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Category: Continuous Testing

Continuous testing is the process of executing automated tests as part of the software delivery pipeline to obtain immediate feedback on the business risks associated with a software release candidate.

  • The Impact of DevOps and Continuous Testing in 2018

    The Impact of DevOps and Continuous Testing in 2018

    At its core, DevOps is meant to touch an entire organization; however it’s heavily weighted in the software development life cycle (SDLC). That’s why DevOps is going mainstream in 2018. Companies are making the business benefits of DevOps a top priority—it’s all about delivering value to the customer faster through maximum automation of the release cycle/processes. And that begins with organizations realizing that to mature their DevOps processes, they need continuous testing as part of their continuous integration practice.

    Cross-platform Engagement and IoT Will Mean More Devices—and More Apps

    With organizations shifting processes and innovation to a mix of digital technologies—a concept known as digital transformation—consumers are engaging with different apps across various platforms 24 hours a day, seven days a week. Add in the rise of internet of things (IoT) devices, which allow for seamless transitions across smartphones, TVs, tablets and other devices. Now is the time for optimum user experience (UX).

    In 2018, industries such as financial services, health care, retail and automotive will fully embrace IoT. We may also see new types of applications replacing current ones, as consumers and developers embrace the constantly evolving innovative capabilities coming in 2018. However, until the C-suite implements the tools needed to keep up with the growing demand for cross-platform upkeep and testing, other industries will experience slow adoption.

    A critical step in delivering flawless UX is testing, and lots of it. Never has there been more to test, measure and develop than in this digital revolution we are seeing today.

    Frequent New Releases Will Require Even Faster Updates

    As the number of platforms consumers engage with rapidly grows, so does the pressure for developers to ensure apps are running as they should at all times. Same goes for the pace of cloud adoption: Cloud test labs will need more sophisticated capabilities, meaning more platforms and blind spots which require continuous optimization to ensure market readiness. This need for faster turnarounds on update releases and bug fixes will multiply in 2018.

    To maintain and grow customers and profitability, CIOs must recognize the importance of empowering developers with the tools and time to implement continuous testing across the SDLC. Tools, such as those powered by automation and the cloud, increase efficiencies and free up time developers previously spent on manual quality-checking, allowing them to ensure the apps they are producing are keeping up with consumer expectations. If users feel their app is not delivering on the experience they want, they will delete it and move on to the next competitor, which has a direct negative impact on the company’s bottom line.

    Outdated Technologies Will Make for Even Slower Updates

    There is a suite of new tools being introduced to the market for all stages of the SDLC in the hopes of keeping up with the heightened speed of testing. As many DevOps environments struggle to adapt their pipelines to these new tools, many are powered by emerging technologies including machine learning and automation. In 2018, developers should ditch outdated infrastructure and processes in favor of more modern architectures, including implementing microservices.

    Modernizing pipelines will allow developers to design in next-gen engagement methods such as artificial intelligence (AI), augmented reality (AR) and virtual reality (VR) without compromising velocity.

    AI Will Experience Its Shining Moment (for Some)

    In the coming year, AI will start to move from a theoretical concept to a commonly applied technology, especially within the DevOps space. However, developers first must understand what they want AI to help them accomplish—and how—within the SDLC and across the DevOps pipeline. One logical place to start is figuring out how they can best leverage it to analyze test automation strategies.

    The value of a well-oiled, or not-so-well-oiled, DevOps process can make or break an organization. As the new year begins, be sure to include the IT leadership in these conversations to ensure developers are getting what they need, when they need it, to keep business moving as usual. IoT, AI and the cloud are just a few things to keep in mind as the industry moves to implement the latest tools in 2018.

    About the Author / Eran Kinsbruner

    Eran Kinsbruner is the lead technical evangelist at Perfecto and the author of the “Digital Quality Handbook.” He is a software engineering professional with nearly 20 years of experience at companies such as Matrix, Qulicke & Soffa, Sun Microsystems, General Electric, Texas Instruments and NeuStar. He holds various industry certifications such as ISTQB, CMMI, and others. Eran is a recognized mobile testing influencer and thought leader. He is also a patent-holding inventor (test exclusion automated mechanism for mobile J2ME testing), public speaker, researcher and blogger. Follow him on Twitter, connect with him on LinkedIn and check out his professional mobile testing blog.

  • Micro Focus Unfurls Functional Testing Service

    Micro Focus Unfurls Functional Testing Service

    The merging of software assets from Micro Focus and Hewlett-Packard Enterprise (HPE) that occurred earlier this year included StormRunner, a series of load- and performance-testing tools. Micro Focus recently extended that portfolio with the introduction of Micro Focus StormRunner Functional, a suite of functional testing tools delivered as service that can be employed to test applications running on any browser, operating system or mobile device.

