A new project aims to make it easier for PLC programmers to implement secure coding practices by cataloging useful files and functions

New Project Analyzes and Catalogs Vendor Support for Secure PLC Coding

Microsoft’s Copilot AI has officially launched for Windows 11 devices. Here’s everything you need to know about enabling and disabling the feature suite.

Microsoft Copilot: Here's everything you need to know about the company's AI assistant

computer security, software security and more. This cohort-based program trains computational specialists who can construct models, develop algorithms, and write software using state-of-the-art graduate-level knowledge and techniques. The program has been ...

Master's in Professional Computer Science

Despite economic fears, Gartner predicts spending on software will increase 11% in 2023, up to $879 billion from $790 billion in 2022. Why? The answer is simple. No business can survive in today ...

Four Crucial Steps For Successful Software Implementation

If you’re on a computer and you get a text on your phone, wouldn’t it be great if you could reply without picking it up? Yes, it would, and there are great apps and services that enable just ...

How to send a text message from a computer

You can have multiple cursors on your computer. However, you will need to use specialized software or hardware configurations. You can use the MouseMax application on Windows to get more than one ...

Can you have 2 cursors on 1 computer?

TRIPS is an important treaty under the WTO. The TRIPS Agreement represented a major expansion in the scope of copyright protection for computer software. TRIPS brought software under the purview of the Berne Convention by defining it as a literary work.

Preserving national integrity: Shunning software piracy

PC hardware is nice, but it’s not much use without innovative software. I’ve been reviewing software for PCMag since 2008, and I still get a kick out of seeing what's new in video and photo ...

The Best Photo Editing Software for 2023

Computer vision at the edge is unlocking actionable ... Dell Validated Designs connects multiple ISVs (independent software vendors) and partners to optimize application-based solutions that ...

Delivering 5 Key Outcomes With Computer Vision At The Edge

Iflexion

iflexion

5 Ways Tech Is Transforming eCommerce Logistics Despite logistics appearing as a term back in the 1940s, it has been pursuing the same objectives through decades: ● enhancing supply chain performance, including service quality ● providing transparent information exchange ● identifying optimal routes and solutions in the manufacturing process There are different types of logistics depending on the business niche. These are transportation, manufacturing, informational, distributional, storing, commercial, and marketing logistics, to name a few. Considering the fact that the global economy is based on unified principles, resources, and processes, all types of logistics share similarities. In eCommerce, which is one of the most profound business niches out there, logistics play a key role in the optimization of customer service and the decrease in costs. The thing is, as opposed to offline business, online sales points usually service large numbers of people from various locations around the world. Thus, optimized supply chains in digital retail is a crucial factor in ensuring successful business operation. Research shows that global logistics spending is set to hit , and the expenses are getting higher by the year. Let’s discuss where technology appears in this equation, and how it transforms the entire logistics industry. $10.6 trillion by 2020 Photo by Ray Kacaribu on Unsplash 5 Ways Technology Is Transforming eCommerce Technologies are coming to change the way logistics providers operate. suggest the following list of five areas where digital innovations are impacting eCommerce logistics most. Ecommerce consultants from Iflexion Backed by automation, artificial intelligence is already being successfully adopted in various modern solutions for logistics, such as warehouse robotics, computer vision-based barcode scanning, drone delivery, etc. Artificial intelligence and automation. The key value of artificial intelligence for logistics today is that it allows rationally planning supply chains (for instance, with the help of AI algorithms, it’s possible to select most optimal routes for transporting a product from point A to point B). At the same time, automation solutions promise to replace a significant chunk of many routine responsibilities found in large-scale call-centers and other customer support departments. The notion of the ‘Internet of Things’ first came up in the late 90s, but it has found the practical application in logistics not that long ago. For example, GPS-based geolocation data generated by RFID tags can facilitate product shipment tracking. Using historical data analysis also allows enhancing logistics operations. Internet of Things. Generally speaking, IoT is finding many applications in logistics: active/passive electronic RFID tags; use of global low-voltage networks instead of the traditional Internet; satellite trackers helping to monitor product locations in real time. All that makes real-time data analytics possible, which is crucial for every single medium- or large-scale online store. A successful case of implementing IoT in the logistics-related workflow is the one from . The company producing hop for its authentic ‘fresh hop’ and ‘wet hop’ beer implemented a special location tracking technology for its time-sensitive products. As their hop is not dried but is sent for immediate use in breweries, it is crucial for the company to deliver raw materials in no longer than 12 hours, otherwise, the beer would lose its quality. Apart from tracking the current location, the company’s employees also use special indicators to collect data on the temperature and dampness during transportation. Rogue Ales Analytics in real time is not an ‘IoT-exclusive affair’ when it comes to logistics. Much of it is made possible with Big Data. Real-time analytics using Big Data. Operating large volumes of data is always a rather complex and cumbersome task if done manually. The tiniest lack of attention spawns risks of provoking errors that will negatively affect your business processes further on. Moreover, as the volumes of data grow, their processing requires a more dedicated workforce, which also brings in human factor-related risks into play. That’s why special solutions for automatic processing of Big Data were developed in order to mitigate these risks. In logistics, such tools can aid significantly by identifying the patterns and trends while also helping to predict the overall efficiency of a logistics company’s performance. Such Big Data solutions are actively adopted for supply chain optimization, fuel tracking, predictive maintenance of vehicles, and so on. For an eCommerce business processing thousands of orders from customers around the world, transportation is a big issue that potentially affects customer satisfaction if the delivery is late. Delivery destinations are random in general, and transport operators seldom have access to resources to optimize their route planning and shorten delivery cycles. Route planning. However, this complex issue can be resolved with the help of dynamic route planning systems, more and more of which are appearing by the day. They help to decrease planning time to a few minutes and allow controlling the process of cargo loading and delivery online. Last but not least, they also help to significantly optimize transportation expenses. Reliability is the cornerstone of logistics businesses, helping them to keep operations efficient. However, if the main system crashes and data gets lost, business downtime is inevitable unless you take care of the safety appropriately. Digital twins of supply chain processes. The simplest way to do that is to regularly make data backups in the cloud, pairing physical assets and processes with their digital simulations. In particular, creating digital copies of the data used in your logistics processes, you decrease the chances of one of your network’s nodes failing at some point and making your workflow stop for an indefinite period of time. Photo by Yu Kato on Unsplash The Bottom Line Summarizing the overview above, the listed technologies can help eCommerce projects become more profitable for owners and affordable for consumers at the same time. The combination of artificial intelligence, IoT, Big Data, real-time analytics, and digital twin technology is what eCommerce businesses should look out for to optimize their logistics processes. Implementation of these innovations promises to create more efficiencies, reduce delivery time and costs, as well as contribute to customers’ satisfaction with digital retailers.

