Automatically Generating Single-Responsibility Unit Tests

Automatic test generation aims to save developers time and effort by producing test suites with reasonably high coverage and fault detection. However, the focus of searchbased generation tools in maximizing coverage leaves other properties, such as test quality, coincidental. The evidence shows that developers remain skeptical of using generated tests as they face understandability challenges. Generated tests do not follow a defined structure while evolving, which can result in tests that contain method calls to improve coverage but lack a clear relation to the generated assertions. In my doctoral research, I aim to investigate the effects of providing a preprocess structure to the generated tests, based on the singleresponsibility principle to favor the identification of the focal method under test. To achieve this, we propose to implement different test representations for evolution and evaluate their impact on coverage, fault detection, and understandability. We hypothesize that improving the structure of generated tests will report positive effects on the tests' understandability without significantly affecting the effectiveness. We aim to conduct a quantitative analysis of this proposed approach as well as a developer evaluation of the understandability of these tests.