    Shane Evans, director of product management for application delivery management for Micro Focus, says StormRunner Functional spans a variety of automated tests addressing unified functional testing (UFT), UFT Pro and Selenium browser testing tools that include elements developed by both HPE and Micro Focus. The Micro Focus StormRunner Functional Testing service also includes pre-built integration with Google Analytics, Micro Focus Octane, GIT and Jenkins to streamline the testing process.

    Interest in automated testing has increased substantially in the last few years, says Evans, because developers are under more pressure than ever to roll out new applications and associated updates faster. Unfortunately, most developers don’t have the time required to test applications themselves, or there is simply not enough money in the budget to hire quality assurance teams to test every element of an application. Micro Focus StromRunnner Functional provides an alternative approach using a set of testing tools that have been widely employed across the enterprise for decades, says Evans.

    Evans notes Micro Focus is pursuing a comprehensive approach to application delivery management spanning everything from testing tools to application lifecycle management. Micro Focus is making the contention that most DevOps teams are a lot more interested in getting access to the results of a test than managing the actual testing technologies themselves, says Evans. In addition, advanced analytics and machine learning algorithms, which now are standard elements of testing process, require access to massive amounts of data to be effective. That data is a lot easier to aggregate in the cloud using SaaS applications than in an on-premises environment. In fact, Evans says, those requirements are among the factors driving a wave of recent acquisition across the application testing sector.

    Arguably, the biggest testing challenge organizations now face is moving away from processes based on IT Information Library (ITIL) guidelines to a more DevOps-centric process, under which continuous testing is more embedded within the application development process, Evans says. Functional testing is only one element of the testing process, but it has become more critical as end users become less forgiving of substandard digital experiences inside and out of enterprise IT environments. Regardless of who inside the organization is responsible for testing applications, the expectation now is that every application experience inside the enterprise will be on par with a consumer application experience.

    — Mike Vizard

  • Tricentis Signs Alliance Partner Agreement with Capgemini to Transform Testing for Agile and DevOps

    MOUNTAIN VIEW, CA–(Marketwired – Nov 6, 2017) – Tricentis, the leader in Continuous Testing, has entered into a global alliance and reseller agreement with Capgemini, a global leader in consulting and technology services, that focuses on helping enterprises transform testing to meet the demands of Agile and DevOps. This alliance is an extension of the long-standing relationship between Tricentis and Sogeti, a subsidiary of the Capgemini Group.

     

    The ability to automate an on-demand assessment of a release candidate’s level of business risk has become critical for protecting user experience. However, companies have experienced limited success with test automation initiatives, to date. The overall test automation rate is 18 percent, and, on average, only 8 percent for enterprises. Moreover, software testers are now expected to test increasingly complex applications, delivered at the dramatically accelerated pace of Agile and DevOps. A new approach to testing is needed.

     

    Tricentis is committed to helping clients modernize their testing processes to support current and future digital transformation initiatives. This agreement will provide Tricentis clients with best-in-class Continuous Testing tools, methodologies, and training so they can accelerate testing for modern applications and delivery processes.

     

    Hans van Waayenburg, Member of the Group Executive Committee and Leader of Testing Services, Capgemini said, “We are delighted to expand our work with Tricentis. Capgemini’s domain expertise and global reach coupled with Tricentis’ Continuous Testing platform forms a powerful combination to help customers to adopt modern testing methodologies, which are now essential to optimize critical processes for business development and growth.”

     

    “We’ve worked closely with Capgemini and Sogeti to transform testing at a number of clients transitioning to Agile and then DevOps,” explained Tricentis CEO Sandeep Johri. “Throughout these engagements, it became increasingly clear that Capgemini’s expertise helps enterprises adopt Tricentis Tosca in a way that delivers measurable business results in terms of accelerating innovation, reducing business risks, and optimizing testing costs. Leveraging the worldwide reach of Capgemini is a great opportunity to make Continuous Testing a reality at business across the globe.”

     

    About Tricentis
    Tricentis provides a Continuous Testing platform that accelerates testing to keep pace with Agile and DevOps. With the industry’s most innovative functional testing technologies, Tricentis breaks through the barriers experienced with conventional software testing tools — achieving test automation rates of over 90%. Our integrated software testing solution, Tricentis Tosca, consists of a unique Model-based Test Automation and Test Case Design approach, encompassing risk-based testing, test data management and provisioning, service virtualization, and more. Prominent analysts have recognized us as a Leader in both Software Test Automation and in Functional Automation Tools. We are established as a reliable enterprise partner, helping to deliver significant performance improvements to testing projects.

     

    Tricentis’ 400+ customers include global names from the Top 500 brands such as HBO, Toyota, Allianz, BMW, Starbucks, Deutsche Bank, Lexmark, Orange, A&E, Vantiv, Vodafone, Telstra and UBS. For regular news and information about Tricentis and the automated testing market, like and follow the company on: www.tricentis.com.

     

    ©Tricentis and Tosca are registered trademarks of Tricentis. Other trade names used in this document are properties of their respective owners.