5 Ways Tech is Transforming eCommerce Logistics

Cybersecurity is a broad term that encompasses all the technologies geared toward protecting networks and computers, along with the software and data kept on them. While more and more data today can be accessed via the internet, online security has become the major issue for businesses. The risks associated with online security are constantly and quickly increasing. The number of internet users steadily grows as well as the amount of information stored online. At the same time, hacking techniques evolve, including numerous social engineering tactics. As a result, online security issues are likely to become more prevalent, particularly in the business sphere. Menlo Security suggests that 42% of Alexa top 100,000 websites are compromised. So what do you need to know to safeguard your online business? We explore five online security measures that will help keep you on the right track. annual research #1. Remember that S in HTTPS is for Security The HTTPS protocol ensures that the data exchange between the user and your website is encrypted and has no intermediaries. It proves that your site is actually your site and not its “shadow copy” created by a hacker, which increases the trust of potential visitors. Apart from security, HTTPS means good SEO (although it’s not reflected in the acronym). Back in 2014, Google announced that they would use HTTPS as a ranking signal, which became one of the biggest incentives for webmasters. As a result, HTTPS has become a standard that every self-respecting organization should follow. The key point here isn’t so much HTTPS encryption, as it is the ability of big companies like Google to set industry standards. Search engines, on which most online businesses are dependent in some way, are the obvious example but legislation is another key area to consider. It will be vital in the future that developers are aware of the demands of both big companies like Google and legislators, and that they tailor their online security measures accordingly. #2. Use Third-party Tools (But with a Caution) One of the biggest areas of growth in cybersecurity over the last few years has been the development of third-party software aimed at developers. There’s often an assumption on the part of businesses that developers have sufficient knowledge to adequately protect websites and apps from attack. Yet this isn’t always the case. Automation is another key part of the picture in regards to the use of third-party software. Tools that allow developers to automate important aspects of the security testing process are vital for allowing the proper allocation of resources and for ensuring consistent and up-to-date testing in the long-term. The widespread implementation of automated processes is also allowing developers to focus their attention on app vulnerabilities that are difficult to detect with non-human technologies. Of course, a tool is just a tool, you still need a professional to choose the right one, fine-tune it, and make the most of it. Note that unproven open-source tools may harm your software instead of protecting it. #3. Watch Your IoT Because the focus of security developers has largely been on desktop browser-based apps, software for smartphones and other connected devices has been left somewhat vulnerable. And hackers are increasingly taking advantage of these opportunities. The fast-growing ecosystem of devices that make up the internet of things also presents another prime hacking opportunity, one with potentially far more serious consequences than traditional website breaches. that by 2020 there will be more than 20 billion connected devices worldwide. That means an immense attack surface and ominous consequences as to how stolen information may be exploited. Connected devices are now used for everything from tracking the user’s location to managing and monitoring hospital equipment. Think of the havoc hackers could wreak if they are able to disrupt these systems. Gartner predicts To secure your IoT devices, keep the firmware up to date, change the default credentials, and disable any P2P features. There are also special tools for IoT security scanning (go to #2). #4. Keep in Mind Users’ Responsibilities In any discussion about web security, it’s always important to highlight the issue of human weakness. The fact that most consumers are unaware of security threats, particularly in regards to B2C, but also within the B2B sphere as well, is a cause of mounting concern. Companies are addressing this problem in two ways. First, the integration of mandatory two-step authentication into apps is becoming increasingly common. This is especially true in areas where security is of vital importance, such as banking. Examples include messaging a pin number to users after they have entered their password or requiring further security details when a login attempt is made from a new location. Secondly, users are actively being encouraged and advised to adopt safer browsing habits, particularly in the way that they use and store passwords and share data online. When it comes to security, an extra reminder can’t hurt your users. #5. Balance the Speed and Quality of Web Development The huge increase in the demand for web apps and complex site architecture is something of a double-edged sword. Whilst it has pushed app-related security issues into the limelight and resulted, as mentioned, in the creation of a host of third-party apps, it has also prompted development companies to streamline and speed up their processes to meet the increased demand. In many cases, security has suffered as a result. Attempts to address problems arising from this phenomenon have taken a number of forms. According to the experience of , applying the DevOps approach helps structure processes and increases productivity of a web development team. This allows for speedy completion of projects whilst taking advantage of expertise from a number of key people and departments within the organization. web development company Iflexion Conclusion More devices and more users mean greater risk. It’s vital that companies of all shapes and sizes work from an understanding of the nature of these risks when shaping their approach to web development. Not only will they be providing a safer experience to their customers, but also it’s very likely that they will save both time and resources in the process.

