{"type":"ScholarlyArticle","title":"A Machine Learning Approach for Statistical Software Testing","authors":[{"name":"Nicolas Baskiotis","slug":"nicolas-baskiotis","given":"Nicolas","family":"Baskiotis","affiliation":""},{"name":"Michèle Sebag","slug":"michele-sebag","given":"Michèle","family":"Sebag","affiliation":""},{"name":"Marie-Claude Gaudel","slug":"marie-claude-gaudel","given":"Marie-Claude","family":"Gaudel","affiliation":""},{"name":"Sandrine-Dominique Gouraud","slug":"sandrine-dominique-gouraud","given":"Sandrine-Dominique","family":"Gouraud","affiliation":""}],"abstract":"Some Statistical Software Testing approaches rely on sampling the feasible paths in the control flow graph of the program; the difficulty comes from the tiny ratio of feasible paths. This paper presents an adaptive sampling mechanism called EXIST for Exploration/eXploitation Inference for Software Testing, able to retrieve distinct feasible paths with high probability. EXIST proceeds by alternatively exploiting and updating a distribution on the set of program paths. An original representation of paths, accommodating long-range dependencies and data sparsity and based on extended Parikh maps, is proposed. Experimental validation on real-world and artificial problems demonstrates dramatic improvements compared to the state of the art.","doi":null,"url":"https://ijcai.org/proceedings/2007/366","pdf":"https://ijcai.org/proceedings/2007/0366.pdf","markdown":"https://ijcai.org/proceedings/2007/366.md","bibtex":"https://ijcai.org/proceedings/2007/bibtex/366","volume":{"slug":"2007","title":"Proceedings of the Twentieth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2007","url":"https://ijcai.org/proceedings/2007/","year":2007,"location":"Hyderabad, India","dates":"","editors":"Ramon López de Mántaras","isbn":"","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":null,"track":"","number":366,"pages":{"first":2274,"last":2278},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}