  • Survey Finds DevOps Teams Under Increasing Pressure

    Survey Finds DevOps Teams Under Increasing Pressure

    The fact that a much larger percentage of companies now recognize they are software companies that happen to specialize in a specific vertical industry is now putting a lot of pressure on developers, according to a new survey of 750 development team leaders in the United States and the UK conducted by Testplant, a provider of tools that automate application testing.

    The survey finds that 42 percent of the respondents claim they are expected to design, develop and test apps in an unrealistic amount of time. More than one-third (36 percent) also report they are not given enough time to ensure apps are properly tested before deployment, while 56 percent note that use of outdated techniques and tools is holding them back from meeting the demands of the digital world.

    Because of this combination of factors, nearly half the respondents (49 percent) say they are deploying applications before they go through an ideal testing amount of testing, and 45 percent admit to putting applications into production that will perform below initial requirements.

    Dr. John Bates, CEO of Testplant, says it’s a matter of time before IT organizations will have to rely more on tools that automate much of the testing process, as pressure on DevOps teams to roll out new applications and update existing ones is only going to increase. The survey respondents (60 percent) say most of the pressure to accelerate software development is being driven from within the organization itself. But nearly half (49 percent) say pressure comes from competitors. As more organizations realize their competitive differentiation comes from the software they develop, there’s now a lot more focus on accelerating application development, says Bates.

    The survey also notes that the applications being built are more complex than ever. Over the next 12 to 18 months, half the respondents (50 percent) say their company will develop more apps using components for an internet of things (IoT) environment. Well over half (58 percent) also say their company will develop more apps with artificial intelligence (AI) components, and 62 percent say their company will increase the amount of applications that incorporate machine and deep learning algorithms.

    When it comes to deploying applications, automation is ranked as the most critical challenge by 67 percent of the respondents, and 70 percent claim they are now more focused on automated testing today than they were in the past.

    In total, 75 percent of the respondents say that with access to better tools, the applications deployed by their team would have a greater impact on the business. A full 81 percent also say that with more time, applications deployed by their team would have a greater impact on the business.

    Unfortunately, more time for application development is luxury most business don’t have today. Not only is a wave of digital business innovation is making it easier for startups to not only enter markets, but companies that traditionally have focused in one market segment are now extending their reach to adjacent areas. The difference between surviving and being made obsolete now comes down the level of customer experience an organization can deliver by the applications it makes available to customers.

    Unfortunately, when it comes to those applications, customers tend to be unforgiving. Once bad application experience and many of them will move on to try an application developed by a rival. Bates notes that too many organizations still seem to think they can test their applications on end users on the assumption they can fix any issue that comes up rapidly. In reality, rather than participate in what amounts to an extended beta testing process, most end users will simply look for a better alternative application experience.

    In short, the difference between success and complete failure now hinges on the level of quality application testing that can be implemented in the shortest amount of time possible.

    — Mike Vizard

  • Testing’s Role in Delivering Digital Transformation

    Testing’s Role in Delivering Digital Transformation

    “We have a quality philosophy now…but it took the rise of the middle child to make it happen.”

    • Ann Lewis, ExxonMobil

    Ann Lewis’ metaphor of testers being the “middle child” between software development and IT operations was present throughout Accelerate 2017, Tricentis’ annual user conference. Nearly every head in the room nodded as Lewis described how testers, like middle children, tend to get less attention than their professional or familial siblings, but she insisted that there’s never been a better opportunity for testers to receive the respect they deserve. Digital transformation, no matter how you define it, requires new commitments to quality, and it’s up to testers to claim be the change agents in the transformations that CIOs are tasked with delivering.

    Tricentis CEO Sandeep Johri and other CxOs who spoke at Accelerate echoed this sentiment. Johri pointed out that speed continues to be a primary focus of maintaining or gaining competitive advantage, and manual testing processes that prevent agility or DevOps success at the enterprise level must be automated going forward.

    What was also made clear is that scaling investments in automation is not the single key to success. The pressure CIOs are under today, especially around digital transformation, requires new investments in a number of different areas, many of which are only just being realized. While CIOs may understand the necessity of quality, it’s up to testers to get the buy-in required for the continuous testing required to deliver it at scale.

    Testers with an oft-ignored middle child mindset may find the concept of being recognized as a “champion” by their CIO or CEO unlikely. But, Todd Pierce’s impassioned session on “What CxOs really think about testing” was designed to inspire testers to change the way testing was viewed too often in the past.

    As a current Rock Health and Dignity Health board member, and former Bill & Melinda Gates Foundation chief digital officer, Pierce shared his peers’ all-too-common beliefs that testing takes too long, costs too much and constrains developer productivity. And, while it may hurt to admit, with manual testing that should be automated and insufficient testing time that results in bugs making it to production, it’s not surprising that CIOs would feel this way.

