is concerned. Batch transfers especially have come a long way from the methods one had to use to conduct them in the past. doing it yourself internally or exporting it to a development shop, there are also several dApps that help manage the process and ensure no tokens slip between the cracks. Aside from the two standard options: It’s important to note that you don’t have to be a developer or programmer to do a batch transfer, there are solutions for the not-so-technically inclined. Why is it important? In order for a token to succeed it needs to have a market of buyers and sellers. Without supply and demand, it won’t go anywhere. Batch transfers are pivotal to a tokens success in this sense, if you can’t distribute your token to excited users, there’s no point in developing it in the first place. Which is why I see batch transfers and the advancement of dApps that facilitate them as an important element of the blockchain ecosystem. Another way to think about the importance of batch transfers is in terms of the technology itself. The growing utility of the Ethereum ecosystem requires this functionality. Why are Batch Transfers important? The Ethereum blockchain is, without a doubt, the most active smart contract platform in existence. On Github the popularity can be measured: 18,728 repository results and 268,000 commits to ETHEREUM Several analysts have stated that ETH currently has and have been adding more than 50,000 developers on a monthly basis since May. (CCN) more than 300,000 developers on its network As of today there have been on the Ethereum network. With many of these contracts featuring hundreds of millions, if not billions, of tokens there is ample need for a tool that allows users to easily send ERC20 tokens in batch or mass amounts. 116,000 ERC20 token contracts deployed Ethereum is the foundation for a majority of cryptocurrencies. Most of these tokens are “ERC-20 tokens,” which made possible the majority of the $5.5 billion raised through token sales in 2017 and the $6.5 billion raised in just the first quarter of this year.” (CON) As of February first of this year, Ethereum surpassed 1 million transactions per day. Additionally, ease of use and user experience are important if we ever want to see mass adoption. Even if you are not onboard with the use of airdrops as a marketing campaign or bounty giveaway, the ability to do transfers to multiple addresses should be accessible to the everyday user for their general transaction, whatever it may be. If we want cryptocurrency to be used in similar fashions to cryptocurrency, we need to have simple functionalities to distribute currency. In the future, we might use batch transfers to divvy up prize money after a Poker tournament. They could even be used to distribute employee salaries seamlessly and automatically. Companies spend valuable resources re-inventing the wheel every time one wants to do an Airdrop. Developers build scripts and throwaway programs which are not shared with the community. Making good software that people can use is hard, and is an Art. PART 2: HOW TO DO A BATCH TRANSFER You have generally 3 options when it comes conducting one. Let’s look at examples of the pros and cons of each of the three options. DIY (Manual AirDrop with a Team) The first two options we’ll look at our DIY (Do It Yourself) options (the good ole’ days of manual batch transfers), the last is through the use of dApps. PROS: No programming experience required. CONS: 1000 wallets sent an ERC20 token with 20 people is going to take at minimum 16 hours (2 work days) with the team sending at a rate of 3.125 wallet transactions per hour. Time-Consuming; If you’re sending a batch transfer to 1000 addresses, you can expect- 1000 addresses x 3 minutes per address = 50 hours of manual label. Assuming a minimum wage for these employees you’re looking at $750 in manual labor alone. Cost Prohibitive: Humans are fallible and make errors. This could be due to a fat-fingered keystroke on an address, pure forgetfulness, or fatigue or other human constraints. This leads to extra cost and wasted tokens. Error Rate and Leak: The longer an AirDrop takes the more likely that the Ethereum network congestion and the frequent fluctuations in “gas prices” can inhibit this process. Market Fluctuation: PIY (program it yourself) If you’re a developer, it might be feasible to simply run the transfer yourself. PROS: If money is the only factor, if you think about the time wasted it’s not much cheaper. Cheaper; allows you to develop specific functionalities. Specificity; CONS: puts responsibility on the users and those receiving (potentially lower security), may upset receiving users if too slow or inaccurate. Risky; not everyone is a talented programmer who understands the tech and the tokens used. Low Accessibility; Programming a functional tool is a slow process and usually needs a debugging phase to implement properly. It may not be an effective use of core developers time, which could be used to move the main platform or product forward faster. Time-consuming; devs are not cheap… Expensive; Pre-built tools and dApps dApps are a great way to mitigate some drawbacks of the other options as they do not require experience in coding and only charge a fee based on usage. dApps vary in the features offered, cost, and ease of use but remove You don’t need coding or contract building skills to perform transfers to multiple Ethereum addresses. the need of coding or contract building skills