{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/an-artificial-immune-system-for-adaptive-test","title":"An Artificial Immune System for Adaptive Test Selection","arxiv_id":null,"date":"2020-12-04","proceeding":"IEEE Symposium Series on Computational Intelligence 2020 12","authors":["Lukas Rosenbauer","Anthony Stein","Jörg Hähner"],"abstract":"The verification of a new product is a major challenge for companies. With the rise of test automation, companies can rely on vast numbers of test cases. There are situations where it is not feasible to run all available tests due to time constraints. Hence a test suite of critical tests must be compiled. The corresponding test suite is usually chosen according to a quality metric. We combine the newest insights about germinal centre artificial immune systems (GCAIS) to produce test suites with high requirement coverage and low execution time. Tests and requirements might change over the lifetime of a project and hence the test suite must be adapated. We exploit results about the usage of memory to reduce the runtime of the test suite's recomputation.","url_abs":"https://ieeexplore.ieee.org/document/9308528","url_pdf":"https://ieeexplore.ieee.org/document/9308528","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"an-artificial-immune-system-for-adaptive-test","repo_url":"https://github.com/LagLukas/adaptiveTestSelection","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}