    Pierce explained that testers who adopt innovative, scriptless “high-precision testing,” are able to shorten their test cycle, reduce defects that make it to production and eliminate costly rework for themselves and developers alike. When high-precision testing is performed continuously throughout the software development life cycle (SDLC), those beliefs that testing takes too long, costs too much and impedes innovation lose all validity. “Everyone in this room should be the drivers of agility in the enterprise,” remarked Pierce.

    Emmet Keeffe at Insight Venture Partners hosted a CIO roundtable later in the day where four CIOs detailed their personal experiences with taking enterprises through digital transformations. Each CIO admitted that in the past they had underestimated the the time being spent on testing, and one somewhat bravely stated that he’d always found testing somewhat “boring.” One might expect a room of testers to storm the stage with charges of heresy, but, given that many testers have suspected that management felt this way for years, I got the feeling that many were simply impressed that someone who felt that way had admitted it.

    But the panel, Pierce, Lewis and countless other speakers at Accelerate also made sure that the attendees of their sessions understood one thing: As more organizations undergo digital transformation—and no matter what stage of digital transformation they’re in—testing has never been in a better position to drive positive changes that will have monumental impacts on the business.

    Whether CIOs have been tasked with delivering greater agility, DevOps shifts, increased security, enhanced user experience, reliability and performance or legacy app modernization, testing may not be the first organization that CIOs turn to for help. But, as Keeffe explained, testing leaders who truly understand the incredible opportunity they have to make those CIOs heroes will make themselves heroes in the process.

    About the Author / Noel Wurst

    Noel Wurst leads influencer relations for Tricentis, and collects stories around cultural shifts and evolving technology’s impact on the software testing industry. By attending global conferences, interviewing passionate software professionals, and working closely with product, engineering and customer success teams, Noel looks for stories that matter and innovative ways to share them with audiences that lead to business growth. You can follow Noel on Twitter and LinkedIn.

  • The Future of Continuous Testing: Fail Faster

    The Future of Continuous Testing: Fail Faster

    In the early days of Agile and Lean development practices, a very noticeable gap appeared between dev teams and ops and QA. Development was accelerating at a lightning-fast pace, but testing processes could not keep up, slowing down the entire life cycle and preventing organizations from achieving continuous delivery. Traditional testing methods, which rely heavily on manual processes and frequently updated GUI tests, proved too cumbersome and inadequate for our new lifecycle timelines.

    The era of testing as an afterthought is dying out, and continuous testing has emerged as the new standard. The idea behind continuous testing is pretty straightforward: Implement a systematic approach towards improvement that incorporates not only automation, but also all of the other tools and processes that will help reduce risk before software progresses to release and production. Organizations embracing this are rethinking testing as a continuous process that starts from the sandbox, rather than a precursor to release.

    Continuous Testing: Achieving ‘Fail Faster’

    At xMatters, we strive to a testing strategy that supports our goal of committing to production multiple times per day—one that we’ve been diligently moving closer to, having progressed from releases every quarter to every month to every week to now, twice per week. Our approach is to conduct unit tests at the team level, code quality, sonar and static analysis, and then deploy to production at limited percentages that we bump up in stages. Our overarching mantra is “fail fast,” because the faster and sooner you fail, the faster and sooner you can fix what’s broken, and the less resources and time you will spend troubleshooting and resolving issues. This, of course, translates to real cost savings.

    Correlating failure to actual events is the biggest hindrance to the continuous testing dream, as pinpointing root causes is an incredibly time-consuming process. This is where automation will take us to the next level, if implemented in a smart way. The future of continuous testing will be adaptive so as to determine the causes of failures faster. We need to automate as much as possible the process of predicting where code quality issues are and identifying the precise data correlations that will enable us to fix issues rapidly.

    Part of this adaptive testing approach will include automating intelligent regression testing. We don’t need to run a black box test in every instance, for example, which can take hours every time. We’ll save incredible amounts of time, money and developer resources if we design tests that can detect new changes and only test those. Smarter regression testing will result in precious time saved that ultimately impacts—and can even make or break—the speed of innovation.

    Another critical consideration to smarter testing is making sure to account for a comprehensive understanding of risk. We need to incorporate real business considerations into our understanding of risk and bake those into our tests as well. We should hold our software to not only standards of code quality and integration success, but also to meet real business expectations for areas such as security, compliance and reliability. Testing from the bottom up must be done in tandem with top-down analysis to account for the full spectrum of potential risks that have the potential to impact the bottom line. Machine learning systems can also be extended to learn new business applications as new functionalities are added and assist in creating test cases that serve to enhance the quality of the application.

    Developing these intelligent automation tools remains our biggest barrier to achieving the continuous testing dream, and while many organizations are gunning for it, most are still mired by manual processes. A global study conducted earlier this year by CA Technologies, for instance, demonstrated that while 75 percent of organizations identify continuous testing as important, just 20 percent report a high quality of test automation coverage.