to perform an airdrop. In addition to saving time and cost on development, batch transfer dApps also help decrease network congestion by aggregating 100 transfer into 1 transaction. How they work: Access the dApp. Upload address list in correct format dApp generate and batches up to 100 transfers in one transaction Some dApps require you to sign after each, others like can automatically sign and automate any number of transactions (100 addresses each) until the task is completed. Ethtree PROS: Accessible: no coding required, typically just requires the formatting of addresses. Low Cost: No development cost; not paying for information, other companies operating expenses. Save time programming. Accessible anytime, dApps never close or sleep. the cost of a batch transaction ultimately depends how many transactions are involved, using a pre-built tool saves in development cost. On cost: Among the ones I’ve listed here, the highest cost is 15 cents per batch transaction which can contain up to 100 addresses. For 100 addresses, you pay only 15 cents plus the eth gas fee. For 1000, you pay only $1.5 in fees. For 10,000 address, you only pay $15. Regardless of how long your dev team takes, it would be hard to beat such a low cost. CONS: You will responsible for getting yourself there. Unlike full service development shops or those that specialize in a particular service, you will have to do your own due diligence for things like ICO, airdrops, and bounty campaigns. — typically you can expect to have less support through the process. Highlight — has an easy to read page, dedicated support, and visible founders. Little Customer Support Ethtree Docs : Not to get into too much detail about how smart contracts and gas works on Ethereum… In order of most gas efficient to least: Coded distribution at TGE, Manually done, dApps and other smart contracts that do batch transfer. On GAS Batch Transfer dApps (that sends tokens directly to the address, as opposed to recievers having to claim them and pay for their own gas) will be Less Gas Efficient compared to coding the distribution within the token itself at TGE. Manual transfers are next gas efficient method for batch transfers because there is no extra gas required for processing the smart contract component of the batch transfer function. That being said, the function does not require much additional gas for what you get in time saved and minimization of error. dApps vary in their cost of gas depending on how many lines of code are involved but generally are relatively similar. PART 3: COMPARING THE OPTIONS I threw together this visual to give you a better idea of how the batch transfer options available compare to each other. the newest and “standout dApp” of the available options. Instead of a webapp, they have a downloadable desktop dApp. Their user interface is clean and simple to use, especially compared to other options. I also really like that they have a detailed docs/FAQ page and the founders can be reached through their socials. From what I could tell, the DApp has a couple unique features that I thought should be standard to the others but aren’t. The first feature is their automatic sign and batch functionality which can save you valuable time and effort if you are processing a large number of addresses. Unlike the other Dapps, that require you to approve every batch of 100 or so addresses (this limit is based on the way Ethereum is designed), Ethtree will continue to batch and send transactions to all of the addresses you give it. The second function is an optional EthGasStation API monitor. You can either choose to set gas manually for all your transaction or let the program set the appropriate gas at the time of processing. This optional feature is particularly important if you are dealing with a large amount of addresses as it ensures that your transaction will go through even if there is any congestion in the network. The third feature is the ability to click on completed transactions as they populate in the dApp. I like that I can verify where the program is at in real-time by clicking on the addresses that have been completed and it takes me to Etherscan. While this feature is not extraordinary by any means, I like that a DApp inutitively does what I think it is suppose to. Lastly, I like that the program lets me know what the cost is and the gas estimate before starting and a reciept upon completion. Ethtree: are all relatively the same. They feature a one-page web dApp where you type out or upload a list of addresses and amounts you want to send. Token Multisender in my opinion has the best interface of the three, but it certainly leaves me wanting more. Aside from decreasing the likelihood of human error, having great UI and thus great UE is vital to adoption. I only recommend using one of these if you are sending tokens to a small amount of addresses as you will need to sign and execute each batch for those above the 100-150 threshold. Token Multisender, Batch Sender, and Dapple Airdrops Cansend is like Token Multisender, Batch Sender, and Dapple Airdrops in almost every way except that it has a better UI and requires a CAN token to operate. Unless you already own CAN tokens, I feel like having a token if anything makes it less friendly. Cansend: — — — — — — I hope this helps answer any questions you might have had about air drops, batch transfers, and how to facilitate them. If I’ve missed out on any options please comment below and let me know!

