Today's developers embrace agile or continuous development paradigms, such as Agile and DevOps, to create and refine applications. Such development efforts rely on frequent software iterations to add capabilities, squash bugs and enhance performance. Each phase of the DevOps infinity loop involves a myriad of tools to edit, version, build, test, deploy and monitor software.
The demands of agile software development create opportunities for process bottlenecks and errors. A typical build might require linking a variety of modules and processes before compilation can take place, and each component might exist in several versions located in one or more repositories. Testing is another troublesome part of the pipeline, where developers must define and execute a bewildering range of tests to evaluate and validate each iteration. More challenges arise in deployment, as the validated build must move into production with minimal disruption to the existing environment.
Automated development tools streamline frequent and redundant tasks, such as building, integrating and testing software, and also maintain code quality standards and security requirements. The tools that underpin this example of IT automation, however, are generally limited in scope and fall into particular pipeline categories. For example, build and integration tools include Jenkins, CircleCI, Bamboo and Apache Maven, while test tools include Selenium, TestComplete, Ranorex, and Tosca Testsuite. Most tools rely on some combination of scripting and object-based workflows to establish automated behaviors.
Future automated development tools will span more of the development pipeline. This will require a high level of integration and interoperability with a vast assortment of tools already in the software development marketplace. AI and machine learning will also play a greater role in future software development automation to evaluate, for example, a code base for style and content.