    It’s worth noting that not every aspect of testing can be successfully automated. The vast majority of functional tests will almost certainly not be manual processes—but what about user experience testing? We have yet to conceive of an approach to this that can truly be automated. Because nothing beats a real human’s assessment of experiential quality, this will be one of the areas of testing that will likely remain manual. Thus, while our goal is to automate 100 percent, realistically this won’t be the case.

    The end goal here is not only to achieve the dream of continuous delivery, but also to eliminate distractions as much as possible. The more repeatable processes you can automate, the fewer distractions your team will encounter, and the more they can focus on creativity, strategy and building new features and capabilities instead of fixing old ones. This is what will ultimately determine your ability to innovate, as you’ll no longer have to sacrifice either time, scope or quality.

    About the Author / Deepa Guna

    Deepa Guna is Senior QA Architect for xMatters. She has been working in technology since 2003. Connect with her on LinkedIn.

  • Continuous Testing: Crushing the Testing Bottleneck

    Continuous Testing: Crushing the Testing Bottleneck

    The practice of continuous delivery has been with us for many years, but it has started to see real adoption in the last couple of years. Continuous delivery is about automating and simplifying the process of delivering new features to the market at any given time, accelerating delivery and helping bring Dev and Ops together to make them jointly accountable for the release process.

    As continuous delivery is helping to break down barriers, culture and bottlenecks in the delivery pipeline, a new practice has evolved to help teams solve this most daunting challenge of the delivery pipeline: Quality.

    The practice is called continuous testing, which can be defined as:

    • Testing your change in an efficient way (so your tests are completing faster),
    • In an optimized way (so that you find issues as early as possible in the cycle),
    • Based on risk and priority (so you test what is important to your users and the business).

    Some may think of this as equivalent to test automation, but that premise would be wrong.

    Automated testing tools can execute tests repeatedly, provide reports on testing outcomes and show comparisons with previous test runs. This is a critical foundation for a continuous testing practice, but just a starting point.

    In a continuous testing practice, testing is not done just in the “testing” phase and not only by test teams. Testing is performed at the level of the build (for example, Unit Test and Security Test) and does not stop after the change has been deployed into the production, where testing can ensure great customer experiences. Here are some other key aspects of continuous testing.

    Continuous Testing Automates Test Environments

    Let me clarify what I mean by environment. Basically, you want to replicate the real-world situation much as possible for testing. A test environment contains the test cases to be run, the right test data and services available, and the right application version deployed in the right environment. The juxtaposition of these elements of an environment must come together automatically to ensure a continuous testing practice.

    Continuous Testing Amps Up Throughput

    A key premise of continuous testing is that you are continually maximizing efficiency. This is a must to keep up with the velocity and frequency of today’s modern software factory.

    You are doing testing earlier in the testing cycle (shift left) where problems are easier to fix and less expensive. You are doing more testing in parallel. You are automating the promotion and feedback during testing stages. And you are ideally able to prioritize the testing order based on the risk profile of the code so that you are testing higher risk areas first. All of this enables you to find issues quickly and roll forward if possible or roll back seamlessly.

    Continuous Testing Applies Intelligence

    Finally, continuous testing means you have the knowledge at your fingertips about the risk profile of a release so you can make more informed decisions. You should be able to see what was changed in the code and the implications. For example, was there a small change in the UI or a complex backend change that affected integrations and could break the APIs for the interface?

    You also need a detailed view of the quality level of the release, including which tests have failed, which tests have not been executed, whether you have tested the new or the risky areas. All this intelligence will help you to understand the quality profile of a release and make faster decisions about whether additional tests are needed or if a release is ready to go to production.

    Steps Toward Continuous Testing

    There is no perfectly prescribed way to put a continuous testing practice in place for your organization. For example, you may find that your biggest bottleneck of the moment is managing test data, so you should tackle that first. But here are five steps critical in your adoption of continuous testing:

    Step 1: Implement best-of-breed test automation tools—Functional, GUI, Performance, Security, etc.

    Step 2: Automate test environments with the right test data and virtual services to ensure real-world, always available testing.

    Step 3: Automate test requirements (you’ll find manual methods can no longer keep up).

    Step 4: Automate the automation—Connect your testing toolchain and stages. Automate promotion from one stage to the next. Automate feedback loops end to end.

    Step 5: Get smarter—Automatically align the right tests to the right app version. Automate testing sequence by risk profile of the code. Build release health profiles.

    About the Author / Uri Scheiner

    Uri Scheiner is a senior director of product management in the Continuous Delivery Business Unit of CA Technologies. He was previously a key architect and responsible for the product road map and vision at a leading release automation company Nolio, which was acquired by CA in 2012. Uri started his career as a software engineer at Mercury Interactive (acquired by HP in 2006) where he was responsible for developing several products for the DevOps and APM markets.