3 Methods to Conduct an Airdrop — Intro to Batch Transfers & the Unsung Heroes of Blockchain

3 métodos para realizar un Airdrop — Introducción a las transferencias por lotes y los héroes anónimos de Blockchain

Recently and I discovered that and Scala are unsound. We submitted the finding and related discussion to OOPSLA, an academic conference on object-oriented . It has been great to see the paper making rounds in industrial circles, but there also seems to be a lot of confusion and I think that’s our fault. The paper was written for academics, and so it doesn’t discuss the issue from industry’s perspective. I’m crunching on a deadline right now, so let me write an abridged version of the industry-targeted paper here, focusing just on Java. Nada Amin Java programming What Does “Unsound” Mean? Most type systems aim to provide some sort of guarantee about how a well-type program will behave. For example, in many languages all memory accesses are “safe” in well-typed programs. A type system is sound if it actually succeeds at providing that guarantee. Thus informally a type system is sound if it ensures what its designers intended it to ensure. This is much like programming: a program is correct if it does what it is supposed to do. Java’s type system is intended to ensure that if a method asks for an Integer, then it will only ever be given Integers, never Strings. Thus the following pseudo-code is rejected by the type system: public Integer increment(Integer i) { return i + 1; }String countdown = increment(“98765432”); Sure, in JavaScript this might make sense, but Java is implemented very differently, and allowing this code could really mess up the heap (or even stack if you’ve ever enjoyed some C/C++ memory mismanagement errors). Now you might already know that Java’s type system has some unsound qualities. For example, for historical reasons Java has covariant arrays, making this code type check: String[] strs = { "NaN" };Object[] objs = strs;objs[0] = 1;String one = strs[0]; And when generics were added, Java used “raw types” so that genericized code could be compatible with pre-generics code. Consequently the following type checks: List<Integer> ints = Arrays.asList(1);List raw = ints;List<String> strs = raw;String one = strs.get(0); Thus both of these examples seem like they allow to contain an despite the fact that it is declared to have type . one Integer String Now this brings us back to intent. The designers the type system to allow this behavior. This is because, although these examples are clearly bad, there are many examples where this permissiveness is useful. After all, untyped languages are all about allowing bad things to happen so that more cool things can happen as well. And because this behavior was intentional, the designers planned for it. Every time you assign a value into an array (of a reference type), the runtime looks up the array value’s actual element type and throws an if it’s incompatible. So in the above sample, the assignment fails before the seemingly unsound assignment can be reached. Similarly, whenever is called on a , the runtime checks if the returned value is actually a in case a raw type was misused, throwing a otherwise. intended ArrayStoreException objs[0] = 1; String one = strs[0]; get List<String> String ClassCastException So Java’s type system seems to be as sound as it was intended to be, though maybe not as sound as you would like it to be. And since generics were introduced, it was believed to be “truly” sound so long as you didn’t use these intentional backdoors. “True” Unsoundness Here’s our “true” unsoundness example that has been making the rounds most recently. It assigns an instance to a variable. According to the Java specification, this program is well-typed, and according to the Java specification it should execute (unlike the aforementioned backdoors) and assign the instance to the variable, violating the intended behavior of well-typed programs. Thus it illustrates that Java’s type system is unsound. Integer String without exception actually Integer String Now you, like many others, might be confused by this example and might have already done some things to make yourself even more confused. So let me first name each common point of confusion: People don’t understand why this type checks or even actively believe it should type check. not If you copy this into your own Java compiler at hand, the compiler might say the program does not type check, contradicting my claim. If your compiler does type check it and then you run it, you