Abstract
Search-based techniques have been successfully used to automate test case generation. Such approaches allocate a fixed search budget to generate test cases aiming at maximizing code coverage. The search budget plays a crucial role; due to the hugeness of the search space, the higher the assigned budget, the higher the expected coverage. Code components have different structural properties that may affect the ability of search-based techniques to achieve a high coverage level. Thus, allocating a fixed search budget for all the components is not recommended and a component-specific search budget should be preferred. However, deciding the budget to assign to a given component is not a trivial task. In this article, we introduce Budget Optimization for Testing (BOT), an approach to adaptively allocate the search budget to the classes under test. BOT requires information about the branch coverage that will be achieved on each class with a given search budget. Therefore, we also introduce BRANCHOS, an approach that predicts coverage in a budget-aware way. The results of our experiments show that (i) BRANCHOS can approximate the branch coverage in time with a low error, and (ii) BOT can significantly increase the coverage achieved by a test generation tool and the effectiveness of generated tests.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
More From: ACM Transactions on Software Engineering and Methodology
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.