  • Codeless Automation: Shattering the Testing Bottleneck

    Codeless Automation: Shattering the Testing Bottleneck

    In his article, “Moving from ‘Tester’ to ‘Quality Enabler’,” Scott Edwards clearly lays out the predicament in which QA testing is currently at: with one foot in the quicksand of manual testing, while the other tries to jump over the hurdle of automation. Ever tried hurdle racing with one foot? You probably won’t reach the finish line.

    Edwards mentions the infamous label that is attached to testing—bottleneck—and cites the “DevOps Review 2017” research paper of Computing.co.uk that found two-third of DevOps practitioners report QA testing as the bottleneck of the development process.

    Why is that? Why is testing bottlenecking development, and how can it be untangled?

    What Creates the Development Bottleneck?

    The testing bottleneck is created primarily due to two reasons:

    1. The reliance on manual testing, and
    2. “All the code that is getting thrown” QA teams’ way.

    Manual testing is extremely time-consuming, sometimes to the point that it’s close to impossible for test teams to keep up with the fast pace of DevOps. Manual testing is also error-prone, simply because the testing is performed by humans.

    The code issue is related to automation. Due to the pressure imposed upon test teams, automation is being hailed as the great savior. While the word “automation” has the flair of hands-free simplicity, the reality of automated testing is quite the opposite.

    Automation relies on code and testers aren’t coders. So instead of simplifying and speeding up testers’ work, the opposite is being achieved. Testers are thrown out of their comfort zone, being bogged down by tasks that aren’t in their “job description.” The frustration of all involved is easy to understand. The development team feels that testing is slowing them down, while the testing team feels they are required to jump through hoops.

    Add to that the complex setup and heavy maintenance required of automation, and you start to doubt whether it is indeed the right path for testing.

    Well, it is. With the ever-faster pace of DevOps, the pressure to shorten release cycles and the cutthroat competition software and web application companies are facing, test automation is the right path, despite all the challenges.

    What must be done to clear that path is remove coding from automation.

    Codeless Test Automation to the Rescue

    Codeless is a growing force in mass technology. It has liberated the web. Codeless platforms such as Wix and Shopify allowed millions of businesses to create an online presence quickly and effortlessly and led to the incredible expansion of the web. On the enterprise side, codeless platforms are making strides with the likes of Salesforce, FileMaker and Nintex, which offer drag-and-drop solutions to speed up and optimize efficiency of large-scale administrative tasks.

    The idea behind codeless is the modern-day “power to the people.” Just a decade ago, a small family business from Minnesota would have never been able to afford and maintain an online presence, but now their 22-year-old can set up an online shop, promote it on Facebook and in no time start selling their goods to a consumer across the ocean.

    Applying the same logic to testing instead of coding from scratch test after test—which is time-consuming and costly, and requires acquired skill—codeless test automation allows for quick and simple creation of tests, no coding skills required. It allows QA testers to focus on what they do best: testing.

    Automation shouldn’t be a hurdle that testers need to jump above; it should be a tool that pushes them forward. As things stand now, automation in testing is at a counterproductive standstill. Don’t get me wrong: Automation means well, but at the moment it’s like a misguided teenager that brings havoc even when he aims for harmony.

    How Does Codeless Test Automation Actually Work?

    Codeless test automation functions very similarly to enterprise codeless platforms. Both take complex tasks traditionally achieved by coding and simplify them through automated code generation.

    With test automation a tester creates a flow by visually binding elements that represent “clicks” in the software or web application. The tester simply goes through motions of the scenario he wishes to test, and the code for the test is generated under the hood.

    We can get more technical than this, but there’s no need. That’s exactly the idea with codeless, isn’t it? Testers could focus their efforts on testing functionality and evaluating the user experience rather than struggling with test creation.

    This ties back to Edwards’ main point: Testers get so entangled with test creation that the whole point of testing—quality assurance—gets lost.

    Side Note: The proposed job title change suggested by Edwards—Tester to Quality Enabler—might sound merely cosmetic, but it can deliver real value. As illustrated in this collection of QA testers’ venting from a reddit forum, QA testers often harness feelings of underappreciation and of being looked down on by their developing colleagues. Recognizing testers’ valuable contribution to the overall quality of the product will surely elevate their feelings of self-worth and enable them a stronger sense of pride in their position.

    Using Codeless for Deeper Integration of Testing Into DevOps

    Codeless automation is best utilized in sanity and regression testing, the two most basic and frequently applied tests. Sanity testing ensures that all incorrect inputs a user could enter are accounted for. Regression testing is like inventory counting, in a way: you just need to go over your stockpiles and see that everything is in order.

    Thinking on inventory: Let’s say I have a huge warehouse full of thousands of items. Checking inventory by hand is a very time-consuming and error-prone process. How many boxes on a piece of paper (representing real boxes on shelves) can you tick before you’ll make a mistake? Now think of Amazon’s warehouse. Inventory counting is done using automation with the press of a button. It is instantaneous and error-free. It’s an action that’s been done so many times before, there’s no need to plan it—or to code it—all over again. Simply run the same command—“inventory”—and you’re done.