get a , also contradicting my claim. ClassCastException You also wonder why this matters, especially since you and your colleagues are unlikely to ever write code like this. I’ll address all of these concerns, though out of order. “But It Doesn’t Compile” If your compiler doesn’t type-check our example, I have news for you. No, your compiler isn’t catching the bug. In fact, your compiler itself has a bug. Your compiler is broken. The Java specification says this example should type check and compile. Your compiler is supposed to implement that specification, and it’s failing here. It’s failing because it didn’t anticipate the corner case we created here. “But It’s Just a Corner Case” How many bugs have you dealt with have been corner cases? A good programmer is supposed to anticipate and handle corner cases, not just excuse a bug because it is hard to create. Sure, sometimes resources are constrained and you might decide that the bug is low priority, but you can only assess its priority after you identify it. So even if this bug turns out to be low priority, which I’ll get to in a bit, it’s still important to know it exists. “But an Exception is Thrown” And thank god one is, and purely due to some good luck! Remember how a call to on a secretly checks that the returned value is actually a ? This secret check is done for backwards compatibility with raw types. It shouldn’t be necessary when there are no raw types in the program. But thanks to it, a is always thrown when our example is run (if your compiler is smart enough to compile it). get List<String> String ClassCastException So had history been a little different, either with Sun deciding to throw out backwards compatibility after adding generics, or with Sun adding generics into the JVM, or with Java first being released with generics, then this exception would not be thrown. Instead I could cast anything into an and get direct access to the raw bytes of many objects, which I could then use to inject arbitrary code (using to bypass security measures). int[] return-oriented programming “But No One Would Ever Write This” You probably would never write this, and your colleagues would never write this. That reasoning is good to apply in many situations. I in fact do this ; it’s a huge part of my research agenda. But you have to be careful where you apply it. Soundness is a security guarantee, not a usability concern. What matters is if can write this, because then that someone can get around the security measures that people have placed their confidence in and do whatever they would like to do. In the case of soundness, it’s the malicious programmer you should be worried, not just you and your friends. all the time someone “But The Code Shouldn’t Type-Check” Many people call out the type and say it should be invalid because requires its second type argument to be a subtype of its first, but , and every supertype of , is not a subtype of . But this reasoning confuses invalidity and uninstantiability. It’s actually faulty reasoning that’s been around in both industry and academia for at least as long as I’ve been out of high school (which has been a while). Constrain<U,? super T> Constrain T T U Here’s a simpler version of the fallacy: class Foo<T extends Number> {Number foo(T t) { return t; }} Is it safe for to be a valid type? For example, is the following code safe: Foo<String> Number bar(Foo<String> foos) { return foos.foo("NaN"); } The conventional wisdom up until now, and probably your gut instinct, would say this is unsafe, since it turns a into a , but the fact is that it’s completely safe. Here’s an equivalent program that illustrates why: String Number interface IFoo<T> {Number foo(T t);} class Foo<T extends Number> implements IFoo<T> {public Number foo(T t) { return t; }} Number bar(IFoo<String> foos) { return foos.foo("NaN"); } For any class with a constrained type parameter, I can just make a corresponding interface without that constraint and use that throughout the program. This will behave identically to the original program. (There are some clarifications to this, but I’ll leave them to the .) paper So why does it seem like should be invalid? How is it safe? Well, the answer to both is the same: is uninstantiable. You’ll never be able to create an instance of because is not a subtype of . Thus the seemingly unsafe invocation of in will never happen because you can’t invoke a method of an object that can never exist. Foo<String> bar Foo<String> Foo<String> String Number foo bar So by this same reasoning it’s perfectly safe for