{"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/a-germinal-centre-artificial-immune-system","title":"A Germinal Centre Artificial Immune System for Software Test Suite Reduction","arxiv_id":null,"date":"2020-07-18","proceeding":"ALIFE 2020 7","authors":["Lukas Rosenbauer","Anthony Stein","Jörg Hähner"],"abstract":"Testing is a crucial part in the development of a new product.\r\nIf too little testing is done, customers might discover previously undetected failures. A common approach to avoid this\r\nis to define a test suite that contains at least one test for every\r\nrequirement. As the execution of manual tests and the implementation of automated ones is timeintensive, it is a profitable\r\ngoal to reduce the amount of tests during the specification of\r\nthe test suite whilst still covering all requirements. In this\r\nwork we provide an artificial immune system to detect redundant tests. Our new approach achieves optimal results for our\r\nindustrial data sets and further we are able to reduce its runtime and memory usage drastically compared to the existing\r\ngerminal centre artificial immune system (GCAIS).","url_abs":"https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/index/index/docId/90780","url_pdf":"https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/index/index/docId/90780","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":"a-germinal-centre-artificial-immune-system","repo_url":"https://github.com/LagLukas/gcais_test_suite_reduction","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}