Software testing should be a standard part of the development process, and while obviously all programs undergo some degree of assessment, the process isn’t where it needs to be. Rather, even though we understand the benefits of continuous testing, many programs only undergo slow, fragmented testing protocols that compromise both speed and quality in the end product. To reach the software outcomes we desire, then, it’s vital that software developers move towards continuous testing – and automation may be the transitional tool we need.
Continuous Testing Adoption
Continuous testing, the process of providing ongoing security and function checks on software in development, should be fully integrated into today’s DevOps ecosystem. One core reason that developers continue to reject the practice, though, is that companies, specifically DevOps teams, consider the process to be too slow. According to research by Capgemini and Sogeti – and reported by Continuous Testing – agile teams spend 30% of their time creating a testing environment – and this is just one of the major barriers to implementation.
With developers launching new code daily, or even hourly, many also find the continuous testing process too onerous when it comes to communications and program handoffs, as well as with building testing into their pipeline. Automating the continuous testing process, however, could push developers to adopt continuous testing with greater consistency.
The Automation Ecosystem
Despite what many people think, continuous testing isn’t a form of automation. On its own, continuous testing requires intensive developer engagement, including designing the test environment, interpreting results, revamping the code, and testing again. It’s continuous because it demands continuous attention by the programmer, not because an automated environment is running the show behind the scenes.
That being said, one reason that continuous testing is increasingly gaining traction, despite challenges, is that simplified automation processes are increasingly available. In fact, there are numerous DevOps tools designed to specifically test new code. This eliminates the pipeline problem cited above and even cuts back on communication issues. As long as the code is identified as new, it will be run through the testing protocol.
Another way automation is changing the continuous testing ecosystem is by enabling developers to modularize testing. Modularized testing breaks up the different parts of the program, making it more precise while also desensitizing the tests. The problem is, without automation, modularized testing takes up too much time and too many developer resources. When automated, though, modularized testing can actually save time by helping developers to identify code issues more quickly and accurately than through a general test process.
Finally, it’s impossible to talk about automation without engaging with how artificial intelligence (AI) makes it all possible. Using AI-based testing, security experts who lack a coding background can actually run code-free tests, while even those who can code save time because they don’t need to maintain detailed scripts. Automation often hinges on an organization’s scripting capabilities, but the machine learning process means that the scripting is based on existing procedures and ecosystems.
Automation is the future of continuous testing and deployment, and it’s the most promising tool in improving software security. If developers can accept that continuous testing fits into their aggressive launch timelines, automation will help them deliver better products with up to the minute updates and patches. Continuous testing is ready for the age of agile if developers will make room.