to be valid. You’ll only ever be able to have an instance of it if is a subtype of at run time, satisfying the constraint. Constrain<U,? super T> T U But is inhabitable in Java, because inhabits every reference type. So keep that in mind as I explain why this program type checks. Constrain<U,? super T> null Wildcard Capture A Java wildcard, , is not a type. It is simply a piece of syntax representing something unknown. And different wildcards can represent different unknown types. So to reason about wildcards, Java uses a process called . ? wildcard capture Suppose we have an expression of type . There is a wildcard in the type of this expression. The type-checker doesn’t know what it represents, but it does represent something, so the type-checker gives that unknown something a temporary name, say . Furthermore, the type-checker knows that the unknown something must at least be a supertype of . Thus the type-checker views as having type where is some supertype of . e Constrain<U,? super T> X T e Constrain<U,X> X T But the type-checker knows something more. It knows that must be a valid type argument. Consequently, the type-checker also notes that must be a subtype of . We call this the constraint on the wildcard, whereas is the explicit constraint on the wildcard. I found out that, although uncommon, this implicit constraints are in fact used for type-checking a number of Java libraries. The gives a specific example showing why implicit constraints are important. X X U implicit super T paper Now look at the example again. In the call to , the type-checker does the aforementioned wildcard-capture process and views as having where is (explicitly) a supertype of and (implicitly) a subtype of . Consequently it infers to be the type argument to and uses its explicit and implicit constraints to type-check the rest of the invocation. bind.upcast(constrain, t) constrain Constrain<U,X> X T U X bind.upcast Thanks, Null! Okay, so if the wonky type isn’t the source of unsoundness, what is? Well, amazingly enough, it turns out null pointers don’t just cause bugs in programs, they cause bugs in type systems too! The reasoning for wildcard capture completely forgets about null pointers. It assumes there must be some actual for some , an assumption that manifests itself in the implicit constraint on . So all of this boils down to a null-pointer bug. But unlike most null-pointer bugs, this one took 12 years to discover. Oh, and it’s also not nearly as easy to fix as most null-pointer bugs, since every feature involved is used in practice. But the Java team is working on fixing it. And before you once more insist that the solution is to disallow the type, realize that that kind of reasoning is what delayed core Scala’s proof of soundness (without null) for a whole decade, and I’m not particularly eager to spend a decade solving this. Constrain<U,X> X X Constrain<U,? super T> P.S. Future language designers, please keep this in mind! Especially if you’re not compiling to the JVM. Java was lucky it was held back by backwards compatibility; you may not be so lucky. is how hackers start their afternoons. We’re a part of the family. We are now and happy to opportunities. Hacker Noon @AMI accepting submissions discuss advertising &sponsorship To learn more, , , or simply, read our about page like/message us on Facebook tweet/DM @HackerNoon. If you enjoyed this story, we recommend reading our and . Until next time, don’t take the realities of the world for granted! latest tech stories trending tech stories

Java is Unsound: The Industry Perspective

This paper is available on arxiv under CC 4.0 license. Authors: (1) Pietro Ghezzi, Brighton & Sussex Medical School, Falmer, Brighton, UK; (2) Peter G Bannister, Brighton & Sussex Medical School, Falmer, Brighton, UK; (3) Gonzalo Casino, Communication Department, Pompeu Fabra University, Barcelona, Spain and Iberoamerican Cochrane Center, Barcelona, Spain; (4) Alessia Catalani, Department of Biomolecular Sciences, University of Urbino Carlo Bo, Urbino, PU, Italy; (5) Michel Goldman, Institute for Interdisciplinary Innovation in healthcare (I3h), Université libre de Bruxelles; (6) Jessica Morley, Oxford Internet Institute, University of Oxford, Oxford, UK; (7) Marie Neunez, Institute for Interdisciplinary Innovation in healthcare (I3h), Université libre de Bruxelles; (8) Andreu Prados, Communication Department, Pompeu Fabra University, Barcelona, Spain, Iberoamerican Cochrane Center, Barcelona, Spain, Department of Biomolecular Sciences, University of Urbino Carlo