The name of a unit test helps developers to understand the purpose and scenario of the test, and test names support developers when navigating amongst sets of unit tests. When unit tests are generated automatically, however, they tend to be given non-descriptive names such as “test0”, which provide none of the benefits a descriptive name can give a test. The underlying challenge is that automatically generated tests typically do not represent real scenarios and have no clear purpose other than covering code, which makes naming them di cult. In this paper, we present an automated approach which generates descriptive names for automatically generated unit tests by summarizing API-level coverage goals. The tests are optimized to be short, descriptive of the test, have a clear relation to the covered code under test, and allow developers to uniquely distinguish tests in a test suite. An empirical evaluation with 47 participants shows that developers agree with the synthesized names, and the synthesized names are equally descriptive as manually written names. Study participants were even more accurate and faster at matching code and tests with synthesized names compared to manually derived names.

Writing good unit tests can be tedious and error prone, but even once they are written, the job is not done: Developers need to reason about unit tests throughout software development and evolution, in order to diagnose test failures, maintain the tests, and to understand code written by other developers. Unreadable tests are more difficult to maintain and lose some of their value to developers. To overcome this problem, we propose a domain-specific model of unit test readability based on human judgements, and use this model to augment automated unit test generation. The resulting approach can automatically generate test suites with both high coverage and also improved readability. In human studies users prefer our improved tests and are able to answer maintenance questions about them 14% more quickly at the same level of accuracy.

Unit testing is a common practice where developers write test cases together with regular code. Automation frameworks such as JUnit for Java have popularised this approach, allowing frequent and automatic execution of unit test suites. Despite the appraisals of unit testing in practice, software engineering researchers see potential for improvement and investigate advanced techniques such as automated unit test generation. To align such research with the needs of practitioners, we conducted a survey amongst 225 software developers, covering different programming languages and 29 countries, using a global online marketing research platform. The survey responses confirm that unit testing is an important factor in software development, and suggest that there is indeed potential and need for research on automation of unit testing. The results help us to identify areas of importance on which further research will be necessary (e.g., Maintenance of unit tests), and also provide insights into the suitability of online marketing research platforms for software engineering surveys.