5 Online Security Measures to Survive as an eBusiness

From news outlets to social media, the topic of AI seems to come up time and again. With so much focus on the topic, it’s easy to dismiss it as nothing more than the latest buzzword. But this would be a mistake. AI is a broad area that encompasses a number of cutting-edge tools that can add real value to almost any company’s business strategy and operations. Taking a deeper look at this technology can help explain its ongoing popularity, as well as provide key information that can help you realize the power of AI with respect to your own business intelligence goals. What Is AI? AI or artificial intelligence is a branch of computer science that focuses on intelligence in computerized systems. Today, this intelligence is achieved mainly with the help of machine learning (ML) algorithms and large datasets fed to these algorithms. Discovering patterns in data, machines learn different tasks, from natural language processing and computer vision to complex decision-making. list a range of feasible real-world applications of this ability of ML models to learn. AI consultants from Iflexion The Value of AI for SMEs and Enterprise Companies The applications for AI are widespread, whether you’re an SME or an enterprise business. A study by analysts predicts that 80 percent of customer interactions will be managed by AI-powered chatbots and intelligent assistants by the year 2020. Improved customer experience and a reduction in operational costs are just a few of the benefits that companies, both big and small can expect when adopting an AI solution. Of course, businesses can also expect more comprehensive customer data and greater ease when it comes to translating that data into meaningful actions via machine learning. Gartner Enterprise organizations that choose to use an intelligent automation system can reduce costly redundancies and complexities in their operations; significantly improving company-wide efficiency and even reducing the amount of time that it takes to get products and services to market. According to , robotic process automation (RPA), a form of AI that uses software robots to automate processes, can even help businesses meet industry compliance regulations and improve internal auditing capabilities. PwC Many companies have more data than they know what to do with. For data-intensive companies, AI is an essential tool for smarter extraction and analysis of Big Data. Likewise, RPA can simplify the data process from beginning to end, covering everything from retrieving data, to aggregating it and even transferring it into documents. When coupled with machine learning for data analysis, the entire data process becomes more streamlined and less error-prone, ensuring a more accurate assessment of data and any derived insights. How Real Companies Are Using AI The power and profitability of AI hasn’t been lost on investors. A 2016 Technology Vision report by Accenture found that investments in artificial intelligence startups had increased 20x in the previous four years. Technology Industry leaders have also taken notice, investing billions of dollars in AI. alone has acquired more than 14 AI-based startups and has an entire division solely dedicated to advancements in this sector, complete with product lines ranging from cloud apps to smartphones and intelligent personal assistants. Google The transportation industry, specifically ride sharing applications like Uber and Lyft, also use AI. Machine learning is applied to help minimize ride wait times and match passengers with those going in the same direction, optimizing the customer experience while reducing driver mileage and traffic delays. Banking is an industry that heavily utilizes AI, applying it to everything from fraud detection and check depositing (which uses image recognition) to personal and business credit approval or rejection decisions. All of which, are based on data and the business intelligence that it provides. If you’ve ever used a streaming on-demand service like Netflix or Amazon, the movies and television program suggestions that you received were provided by a recommender system. This specialized machine learning algorithm is a form of AI. But major businesses aren’t the only ones using AI. SMEs and enterprise organizations are also using it to automate payroll and HR, effectively manage data and eliminating tedious and repetitive tasks that can be better performed by automation. The last of which can dramatically improve company efficiency. In fact, companies like have entire AI product lines that are designed to help almost any business save time and money. Salesforce The Future of Business Intelligence and AI The business landscape has become increasingly competitive. As a result, only those companies that actively seek out the most innovative technologies and processes can truly gain a competitive advantage. Right now, AI may seem like a nice-to-have tool but it is quickly becoming the standard for everything from data management to intelligent automation. Today, about 15 percent of all businesses use AI. However, a survey conducted by found that more than 30 percent of companies surveyed plan to add it to their agenda this year. Likewise, according to the , half of all of the largest companies (or those with more than 100K employees) already have a defined AI-based strategy. The message is clear: AI is here to stay. Adobe MIT Sloan Management Review Businesses that aren’t in the tech space may feel like AI just isn’t for them. But marketing, which impacts nearly every company, regardless of industry, is one area that is already being strongly influenced by AI. Bespoke, or one-to-one, marketing has the potential to change the way that brands connect with consumers in a profound way via highly personalized messages, applications and even customer services experiences. In fact, a study by found that 29 percent of respondents believe that consumer personalization will be the next big marketing trend. BrightEdge Conclusion AI is one of the hottest topics of the day. But it’s more than just a buzzword. This powerful technology is already revolutionizing the way that companies do business and interact with their customers. Understanding what AI is, how it can be of value and its future in the world of business intelligence is essential for any company that wants to gain a meaningful advantage in the increasingly tech-driven business world.

