Serena Gray's Blog

  Constant integration means constructing your software every time a developer pushes code. This impacts your testing and requires careful planning and using test automation. CI has a large effect on testing, as it means you are not testing stable applications. On the flip side, the changes you are testing are much smaller. This usually means you've got to adopt another approach to analysing than has been traditionally the case. In this blog, we'll explore CI and examine the challenges it creates for testers. Continuous Integration The foundation and inspiration for CI CI isn't brand new, but it indicated a change from the traditional method of building software. To do CI nicely requires careful coordination and buy from the developers and testers. Once on a time, developers would work individually and in groups on developing their part of their program. Every few weeks they would upload all their code into the server, together with the code from the rest of the teams. The

 DevOps, an IT methodology and culture now about 10 years old, still feels fresh -- and challenging -- to many people in IT. That is because DevOps methodology tools, and cultural principles keep morphing and enhancing. "Its entire purpose is to evolve and change over time." How can you keep up with the changes and remain conscious of the latest lessons learned from DevOps professionals? Our DevOps manual for IT leaders brings you the latest and best information out of our continuing coverage, which means it's possible to have a deep dip in 1 spot. Let's delve into specialist advice and evaluation from DevOps experts and best CIOs. Why is DevOps popular in business IT? DevOps continues to win fans in enterprise IT to get a few important explanations. This manner of working prizes rate, experimentation, and cooperation, all happening on cross-functional teams. All these factors suit the business goals of the instant: Transform the company -- so that it can quickly chan

So what exactly is DevOps? Let's take a small hypothetical example to illustrate. Let us say there's a small startup that assembles AI-enabled cleaning robots. There are 3 programmers (let's be lazy and simply call them Team D) who compose and execute the code to produce the robots and 2 operational people (Team O of course) who maintain the robot infrastructure in the real-world environment and supply aid for the robot consumers. Team D has only spent 8 months producing the latest robot. It can recognize individuals, take orders from Alexa devices, and clean like a boss. Team D has spent time producing this robot into their controlled dev environment and everything seems to be working smoothly. They couldn't be prouder. They hand over their production to Team O that immediately takes it out to the real world. That's when the problems start. It turns out that the perfect cleaning robot isn't so perfect after all. It does not recognize everybody, it can follow Al

Let's start by saying that integration testing is looking for information on how two systems work together. That's a little vague, right? A system could be nearly anything. APIs send and get data from databases. That could be entire software products working together like TweetDeck and Twitter. An integration test can be performed anywhere there is a  coupling  between two software systems. When that coupling is broken, software becomes a black hole. Customers can submit forms and send data all they want, but it doesn't do any good. FedEx doesn't know that Amazon has packages ready to be shipped from the warehouse to customers that have already paid. Insurance companies can't make decisions about which parts of a healthcare bill they should cover for their customers.  It is easy for a tester to get a sort of blindness during a release cycle. New features come in one at a time, and sometimes one piece at a time. Testing happens at a granular level. First the  API get

Smoke testing is explicitly helping many teams in ensuring that the critical and major functionalities of the application are working before it is released for end-users. This method is a functional testing type and also known as the Build verification process. By including smoke testing into the software testing lifecycle (STLC), developers and testers experience several benefits such as saving time and effort, improvement in the effectiveness, etc. Thus, it is essential for the teams to have a clear understanding of smoke testing. For any software project, the main objective is to deliver a quality and high-performing application at a faster speed with cost savings. Thus, to achieve this, there is a huge need for the teams to perform software testing, make sure that the application is defect-free and all major functionalities are working fine before its release. One of such testing methodology that effectively helps is Smoke testing. Yes, smoke testing is one type of functional test

Web performance is a broad topic, and you will find no lack of performance testing tips and tutorials all around the net. Before beginning tuning your site or application, you have to first figure out which metrics matter to your own users and establish a few achievable benchmarks. What is performance testing?  In the context of web development, performance testing entails using software tools to simulate the way the application runs under particular conditions. After the word"performance" is heard, most people instantly think of the rate. Fast load times and response times are absolutely necessary these days, but you have to consider the larger picture, which requires more than simply clicking through all your links to be certain they work. Just because everything works flawlessly during production testing does not mean that will be the situation as soon as your site is flooded with traffic. What are the advantages of performance testing?  Testing the operation of your site

The disagreement over whether to write a unit test or an end-to-end evaluation for an element of a software system is something I have encountered a number of times. It mostly appears as a philosophical conversation along the lines when we can only write one test for this feature, should we write a unit test or an end-to-end test? Basically, time and resources are limited, so what type of test would be most effective? In this article, I'll provide my view on this question. I must be aware that my experience has been in building software infrastructure for industrial applications -- streaming data system for near-real-time data. For someone who has worked in another domain, where calculating and analysing the whole software process is simpler, or at which the functional environment is more forgiving of mistake, I could understand the way their experience might be different. I've worked on hosted solutions in addition to infrastructure that's installed on-premises and operate

Learning to build code, if through self-study or a computer science degree, isn't the same as learning how to construct applications, especially in a changing company setting. Your research may have instructed you what code has to be composed to construct a better piece of software, however, they probably did not teach you the way a team of engineers should think about writing that code. How does the work get divvied up? What does the development cycle look like? How can quality management work? Over the past 60 decades, many methodologies have tried to define exactly how teams can maximise their software development, however, the one which reigns supreme--at least over the past twenty years--is the agile methodology. Emphasising speed, adaptability, and user-centric layout, the agile technique is the backbone of contemporary software development. Most of the popular project management tools you've likely used (like Trello and Jira) are based entirely on their features. If you&