This article covers the basics of automated software testing and provides a basic introduction to the vast, technical topic: what it is, why it’s necessary for the Agile IT industry, and how to make sense of the technology behind it. Along the way, you’ll find input from professionals in the test community that will help you determine what you need to explore further.
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When we talk about continuous testing, and with it continuous delivery and DevOps, the term automation gets thrown around a lot. In a basic sense, we all understand what automation means — the use of some technology to complete a task. But when we talk about automation in terms of continuous testing, there are some nuances that we need to take into account.
The promise of automation, touted by optimistic economists and sanguine futurists, has been that yielding work to machines would eliminate the drudgery of mindless, repetitive labor, freeing humans to fill our days with leisure, creative pursuits, or more dynamic work. In 1930, John Maynard Keynes famously speculated that “automatic machinery and the methods of mass production” would help deliver a 15-hour workweek—and even those hours would only be necessary to help men feel they had something to do.
There are lot of governance challenges related to instantiating a single bot in environment let alone thousands. One Deloitte client spent several meetings trying to determine whether their bot was male or female, a valid gender question but one that must take into account human resources, ethics and other areas of compliance for the business, Kuder says.
BPA is often confused with other terms such as industrial automation, robotic process automation, smart factories, infrastructure management, and enterprise risk management. Industrial automation (IA) uses control systems such as computers to automatically run industrial processes. Primarily found in manufacturing, it replaces the human element and improves the production rate through consistently managed processes. Whereas BPA automates processes and workflows, IA strictly automates the physical human labor in processes and workflows.
Experts say that BPM has five to six stages: planning and strategic alignment, process analysis, process design, process implementation, process monitoring, and process refinement, although the planning and strategic alignment stage is under debate. Regardless, all experts agree that the last step should include continuous improvement activities, making the overall process a cycle that never really ends.
Automation is already contributing significantly to unemployment, particularly in nations where the government does not proactively seek to diminish its impact. In the United States, 47% of all current jobs have the potential to be fully automated by 2033, according to the research of experts Carl Benedikt Frey and Michael Osborne. Furthermore, wages and educational attainment appear to be strongly negatively correlated with an occupation’s risk of being automated. Prospects are particularly bleak for occupations that do not presently require a university degree, such as truck driving. Even in high-tech corridors like Silicon Valley, concern is spreading about a future in which a sizable percentage of adults have little chance of sustaining gainful employment. As the example of Sweden suggests, however, the transition to a more automated future need not inspire panic, if there is sufficient political will to promote the retraining of workers whose positions are being rendered obsolete.
“I’ve worked with many clients to improve their business process efficiency. The main way I achieve efficiency is through the integration of financial and operational applications. There are many ways to use cloud applications to get rid of redundancies, reduce data lag/availability, and — by eradicating human intervention — improve accuracy in the collection of data. You will often observe that a human entering or moving data through a process is susceptible to inaccuracies and the delays of office life. By automating these processes, you reduce or eliminate the inaccuracies and can significantly cut down on the time it takes to get actionable data.
Summary: Simplifies inviting beta users, distributing builds and collecting feedback for beta testing of mobile apps. Applause Mobile Beta Management is mobile-only. It allows users to share feedback and submit bugs directly from within the app they are testing and provides managers with bug and feedback reports as well as participant session information and automatic crash reporting.
API testing is also being widely used by software testers due to the difficulty of creating and maintaining GUI-based automation testing. It involves directly testing APIs as part of integration testing, to determine if they meet expectations for functionality, reliability, performance, and security. Since APIs lack a GUI, API testing is performed at the message layer. API testing is considered critical when an API serves as the primary interface to application logic since GUI tests can be difficult to maintain with the short release cycles and frequent changes commonly used with agile software development and DevOps.
Summary: Offers a community of users to test and provide feedback on websites, mobile applications and desktop applications. With BetaEasy, users solve problems collectively by communicating with one another and voting on each other’s suggestions. It also allows companies to communicate with users and react to their suggestions and provides detailed reports of all communications and progress.