From news outlets to social media, the topic of AI seems to come up time and again.

About Performance Testing Performance testing is a method of identifying whether software (a web application) is capable to handle a high load, among other possible performance issues. Therefore, the ultimate goal of a performance test is to analyze the overall performance against heavy loads. Apache JMeter is an open-source tool that can be used exactly for this purpose. What is a Single-node Server? This is the case when a server runs on a single machine only. If the server crashes due to some issue, there will be a downtime until the issue is fixed. What is a Two-node Cluster? A two**-**node cluster is a setup where two servers are configured with high availability. If clustering is used, there won’t be downtime due to a server crash. The advantage of having your servers in a cluster environment is that if one server is unavailable due to a crash or some other failure, the other node will operate as the primary one and the system will be operated without causing downtime for users. Why Apache JMeter Is the Best Tool for It Apache JMeter enables test performance for static and dynamic resources. Static resources include JavaScript, HTML, and others. Dynamic resources include JSP, Servlets, AJAX, and more. In addition, Apache JMeter has more properties that make it a suitable tool for performance and load testing: · Overall performance analysis presented as a report · A performance testing report containing analysis of different attributes, such as response time, page load time, throughput, error rate, and more · Optimization suggestions provided in a report · Graphical analysis reports with metrics such as transaction per second, hits per second, etc. · Ability to identify the maximum number of concurrent users that can be handled without the server crashing · Ability to extract data from a number of response types such as HTML, JSON, XML, etc. · Support of an extensible core with pluggable samplers, scriptable samplers, pluggable timers, and visualization plugins · Ability to integrate with any third-party open-source libraries such as Maven, Gradle, and Jenkins · Support of multithreading frameworks A performance test can be carried out in either of the two ways mentioned below: this is a testing type that models the expected usage by simulating multiple concurrent user accesses. Load Testing: this is a testing type used to identify the maximum load that can be handled by the server. When the load goes above the benchmark, the server may start responding slowly. Stress Testing: In the following, we will see how we can measure server performance using Apache Jmeter using the standard practice adopted at . Further, I will explain how this can be extended to test the performance of two servers running in parallel in a two-node cluster environment. You can use any web app that you are familiar with to conduct the test. I will be using eBay for this purpose. A1QA This process will consist of five main steps: Add a Thread Group Add necessary JMeter Elements Add Graph Results Run the test Obtain and analyze the results 1. Let’s Get a Thread Group The Thread Group element will be the initial step of the test plan. The Thread Group is a set of threads that will be executing the same scenario. This defines a pool of users participating in a particular test case. Other samplers and controllers need to be included inside the Thread Group. This article assumes that you have installed Apache JMeter on your machine. If not, please refer to for more details. this official guide How to add a Thread Group: Start Apache JMeter See the Test Plan option on the left-hand side Right-click on the Test Plan option Select the Add option Select the Threads (Users) option Select the Thread Group option After adding a Thread Group, you will see the Thread Properties section where you can control the properties of the Thread Group. : 100 (number of users connected to the web app: 100) Number of Threads ● : 10 (number of times to execute testing) Loop Count ● : 100 (time required for JMeter to get all the threads up and running. Also, this is explained as the delay time before the start of the next user.) Ramp-Up Period 2. Let’s Add Necessary JMeter Elements We will be using two elements in this use case. They are HTTP Request Default and HTTP Request. How to add an HTTP Request Default You can add an HTTP Request Default sampler in the following way: 1. Right-click on the Thread Group from the tree node 2. Select the Add option 3. Select the Config Element option 4. Select the HTTP Request Defaults option You can see input values for the server IP and Port on the control panel. This is where you will input the IP and the port relevant to the web app for which you are carrying out the performance test. In this tutorial, I will be using the IP of eBay. How to add an HTTP Request You can add an HTTP Request sampler in the following way: 1. Right-click on the Thread Group from the tree node 2. Select the Add option 3. Select the Sampler option 4. Select the HTTP Request option After adding the HTTP Request Sampler, you can see the Path field as shown in the image below. You can input a specific path to which you need to send the HTTP Request. For example, if you need to send the request to the Daily Deals section in eBay, you can check the path address relevant to that section from the website and input it under the path section: Path: /globaldeals So if you input /globaldeals for the path section, JMeter will send the HTTP Request to the complete URL . If the path field is blank, it will send the request to . https://www.ebay.com/globaldeals https://www.ebay.com I will keep the path-field blank. So, the requests will be sent to https://www.ebay.com 3. Let’s Add Graph Results You can use Graph Result Listener to observe the test results in the following way: 1. Right-click on Test Plan 2. Select Add 3. Select Listener 4. Select Graph Results 4. Let’s Run the Performance Test Before running the test, you need to save your test plan by giving a name such as Perf-test.jmx. Then click on the green mark in the toolbar to run the test. 5. Let’s Obtain and Analyze the Results While running the test, you can observe the test results which are displayed as Graphs in real time. You can see the graph that shows the performance results obtained for the sample use case we tried, in which 100 users accessed eBay server. The statistics displayed at the bottom of the graph according to their colours: ● Black shows the total number of current samples sent. ● Blue shows the average value for the total number of samples sent. ● Red shows the standard deviation. ● Green shows the throughput rate (This is responsible for the total number of requests per minute that the server handled) To gain an idea about the performance of the eBay server, we need to focus on two parameters: throughput and deviation. is the ability of the server to handle a heavy load. The higher this value, the better performance of the server. Throughput In this sample test, the throughput of the eBay server is 199.609/min. This means the eBay server can handle 199.609 requests per minute. This value is quite low compared with other web servers such as Google. Likewise, you can take the values for different servers and compare them with other servers to get an idea about the overall performance. indicates the deviation from the average. The smaller value of deviation, the better server performance. Deviation Extending the Performance Test to Two Servers Running In Parallel In a Two-node Cluster Environment Let’s assume your servers are deployed in a cluster environment where the cluster operates with two nodes. Let’s see how you can carry out a performance test against a setup similar to this: Add Thread Group Add necessary JMeter Elements Add Graph Results Run the test Obtain and analyze the results Step 1 This is similar to what I explained above. You can add a Thread Group by following the same steps. After adding the Thread Group, configure the properties as shown below. Step 2 Now, we need to add two HTTP Requests to send requests simultaneously to two nodes. There, you can follow the steps that I have explained above to add an HTTP Request. Under the Methods section, specify the method of the request. As I am sending a POST request, I have changed it for the type POST. Then, under the Path section specify the URL of the server including the IP address and the port. An example is shown below. You need to add two HTTP Requests including the same configs other than the server URLs. When two servers are running on a cluster, the URLs for the two servers will be different. Therefore, when you are adding the second HTTP Request, specify the URL relevant to the second node. Step 3, Step 4, Step 5 will be similar to the ones explained above. Therefore you can just follow the same actions. Summing Up In this article, we learned how to carry out a performance test of a web server with a single node and how to extend the test to a two-node cluster using Apache JMeter. We also discussed how we can analyze and compare the results with those of other servers.