    If you’re using codeless automation, all you need for regression testing is to click a button and the scripts run. You are done and able to divert your attention to sanity testing, making sure the new iteration is solid.

    For the next iteration, you simply pile the sanity testing of the previous round on top of the regression scripts and, again, you’re done.

    Continuous testing is getting a whole new meaning with codeless automation as part of the equation. If regression testing is done with the click of a button, and sanity taken care of simultaneously, the reporting back to development is swift and focused and the bottleneck is shattered.

    Codeless enables deeper integration of testing into the development process simply by arming testers with automation tools that simplify tasks, not complicate them.

    About the Author / Assaf Dudai

    Assaf Dudai is the content marketing manager at TestCraft, a pure SaaS continuous test automation solution for QA professionals. Assaf is mostly looking into the future of testing, how automation, codeless and machine learning can and will help testing evolve. You can connect with Assaf on LinkedIn.

  • Move the Needle in DevOps with Continuous Testing

    Move the Needle in DevOps with Continuous Testing

    Shift-left testing, risk based testing, early testing and technical debt reduction are all predicted to be some of the most sought-after trends in product development life cycle. All of these can be achieved with continuous testing through DevOps, as it emphasizes quicker transitioning of quality products to production environment at a reduced business risk.

    Software Engineer in Test (SEiT) or Software Developer in Test (SDiT) was long-spoken earlier and now implemented as part of DevOps culture. As the software side of the organization moves to continuous testing practices, so, too must the product side of the organization. External market forces including competition, innovation quotient, faster time to market, scalability and lean process initiatives definitely play a role in driving the continuous testing trend.

    From a technical standpoint, test environment creation, full test coverage, regression testing and integration testing of multiple endpoints are key parameters to ensure a faultless production environment when a new feature is added.

    Adopting Testing Tools for DevOps Implementation

    Continuous testing implementation not only includes adoption of right tools and test automation, but also a cultural change to incorporate testing at each stage of the agile development life cycle. It will involve changes right from test planning, test scenarios creation, automation feasibility analysis to test execution.

    Teams need to be restructured in an agile setup to align testers closer to developers and operations teams, and have common goals for product/software delivery. This involves changing the culture and organization structure, which generally takes a longer gestation time. Test management tools such as JIRA and TestNG can help expedite this structuring, as both parties would be aware of the product features that need to be delivered and can view the progress at all times. There also are various open-source tools, including Selenium, Appium, Python robot framework/pytest and JMeter, that aptly meet the needs of agile testing.

    Regression testing generally takes up the bulk of the time, as new features need to be tested every time they are added to avoid critical failures. Hence, automating regression tests have become an imperative as part of continuous testing. JUnit, which is a unit testing framework, promotes test-driven development and early code quality improvement. Bamboo can run tests in parallel batches and support hundreds of build agents providing an early feedback to developers. Automation scripts for test data cleanup, load and execution saves the testing effort of the operations team. Selenium test automation framework for web applications is one of the most famous tools for continuous testing, as it works with a host of programming languages including Java, C#, Groovy, Perl, PHP, Python and Ruby. Appium is another tool used frequently for cross platform mobile application testing.

    Ensuring an Effective Product Release

    Testing UI components and functionality of a product through API-based test automation is another important phase in continuous testing. API test scenario creation also generally needs involvement from the ops team. Considering virtualization of devices, along with applications or services, will accelerate test setup environments. Device virtualization using Raspberry pi helps in testing end–to-end use cases in IoT scenarios. Network virtualization for performance testing ultimately helps improve uptime and reduce outages.

    The orientation of continuous testing with continuous integration and continuous delivery pipeline within an enterprise will determine the long-term success and standing of the final product in the market, from a quality perspective.

    About the Author / Urvashi Babaria

    Urvashi Babaria is a Product manager at eInfochips working in new age areas like IoT, DevOps and CloudOps. She is a techno commercial marketer with nine years of experience in product and project management, business analysis and transformation. She has keen interest in areas of data science including visualization, analytics and modeling. Connect with her on LinkedIn.

     

  • Tricentis Acquires Flood IO, Scaling Open Source On-Demand Load Testing for DevOps

    Tricentis extends leadership in software test automation by adding load testing to its Continuous Testing platform

    Mountain View, CA – July 27, 2017 – Tricentis, leader in Continuous Testing and software test automation, announced today that they have acquired Flood IO: the industry’s most flexible and scalable on-demand load testing solution. Flood’s breakthrough technology frees load testing from resource-intensive performance labs and “shifts it left” with a simplified and highly-scalable approach. Together, Tricentis and Flood are transforming load testing for today’s lean, fast-paced delivery pipelines.

