Software testing methods are essential in building software. It helps developers deal with different types of bugs. As we all know, these bugs may range from a missing semicolon to a critical business requirement. Thus, software testing becomes an essential part of a test driven development environment. We are in the era of process automation. Today, businesses are dependent on one or more software products. Therefore, software quality becomes crucial.

This post is about Kafka and the process I have been through recently writing a performance test for an application that subscribes to messages from this technology. The test I ended up with was in the end very straightforward but there were several hurdles that took a while to resolve. I hope that reading this post will hopefully help you avoid them.

If you are working in an agile environment, you may have come across the term ‘code review’. It is a strategic operation where you break the source code into snippets in order to audit the code before it is moved to the testing phase.

It’s been some time since our latest major release, in fact OctoPerf v12 is probably our biggest/longest coming release to date. There’s of course been a couple of minor versions this summer and we’ll also cover them but first let’s focus on the new killer features: the scheduler, alerting through slack/mail and a better UI for the menus. The scheduler is the first item left on our original roadmap (back when OctoPerf was still called jellly.io).

Have you abandoned a web service, because it took too long to load? I bet you have, everyone does that every now and then with slow applications. There are a lot of services to check load times, but is it the only thing to check about website’s performance worldwide? Certainly not! It is just one thing to check, not the only one. You may have performance tested the service locally and validated that everything works just fine.

This traditional financial institution is a high-performance, full-service bank with more than 5,000 employees and the biggest in this Central European country. They operate internationally in order to meet their clients’ cross-border requirements.

Automated UI testing is a daily struggle for efficiency and reliability. A single misconfigured line of code can cost teams in hours of lost feedback time and test error triaging—potentially costing companies hundreds of thousands of dollars. In this case study we will see how interactions with only two web elements led to a 34% degradation in the test execution time.

Every company is a digital company. Whether you are a traditional e-commerce company who has been selling goods online for years, a healthcare company who recently needed to accelerate online visits for telehealth, or a company whose business model has drastically shifted due to Covid, the need for digital transformation is here.

In the first blog in this series, I talked about test speed, and why it shouldn’t be your first priority. Rather, you should focus on getting accurate test results back consistently. This week, I’ll discuss the power of parallelization in testing.

Waldo is a no-code testing platform, that allows teams to test apps without the hassle of scripting. With the Waldo Verified Step, you can automate testing and ship your app to the users faster, directly from Bitrise.

SaaS (software as a service) which is one of the most popular forms of cloud computing has completely revolutionized the world of cloud computing as it is being adopted by a majority of the IT organizations to modernize their IT structure. With companies shifting their tools and platforms from on-premise to cloud-based solutions, there is no doubt the future belongs to the SaaS test automation platforms.

In traditional software development projects with clear departments and defined roles, people tend to see their responsibilities as limited to the boundaries of their position. Siloed teams are not able to see the systemic view of the whole application delivery since: Siloed departments lose the vast opportunity to help and collaborate with each other and prevent problems and bugs from happening in the first place.

I used the K6 load testing framework to benchmark the Compute Engine f1-micro and Caddy web server hosting this site. With CloudFlare caching turned off, the server was able to serve an onslaught 800 virtual users continuously reloading the page (while maintaining a median request duration of <400ms), but started dropping requests when increasing the load further. This is fine.

Although automation testing is becoming more popular, there remain certain difficulties for automation teams, including selecting which test cases to automate. According to the World Quality Report in 2019, 24% of teams encounter obstacles prohibiting them from deciding on the right test scenario. This article will detail how to choose test cases for automation and maximize your testing journey.

This spring, Sauce Labs announced the Sauce Testrunner Toolkit (beta) to expand developer-first capabilities and support for native JavaScript frameworks. The Testrunner Toolkit makes setting up, writing, and running web tests easier and faster for developers during early pipeline testing. First it supported Puppeteer, followed by Cypress, TestCafe, and Playwright to provide the flexibility to test the way you want, along with Sauce Labs insights, at scale.

Automation testing has become a recognized domain in the world of software testing. As the name implies, automation testing involves the use of automated tools to carry out test cases with minimal human intervention, then comparing various outcomes and generating test reports. Automated testing is a crucial part of every Agile team to keep up with the demands for fast but high-quality software projects.