Performance Testing of a Single-node Server and a Two-node Cluster with Apache JMeter

People prefer eCommerce solutions when shopping. A survey of 2,500 participants conducted by found that more consumers are shopping for everyday items online. However, the modern digital shopper is easily turned off by poor user experience (UX). This is partly why eCommerce testing for your website and/or mobile application is critical prior to launch. This article looks at effective ways of improving eCommerce testing so you can truly serve your customers. Periscope Are There Any Other Reasons Why We Test eCommerce? Yes, lack of testing means you’re willing to compromise other things that quickly become business nightmares, such as data security. Truly knowledgeable eCommerce development companies not only build your application but also test for exploitable vulnerabilities. This is paramount. Simply put, the level of business success you gain is highly dependent on ensuring that your platform is secure and bug-free. There’s a massive growth expected in online retail, considering that there were over 2.5 trillion USD in eCommerce sales worldwide in 2018. Sales in eCommerce retail — Statista Companies need reliable platforms to handle all that growth, but eCommerce solutions can fail and if they do, it’s often costly. For instance, every second that Amazon is unable to transact or serve its customers can mean millions in losses. Fortunately, virtually every catastrophic eCommerce software failure can be avoided or significantly reduced with . The primary objectives here are a) to inspect functionality, b) to gauge how friendly it is for a user, c) to correct any bugs and security vulnerabilities. web testing Two main steps in the entire process need to be carried out with care. Know What You Intend to Test Proper eCommerce solution testing requires knowledge in the commerce domain and effective planning. That’s why the first thing to do is put together a list of what you’re going to test. Typically, that list will include the following components. UI Functionality and Workflow Important customer touch points must be tested for proper functionality. This involves testing all the core areas of your site that a visitor would interact with. These include but are not limited to primary landing pages, catalog and its categories, and shopping cart. Note that eCommerce platforms are normally customized to meet business needs, so website layouts and key pages may vary accordingly. In all cases though, your main pages would usually consist of the homepage, login/accounts, product, item description, order form, purchase confirmation, and search, among others. Testing will ensure the critical functions of your UI work as intended (for example, product categories sort by relevant products only). Things like typography, font size, color, wish list, and sorting/filtering should be thoroughly tested. Product classification allows customers to pick what they’re interested in fast. This function needs to be so intuitive that it’s a no-brainer for the visitor. The following screenshot from Best Buy is a great example of excellent product categorization. In addition, there’s nothing worse than visiting an eCommerce product page that features a zoom option for images or some other functionality that isn’t working. So check all your features, including but not limited to related items, product description and comparison pages, add-to-cart, etc. It all needs to be in great shape. You can eliminate plenty of guesswork by simulating the visitor and checkout journeys. Essentially, put yourself in the typical prospect’s shoes. For added measure, use ethical tracking systems like to see what people are doing on your site. Hotjar Browser Compatibility It’s necessary to test your eCommerce website platform on all web browsers. Firefox, Internet Explorer, Safari, Chrome, etc. all will be used by your prospective customers to access your site. However, they slightly differ in how they will display your website. Better go through browser checks at all levels and save yourself the headaches that usually arise from incompatibility issues. Mobile Internet browsing via mobile is dominating. People access the Internet through their smartphones now. Therefore, a mobile-first approach is recommended when developing eCommerce software. It’s super important that you test the responsiveness of your design on all applicable screen sizes (like tablets, iPhones, etc.). If you’re serving mobile users a different version of your desktop/laptop site or application, then you need to test that too. For that, you’ll need to add your mobile site testing to the plan too. Payment Processing Imagine that you were trying to pay for something and for some unknown reason, your Visa wouldn’t go through. You know you have the money but are forced to use your MasterCard instead. You contact the business and they say it must be your card. Your credit card company disagrees and yet, the business isn’t acknowledging that maybe a problem exists within their platform. The end result is frustration. Yes, not cool. Similar situations can plague a company for years without them ever noticing that there’s actually an issue until it’s too late. That is… typically after they’ve disappointed enough consumers. Run multiple tests on your payment gateways to ensure that your website is accepting and processing payments via all the options as intended. Security Assessment We’ve seen that take their collected PII (personally identifiable information) and financial data lightly. Don’t be one of those companies. what happens to companies Rigorous testing methods such as ethical hacking or SQL injections can be used to find and address all security issues. Also, you’ll need a robust firewall and virus protection system in place on the server side. SEO-Friendliness SEO (search engine optimization) is something that’s often overlooked by eCommerce website developers who are not even supposed to understand it. However, search engines are the #1 source of organic (or free) website traffic on the Internet, with social media at the second place. This means that your eCommerce application needs to be friendly to SEO techniques. That means being able to facilitate the use of advanced tactics that can improve the performance of your webpages on SERPs (search engine results pages). Develop Testing Scenarios eCommerce software testing is very different from testing desktop, mobile, or IoT applications, for example Visitors access such web-based applications with a browser that has to communicate with a web server to receive data (in fact, to download webpages). Many consumers frequent eCommerce platforms instead of physical shops as digital retail proves to be more accessible with 24/7 business hours. As a result, eCommerce sites are prone to failures caused by heavy workloads, especially around holidays. So identifying potentially crippling problems ahead of time is important. Hence, testing scenarios should be created with peak loads in mind. Also, web applications are likely to become the target of cyberattacks, which means your testing team should go through all potential hacking scenarios to protect your website security. So altogether, your testing cases should include the ones for security, performance, cross-browser compatibility, mobile responsiveness, and scalability. Failing to Test Leads to Loss eCommerce testing will help you find errors or potential dangers before launching your platform publicly. Trust it, customers will love you for taking the steps necessary to ensure their satisfaction, security, and privacy when interacting with your application. Thorough testing significantly reduces the chances of glitches and security breaches, which ultimately brings longevity and profitability to your business.