    Transforming Load Testing for DevOps and Agile

    Flood lets DevOps teams test how their applications scale with massive load generated from around the world.  Test plans can be defined in open source tools such as JMeter, Gatling, and Selenium, or specified directly in the Flood interface.  Over 5,000 companies globally already use Flood, including DirecTV, Bloomberg, Heroku, Red Hat, NEC, ABC, Paperless Post, AT&T, Riot Games, and Telus.

    Tricentis is recognized for transforming traditional testing to meet the needs of Agile and DevOps processes. This acquisition broadens that mission to embrace load and performance testing—enabling teams to “shift left” load testing and integrate Continuous Load Testing into their delivery pipelines.

    “Times have changed. Old performance testing approaches are too late, too heavy, and too slow for today’s lean, fast-paced delivery pipelines,” explained Sandeep Johri, CEO of Tricentis. “Yet, releasing updates without insight into their performance impact is incredibly dangerous in today’s world—with competitors just a click away. Flood’s technology offers DevOps teams unparalleled flexibility for load testing early and continuously. This acquisition enables us to take our mission of ‘transforming testing for DevOps’ to the next level.”

    Andrew Midgley, Software Testing Lead at REA, described how Flood helped REA break free from legacy performance testing approaches: “We previously had very specialized tools for load and performance testing that were quite expensive. They were very richly featured—but completely disconnected from our everyday development tools. We ended up with a couple of engineers who were quite good at load and performance testing with our enterprise tools, but the majority of engineers found the barriers too great. With Flood, we have moved to an approach which is far more inclusive and utilizes many of the tools our engineers are working with on a daily basis.”

    The Flood team has joined Tricentis and will continue driving the Flood technology forward. “At Flood, we set out to build insanely easy-to-use performance testing tools that help teams scale their apps to millions of users,” remarked Tim Koopmans, Flood co-founder. “Joining forces with Tricentis will help us advance our vision for achieving Continuous Load Testing in a DevOps environment. We’re excited about the opportunity to accelerate the path to Continuous Testing—making it faster and easier to ensure that applications meet users’ rising expectations.”

    To bring load testing into the fold of Tricentis’ Continuous Testing platform, a fully-integrated offering uses Tricentis’ scriptless test cases for “shift left” load testing. This enables teams to:

    • Start load testing with any Tricentis Tosca cross-browser test case
    • Create smoke tests on the fly with the Tricentis Tosca recorder
    • Integrate load testing into CI for immediate feedback
    • Identify performance problems early—when they’re easiest to fix

    Details on the Tricentis-Flood integration, as well as upcoming enterprise load testing offerings, will be unveiled at the Accelerate 2017 conference in Vienna.

    The Need for Early and Continuous Load Testing

    “Agile delivery cycles rely on continuous quality, including user experience and performance testing across dynamic release cycles (and we are also seeing increased use of open source),” explained Melinda Ballou, Research Director for IDC’s Agile Application Life-Cycle Management (ALM), Quality and Portfolio Strategies program. “Organizations are re-architecting the quality process for accelerated delivery to help enable business adaptability and brand innovation that ultimately impact competitive responsiveness and the bottom line. As part of that process, I am seeing adoption of lightweight, continuous load testing emerging across development teams, from early-stage startups to large enterprises.”

    Additionally, The Forrester Wave™: Modern Application Functional Test Automation Tools, Q4 2016* confirms the importance of early load testing as well as the convergence of functional testing and load testing: “Driven by mobile, the internet of things, and the need for speed, dev teams want to use their functional test cases not only for user acceptance testing (UAT) and automated regression testing, but also for testing load performance — and they want do more of it. Performance testing is shifting left, meaning that teams test load performance early and locally so they can fix their designs sooner rather than later.”

    Additional Details

     For additional details on the acquisition and upcoming offerings, see the Continuous Load Testing page and Tricentis Acquires Flood IO, Scaling Load Testing for DevOps blog.

    About Tricentis
    Tricentis provides a Continuous Testing platform that accelerates testing to keep pace with Agile and DevOps. With the industry’s most innovative functional testing technologies, Tricentis breaks through the barriers experienced with conventional software testing tools — achieving test automation rates of over 90%. Our integrated software testing solution, Tricentis Tosca, consists of a unique Model-based Test Automation and Test Case Design approach, encompassing risk-based testing, test data management and provisioning, service virtualization, and more. We are established as a reliable enterprise partner, helping to deliver significant performance improvements to testing projects.

    Tricentis’ 400+ customers include global names from the Top 500 brands such as HBO, Toyota, Allianz, BMW, Starbucks, Deutsche Bank, Lexmark, Orange, A&E, Vantiv, Vodafone, Telstra and UBS. For regular news and information about Tricentis and the automated testing market, like and follow the company on:

    ©Tricentis and Tosca are registered trademarks of Tricentis. Other trade names used in this document are properties of their respective owners.

    — Parker Yates