Bo, Urbino, PU, Italy, Institute for Interdisciplinary Innovation in healthcare (I3h), Université libre de Bruxelles, Oxford Internet Institute, University of Oxford, Oxford, UK, and Blanquerna School of Health Sciences, Universitat Ramon Llull, Barcelona, Spain; (9) Mariarosaria Taddeo, Oxford Internet Institute, University of Oxford, Oxford, UK, Blanquerna School of Health Sciences, Universitat Ramon Llull, Barcelona, Spain, and The Alan Turing Institute, London, UK; (10) Tania Vanzolini, Department of Biomolecular Sciences, University of Urbino Carlo Bo, Urbino, PU, Italy; (11) Luciano Floridi, Oxford Internet Institute, University of Oxford, Oxford, UK, Blanquerna School of Health Sciences, Universitat Ramon Llull, Barcelona, Spain, and The Alan Turing Institute, London, UK. Table of Links Abstract and Introduction Methods Web search and content analysis Results Discussion Conclusion and References Table 1. Example of classification of webpages Table 2. Percentage of vaccine-negative webpages in different SERPs Discussion The aim of this research was to investigate whether search engines focused on privacy preservation ranked webpages with higher and/or lower levels of IQ (interpreted as EBM based content i.e. vaccine-positive rather than vaccine-negative) differently to the primary commercial search engines. In turn, this answered the research question “What is the current relationship between search engines’ approach to privacy and the scientific quality of the information they return?”. The results indicate that currently privacy-enhancing search engines often give more visibility to webpages promoting vaccine hesitancy or with a clear anti-vaccine position than Google. This is in agreement with the findings from a recent study by the Economist which analyzed 175,000 news links returned by Google to demonstrate that the search engine’s algorithm favorstrustworthy publications 20. Reputation and trustworthiness are key factors included in Google’s ranking algorithm. In 2019, Google published search quality evaluation guidelines, 4 which define webpages containing information that may affect the users’ health or financial stability, as “your money your life” (YMYL) pages. These guidelines reveal that when rating YMYL webpages, Google looks at the three criteria of Expertise-Authority-Trustworthiness (EA-T) and states “High E-A-T information pages on scientific topics should be produced by people or organizations with appropriate scientific expertise and represent well-established scientific consensus on issues where such consensus exists”. Thus, in the case of Google, the bandwagon heuristic mechanism of assessing medical information credibility is working in favour of promoting IQ. This is perhaps because those responsible for driving up the ‘reputation’ of specific websites by, for example, linking to them, have higher levels of eHealth literacy and therefore act as pseudo-gatekeepers protecting those with lower eHealth literacy from poor IQ results by ensuring that websites providing inaccurate online health information have a low ranking in the search results. In the case of privacy-preserving engines this appears not to be working – potentially because they do not track ‘reputation’ factors, which could be seen as proxies for IQ and credibility, e.g. clicks and bounce-rate, and so have no gatekeepers (pseudo or otherwise) working to limit the circulation of misinformation. To our knowledge, the algorithms used by these ‘alternative’ search engines are not public - Qwant states that they use their own algorithms5 - but despite this, we found a large overlap between the SERP of Qwant and those of Bing and Ecosia. Likewise, Ecosia and Swisscows showed a similar overlap (70%) with Bing. This means that it is not possible to check what factors determine the outcome of the decision making processes of the search engines algorithms, and hence identify those elements that contribute to circulate misinformation. Even without being able to check the exact mechanisms for the overall poorer results, the results suggest that, currently, decisions made by search engines to prioritize privacypreservation may have a negative impact on the IQ of results returned to users in health contexts. The pledge to provide independent and unbiased results or not to promote or hide websites based on political or moral interests can be seen as ethically ambiguous, in view of the potential consequences of pointing to scientifically unsound health information. Medical ethics requires that patients give informed consent