Effective Ways of Improving eCommerce Testing

In 2014, the publication of a study from a Google-led AI research team opened up a new field of hacking called an . The techniques the paper demonstrated not only changed our understanding of how machine learning operates but also showed in practical terms how one of the most commercially promising and highly anticipated aspects of the AI revolution could potentially be undermined. adversarial attack This new attack surface proved so intrinsic to the basic structure of deep neural networks that, to this date, the best minds in AI research are having difficulty in devising effective defenses against it. This was no Y2K-style fixable programming oversight, but rather a systemic architectural vulnerability, which, barring new breakthroughs, threatens to carry over from the current period of academic and theoretical development into the business, military, and civic AI systems of the future. If machine learning has a fundamental weakness equivalent to the scenario in cryptocurrency schemes, then its susceptibility to adversarial attacks would seem to be it. 51% attack Image is everything The core benefit of the new generation of neural networks is a capacity to deal with the visual world. AI-based can drive vehicles, analyze medical imaging, recognize faces, carry out safety inspections, empower robots, categorize image databases, create spaces in augmented reality, analyze and interpret video footage for events and language, and even assist in surgical procedures. image analysis software To accomplish this, an image-based machine learning system needs two resources. The first is a training set of still images or video, which allows it to gain a suitably accurate understanding of objects and events that it might later need to recognize. The second is actionable imagery, such as CCTV footage. From an economic standpoint, such a system must be designed to work with available material. Even if the image input has issues such as compression artifacts or low resolution, the AI must factor these limitations into its process. This high level of fault tolerance, as it transpires, enables attackers to poison the input data and affect — or even command — the outcome of the AI’s analysis. A malicious ghost in the machine The term “adversarial attack” was first coined in a led by Google AI researcher Christian Szegedy in 2014. By subtly altering wildly differing test images from the ImageNet database, the researchers caused a machine learning system to misclassify them all as “ostrich” on an instance of the popular and respected AlexNet convolutional neural network. paper Image Source The left column shows the original ImageNet source images. The middle column shows the subtle matrix of differences applied by the researchers. The right column shows the final processed images, which were all classified as “ostrich.” Not only was the procedure easily replicable, but, amazingly, it proved to be across different neural network models and configurations. broadly transferable The attack is a misuse of a fundamental feature in the conceptual model of image-based machine learning systems, exploiting the process of elimination that the system uses when estimating which label to apply to an image. Characteristics can be extracted from the image likely to be classed as — for instance — an ostrich, and then applied imperceptibly to non-ostrich images so that these become classified as “ostrich.” The math powering the elimination routine allows an attacker to systematically push the poisoned image over the boundary into the target classification. most The level of visual “perturbation” in such adversarial images is so low that both the human eye and the neural network are trained to discount them as noise. But the neural network cannot do this since this noise is shaped as a distilled “hash” for an established (though incorrect) classification. Therefore, the machine abruptly closes the analysis routine and returns the wrong result, and the reductionist mathematics of the neural network is turned back on itself in the form of an attack. Shock to the system Szegedy’s discovery was doubly astounding because it revealed the linear nature of the higher dimensional space of deep network learning models. Until this point, neural networks were thought to possess little linearity at this level of operation — an eccentric feature that, ironically, should protect them from systematized attacks like this, and which in fact contribute to the of artificial intelligence systems. controversial “black box” nature Instead, the attack was not only trivial to reproduce but quickly proved to have “real world” applications. In 2016, out of Carnegie Mellon built on the Szegedy findings to create a method capable of fooling a state-of-the-art facial recognition system (FRS) by the use of 2D-printed glasses. research Image Source First column: two researchers evade FRS detection. Second column: Researcher successfully identified as a target, actress Milla Jovovich [ source ]; Third column: Researcher successfully identified as a colleague; Fourth column: researcher successfully impersonates TV host Carson Daly [ source ]. By this stage, a plethora of new research papers had seized on the theory of adversarial attacks and begun to distinguish between misclassification (evading correct identification) and targeted classification (grafting a specific and incorrect target identity onto an image). In this case, the researchers were