For example, let’s say that an app that we’re working on supports multiple themes, and that we’re keeping track of the user’s currently selected theme (and other user-configurable settings) through a SettingsController — which in turn uses Foundation’s UserDefaults API to persist those settings, like this.

The world is witnessing the rise of Agile methodologies in software development. They require a new approach to software testing, which must well align with the nature of Agile, a fast-moving philosophy. Test automation was not born to serve Agile teams, however, it makes Agile testing- a crucial part of the Agile concept- achievable. This article shows all essentials for the implementation of automation testing for Agile teams.

In our last post, we looked at the multiple layers of testing and where UI tests fit into your overall architecture. In case you didn’t read it, here’s a TLDR: Testing architecture can be grouped into 3 “layers”: Layer 1 tests tiny chunks of code in complete isolation. Layer 2 tests larger pieces of code in partial isolation.

The landscape of software testing is changing. In the hyper-competitive world of technology, speed and quality are often seen as opposing forces. We are told to “move fast and break things” if we are to succeed in getting our products into the hands of users before our competition beats us to the punch. This often times means sacrificing quality and confidence in the name of getting new features out the door.

Is your team able to pivot with changing demands, accelerate new features, and provide the highest product quality? Being agile allows you to move fast, make changes, and keep quality at the center of your work. Xray empowers your team to strive towards continuous improvement, optimize testing efforts and exceed quality goals with features and workflows that support agile methodologies.

Deep in the implementation of every automated UI test lives the potential to turn something simple into something slow and unreliable—simply by adding extra Selenium commands. The data clearly show that longer tests are less likely to pass. In this case study, I will show you how to optimize a test and make it 560% faster. We will do this by tackling inefficient use of Selenium commands.

Apache JMeter is a Java open source tool. If you want to run load or performance tests using Apache JMeter, you can use their Graphic User Interface (GUI) and you don’t need to know any programming language, follow the JMeter documentation and you are ready to go to design your API testing scenarios.

According to a survey conducted on software test automation, 51% of organisations prefer to retrain existing staff in test automation skills. While there are still 49% that would like to hire them specially for test automation related tasks. Other findings from the same survey confirmed that organisations want to move to more of test automation and a minimum of manual testing. To quote the findings, “Only 5% of survey respondents said they currently carry out 0:100 manual: automation testing.

As the lead of the Selenium project, I wanted to kick off a new blog series leading up to the release of Selenium 4. During this series, I’ll talk all about how the Selenium project works, who is involved, how you—yes, you!—can get involved, and we’ll get a sneak peek at what’s new in Selenium 4. I've been speaking about this off and on for a while, but now the 4.0 release is looming I wanted to start sharing in more depth.

Testers, in their day-to-day lives, have to do many types of tasks. And to enable them to do those tasks there are many tools in the market too. These tools usually specialize in helping the testers perform a certain task. Sometimes these tools can be used to completely automate the tasks while at other times these tools can make the tasks easier. In this article we will try to broadly categorize these tools. The categories have been created according to when these tools are used.

Socrates preached, “To know thyself is the beginning of wisdom.” This ancient Greek anecdote applies to your modern Apache Kafka project: developers, go forth and load test your real-time application to understand the capacity and limitations of your project before deployment. Failure to do so will cost you time and money (e.g. Robinhood’s outage on a historic trading day). Load testing your real-time applications has three main objectives.

With exponential growth in remote working, teams are struggling with collaboration and maintaining visibility. Sound familiar? In this blog we’ll explore how to keep track of your testing activity and team’s progress in Jira, and how TM4J – Test Management for Jira can help identify common problem areas so proper measures can be taken.

QA professionals, testers, and developers are constantly learning new tools, tech stacks, and development practices. When they’re told they have to learn accessibility, it can often feel like an unwelcome and overwhelming disruption, slowing them down and forcing them to test and rewrite what they thought was perfectly good code. The good news is accessibility tools are more tester-friendly than ever.

Today we’re launching new names for some of our most popular API products. This is part of refreshing our outlook on the API space and our subsequent API lifecycle tools. We loved our old names, and know many felt the same. And yet, here we are to explain why we decided the progression was necessary.