before treatment and must, therefore, be informed accurately of the risks and benefits associated with treatment, something that is not possible if the search engine provider used by an individual is returning results with low IQ. From this consequentialist perspective, it is inherently unethical choosing not to interfere with a search engine’s ranking algorithm to ensure ‘manually’ that results of higher IQ are prioritized, whilst those of lower IQ are suppressed. This builds on arguments already made in the wider literature about algorithm ethics 21,22. For example, the Association for Computing Machinery (ACM) code of ethics and professional conduct includes, as a general principle, “avoid harm” along with that of “respect privacy” 23, which aligns with the Hippocratic oath. Specifically, the implication that the current design of privacy-preserving search engine algorithms underestimates the need for evaluation of IQ fits into the wider discussion about algorithmic design and how to ensure design decisions are made to protect and incorporate key values such as IQ. It is necessary, but insufficient, to design search engine algorithms that index purely on ‘relevance’, they must also be designed to index on quality. The challenge lies in the ability to do this in a way that balances the need to accept different perspectives (particularly those that are rooted in different cultural, religious or social ideals) whilst also filtering for IQ. Supporters of such arguments, including the authors, note that this requirement necessitates making the workings of search engine algorithms more transparent 24 to ensure their ethical compliance. Providing information on vaccines that is based on misinformation or disinformation (including studies whose data or conclusions have been shown to be wrong) is a deceptive practice, which goes against the basic tenets of medical and business ethics 25. This is in line with those who argue that the promotion of ‘alternative medicine’ is unethical because it lacks evidence and transparency of clinical efficacy and should be considered ‘false advertising’ 26. Online service providers have a moral responsibilities to ensure that users access health information that is scientifically validate 27. Misinformation and disinformation concerning healthcare circulating on the internet can have severe consequences and lead to widespread harm. Consider the example of South African president Mbeki, who delayed introducing anti-retroviral drugs in favor of alternative medicine based on information obtained from HIV-denialist internet websites, a decision estimated to have resulted in over 300,000 deaths 28. More recently, a cancer patient died in China after following an alternative, non-approved therapy they found using a search engine 29. In response Chinese authorities issued new rules that require search engines to provide “objective, fair and authoritative results”. Moral responsibility follows on the level of harm that misinformation and disinformation on healthcare may cause. It could be argued that there is a greater onus on Google – and other commercial search engine providers – than on alternative search engines to take these considerations into account when designing or interfering with algorithms for the purposes of promoting ethical compliance, given their larger market share. Google currently has over 90% of the worldwide market share6 and therefore has the potential to indirectly ‘cause harm’, through the potential promotion of low IQ webpages on vaccinations, to a great many more people than any of the alternative providers. However, studies have shown that those who hold anti-authoritarian views, openness to (potentially) controversial opinions, and an interest in alternative medicine are, in some cases, already more likely to hold vaccine-hesitant beliefs 30. These are also the individuals who are most likely to use alternative search providers given their sensitivity to privacy and tracking concerns. Therefore, while the alternative providers might reach a proportionally smaller audience – they are reaching an audience that is already more receptive to antivaccine information 31, and therefore more vulnerable to its effects. In other words, unless the alternative providers take steps to rank vaccine-related search results according to IQ, they may cause greater harm to those they do reach, meaning that the net negative impact is still greater even though the number of individuals they reach is smaller.

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