able to convince a facial and object recognition system that one of the male researchers was Hollywood actress and model Milla Jovovich and that another was TV presenter Carson Daly. Additionally, they were able to swap identities among themselves, or otherwise cause the FRS to fail to identify them. In all cases, the key to the subterfuge was the encoded texture printed out on their outsize glasses, which was sufficient to “hash” to the target for the machine learning system. Any doubt about the resilience of target-enabled textures was eliminated in 2017 when MIT researchers 3D-printed a specially crafted turtle model capable of convincing Google’s InceptionV3 image classifier system . that it was a rifle The encoded texture on MIT’s turtle object consistently reads as “rifle” in Google’s object recognition algorithm. Defensive efforts A wide range of countermeasures have been considered since the existence of the adversarial attack was revealed. Research out of Harvard in 2017 proposed in order to level the playing field and make crafted attack images easier to identify. However, the technique requires doubling the already-strained resources needed to operate a viable machine learning system. Even where variations on this “Gradient Masking” technique can be made practicable, . regularizing the image input counter-attacks are possible A 2017 Stanford research paper proposed , which artificially creates the non-linearity that researchers had, prior to the 2014 paper, presumed existed. However, peer criticism suggests that by stabilizing the gradient input. “biologically inspired” deep network protection the technique is easily negated A from the Institute of Electrical and Electronics Engineers (IEEE) evaluates four years of defense-oriented research following the disclosure of the adversarial attack technique and finds no proposed approach that can definitively and economically overcome the systemic nature of the vulnerability. The report concludes that adversarial attacks pose “a real threat to deep learning in practice, especially in safety and security-critical applications.” recent report Research out of Italy in 2018 that the adversarial attack scenario is immune to current countermeasures. agrees Widespread applicability of adversarial attacks The most alarming aspect of adversarial attack is its transferability, not only across different machine learning systems and training sets but also into other areas of machine learning besides computer vision. Adversarial attacks in audio in 2018 demonstrated that it is possible to add an adversarial perturbation to a soundwave (such as a speech recording) and completely change the speech-to-text transcription to a targeted phrase — or even conceal speech information in other types of audio, such as music. Research from the University of California It’s an attack scenario that , among other possibilities. The commercial exploitation of constant-listening devices in the home has already come under fierce criticism, and the spoofing of spoken user input has clear implications for invasive marketing campaigns. threatens the integrity of AI assistants Adversarial attacks in text A 2017 from IBM’s India Research Lab outlines an adversarial attack scenario based on pure text input and observes that such a technique could be used to manipulate and deceive sentiment analysis systems, which are using natural language processing (NLP) techniques. At a widespread level, such a technique could potentially enable a campaign of analytics-led misinformation in the category of “fake news.” paper Implications of the adversarial attack vulnerability for machine learning Ian Goodfellow, the creator of and a key contributor to the debate about adversarial attacks, has that machine learning systems should not repeat the mistake of early operating systems, where defense was not initially built into the design. Generative Adversarial Networks commented Yet the IEEE report, backed up with other research overviews, suggests that deep learning networks had this weakness baked into them from conception. All attempts to counter the syndrome on its own terms can be repulsed because they are iterations (and counter-iterations) of the same math. What’s left is the possibility of a “firewall” or sentinel approach to data cleansing, where satellite technologies evolve around a continuously vulnerable machine learning framework, at the cost of network and machine resources, and a diminishing integrity of the entire process. Commercial concerns seem to be taking precedence. To date, the only real-world example of adversarial attack to have impressed the potential gravity of the problem to the media was when a team of researchers caused a machine learning system to misinterpret traffic signs by simply of them. printing subtly altered versions Nonetheless, the IEEE report notes the generally dismissive attitude towards the threat in academia: “Whereas few works suggest that adversarial attacks on deep learning may not be a serious concern, a large body of the related literature indicates otherwise.” The current applicability or scope of adversarial attacks is irrelevant if the fundamental vulnerability survives into later production systems. At that point of commercialization and widespread diffusion, such systems are likely to present a much more attractive target, deserving of greater resources from those that would exploit some of the most sensitive and critical new AI-driven applications of the future.