Robot Framework is an open-source automation framework that implements the keyword-driven approach for acceptance testing and acceptance test-driven development (ATDD). Robot Framework provides frameworks for different test automation needs. But its test capability can be further extended by implementing additional test libraries using Python and Java. Selenium WebDriver is a popular external library used in Robot Framework.
There's plenty of failure in that combination. First of all, the feedback loop from development to test is delayed. It is likely that the code doesn't have the hooks and affordances you need to test it. Element IDs might not be predictable, or might be tied to the database, for example. With one recent customer, we couldn't delete orders, and the system added a new order as a row at the bottom. Once we had 20 test runs, the new orders appeared on page two! That created a layer of back and forth where the code didn't do what it needed to do on the first pass. John Seddon, the British occupational psychologist, calls this "failure demand," which creates extra work (demand) on a system that only exists because the system failed the first time around.
Selenium is possibly the most popular open-source test automation framework for Web applications. Being originated in the 2000s and evolved over a decade, Selenium has been an automation framework of choice for Web automation testers, especially for those who possess advanced programming and scripting skills. Selenium has become a core framework for other open-source test automation tools such as Katalon Studio, Watir, Protractor, and Robot Framework.
There is a common reference to a “shift left” approach in modern development practices. This term refers to the advent of testing software earlier in the development cycle than traditional methods. Developers are now responsible for, and held accountable to, testing their code as they create it (sometimes before it's developed, but more on that later). Also, test professionals capable of a higher level of technical expertise, including the ability to write code (automation code), are in demand and job titles often go by a variety of names.
RPA alone covers mostly low-value tasks, but when combined with ML and AI, it can automate higher cognitive tasks. This includes work that requires perception and judgment, sometimes intelligently automating 15-20 steps of a process. Gartner says that by 2020 the RPA market will top $1 billion, going from use in less than 10 percent of businesses to about 40 percent, and reducing the human need in service-share centers by 65 percent.
One could also argue that RPA lays the groundwork for machine learning and more intelligent applications. It both gathers useful data and is being combined with AI capabilities. One of us (O’Dell) recently interviewed Eric Siegel, a predictive analytics expert and author of the book, Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die. Siegel pointed out an often overlooked benefit of starting by digitizing processes with simple RPA: the digital bread crumbs it now leaves behind. “This data wasn’t amassed in order to do machine learning. It’s just a side effect of doing business as usual. The transactional residue accumulates and, lo and behold, it turns out this stuff is really valuable because you can learn from it. You can derive these patterns to help improve the very transactional processes that have been accumulating the data in the first place.”
“I use Zapier to automate my outreach and collect user stories to feature in blog posts. After compiling a list of users to reach out to in a Google Sheet, I set up an automation between my Google Sheets and my Gmail. Then, every time I update a row in my Google Sheet, the system sends a personalized email to the user using a template I created. The email has a link to a Typeform survey with a couple of questions. After users submit the survey, their answers are automatically routed back to the Google Sheet. With this automation, I can spend more time crafting a piece of content and less time manually compiling the information I collect.”
Automation frameworks provide guidelines to achieve beneficial results from test automation tools and automated testing activity. They establish a universal standard for testers to achieve the specific goals of the automated tests. The framework should be easy to maintain and easy to change. Consider dedicating the role of framework design and development to a dedicated, qualified tester. A poorly designed — or hard to maintain — framework causes problems even if you are using the right automation software tools. Poor planning and the failure to create or select the appropriate framework to guide test automation activity limits the benefits of automating tests.
Test automation is a fundamental part of Agile. Various core practices of Agile, such as Continuous Integration (CI), Continuous Delivery, Test-Driven Development (TDD), and Behavior-Driven Development (BDD) rely on the efficiency and reliability of test automation. For teams using Agile methods, test automation impacts more than just the software being developed: successful test automation practices also highlight the culture change and importance of teamwork associated with Agile.
Business process automation (BPA), also known as business automation or digital transformation, is the technology-enabled automation of complex business processes. It can streamline a business for simplicity, achieve digital transformation, increase service quality, improve service delivery or contain costs. It consists of integrating applications, restructuring labor resources and using software applications throughout the organization. Robotic process automation is an emerging field within BPA and uses artificial intelligence.