Exploring the Interaction of Code Coverage and Non-Coverage Objectives in Search-Based Test Generation

Artikel i vetenskaplig tidskrift, 2025

Search-based test generation typically targets structural coverage of source code. Past research suggests that targeting coverage alone is insufficient to yield tests that achieve common testing goals (e.g., discovering situations where a class-under-test throws exceptions) or detect faults. A suggested alternative is to perform multi-objective optimization targeting both coverage and additional objectives directly related to the goals of interest. However, it is not fully clear how coverage and goal-based objectives interact during the generation process and what effects this interaction will have on the generated test suites. In this study, we assess five hypotheses about multi-objective test generation and the relationships between coverage-based and goal-based objectives, focusing on the effects on coverage, goal attainment, fault detection, test suite size, test case length and the impact of the search budget. We generate test suites using the EvoSuite framework targeting Branch Coverage, three testing goals—Exception Count, Output Coverage and Execution Time—and combinations of coverage and goal-based objectives. Ultimately, we find that targeting multiple objectives does not reduce code coverage, yields no or minor reductions in goal attainment, but—at the same time—detects more faults compared with single-target configurations. In addition, it produces larger test suites, but test case length is not increased. The benefits of multi-objective optimization are often more limited than hypothesized in past research, but improved fault detection is still sufficient to recommend multi-objective optimization over targeting coverage or testing goals alone. Our study offers insights and guidance into how coverage and goal-based objectives interact during multi-objective test generation.