Adversarial attacks: How to trick computer vision

When your team has been asked to , methodological purity can fast give way to sprint-speed pragmatism. However, this phrase — once the credo of Facebook — doesn’t mean we can take risks in the QA department. It’s really an admonition for us to open our eyes to new opportunities instead of closing them and praying that things will stay the same. A kind of rallying cry to be disruptive and try (and discard, if necessary) new things quickly. move fast and break things What’s all this got to do with testing and QA? Quite a bit. In our experience, QA is one of the slowest moving disciplines across the development landscape. This goes for both the supply side and the demand side of the market. It’s rare for new testing technology to reach the market in the first place. And equally, it’s not so common for product teams to have the capacity, time, and will to look for new tools. This is not surprising since many QA teams have a corpus of test libraries that they can’t simply forget about. All of which is by way of encouragement for you to get to know a testing framework called , which is ruffling a few feathers of , the market leader. You might have heard of it. Timewise, Cypress has just left Beta, and we thought that this would be an opportune moment to contrast the very different approaches the two frameworks take. In this post, we’ll review their main differences, most of which stem from a smaller set of design choices made by developers. Cypress Selenium A crash course in history Selenium was originally developed in 2004 by Jason Huggins and has been maintained and updated to cope with technology changes ever since then. Along the way, a super team coalesced around the technology. Cypress is developed by Brian Mann and his no-less-super team, and its first commit was just over four years ago. Both Selenium and Cypress are now . open source Architecture Architecturally, the two are polar opposites, and it’s these architectural differences that are likely to inform your preferences rather than anything else. Selenium is composed of a component called WebDriver, which can manage and control a (specific) browser, together with a set of bindings that determine which language your tests are written in. When tests run, at least three processes are involved: WebDriver A browser driver The browser itself The network overhead between these processes has been known to make test execution slow. Even if you have everything running on the same machine, that network overhead persists — locally, Selenium uses the 127.0.0.1 loopback interface. Cypress takes a different approach and comes as a single monolithic application — the only choice you need to make is whether you want to install it via npm or in standalone mode. Choosing npm gives you access to the rest of its ecosystem inside your test suite — indeed behind Cypress is a Node.js server process (which, in standalone mode, is embedded). Most people choose the npm route, but standalone mode might suit a brief visit while evaluating it. Cypress runs tests and has access to the DOM and even the application under test, a configuration which sets things up, among other things, for it to be blisteringly fast. Don’t forget though that having that back-end Node.js process means that it can also work outside of the browser for tasks that require a higher privilege. This said it does take a little extra work to communicate with back-end processes like a database or another server. inside the browser itself This trade-off means that Cypress can only support JavaScript, and will never support anything else, while Selenium currently has bindings for Java, C#, Ruby, Python, and JavaScript (node), which is currently in Alpha. And for some, this is going to be a killer feature and may well be the reason why some teams are going to have to reject Cypress out of hand. Flake Flaky tests — tests that could pass or fail when in exactly the same application state — are the bane of testers and . Cypress wraps all DOM queries with the retry-and-timeout logic that its developers claim to work better for real web apps, leading to a massive reduction in . QA engineers test flake The Cypress team also claims that despite Selenium’s impressive evolution to support today’s web, Cypress’s support for modern asynchronous single page applications makes it a more natural fit for current development workflows and application design patterns. Code, libraries, and on-boarding Both Selenium and Cypress mandate that you write your tests in a programming language. This might sound obvious but there are some testing products that use other models, for example, via GUI-based test recorders. In Cypress’s case, that language must be JavaScript. Language wars aside, Selenium offers a choice, and is, correctly, more of a library than a framework like Cypress. Selenium goes on to integrate well with many unit testing frameworks and assertion libraries, while with Cypress, the choice is limited to Mocha, Chai, and Sinon. Out of the box, it’s, therefore, easier to get going with Cypress, because everything is already bundled. Selenium takes a little more preparation and thought about which companion technologies are the best fit for your use case. It’s not a huge speed bump but it might make a difference, especially when you’re trying to assess multiple options. Debugging Cypress is aimed squarely at developers and QA engineers and has a great debugging story. Because it executes in the same run loop as the application, it has access to variables, code, and the things the browser makes available like document, window, and debugger. Once you’re familiar with its asynchronous nature, it’s a simple job to hop into the debugger. It also takes automatic snapshots of the DOM and lets you “time travel” to earlier application states if you’re hunting down a bug in your test scripts. With WebDriver/Selenium, debugging is not particularly intuitive. When you hit problems, all you get is an HTTP error response after running all the tests. At this point, your application is gone and the browser is closed — yet you somehow have to intuit the cause of that HTTP error. It can be frustrating. The bottom line Words and laundry-list comparisons don’t seem to do either of these great testing solutions justice. You have to experience them in the context of your own needs. What to some might be a showstopping lack of a feature or an architectural quirk, might to others not make any difference at all, or even be a benefit. Sure, we’re excited that the arrival of Cypress means that for the first time in many years, there’s another open-source automated testing game in town. But there’s no doubting that Selenium is a wonderful success story and will remain vital to many for the foreseeable future — it mitigates several gaping holes in Cypress’s current capabilities, such as cross-browser testing and support for multiple languages. If your team uses Selenium, we can’t tell you if you should switch to Cypress, but what we can tell you is that you should beg, borrow, or steal the to check it. Then, try it out for real perhaps on a small, well-defined new product feature, rather than your complete application. Maybe, ultimately, the smart decision will be to use technologies? time both Go on. Move fast. Break things.

Stories, News & Mentions about IFLEXION

Iflexion’s Stories on HackerNoon

Iflexion's News & Mentions