Name
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 mechanismcalled 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. |
Year | Venue | Keywords |
|---|---|---|
2007 | IJCAI | artificial problem,statistical software testing,feasible path,statistical software testing approach,distinct feasible path,data sparsity,software testing,exist proceed,control flow graph,mechanismcalled exist,program path,machine learning |
Field | DocType | Citations |
Data mining,Statistical software,Control flow graph,Inference,Computer science,Adaptive sampling,White-box testing,Sampling (statistics),Artificial intelligence,Machine learning,Software testing | Conference | 10 |
PageRank | References | Authors |
0.63 | 15 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nicolas Baskiotis | 1 | 119 | 11.73 |
| Michèle Sebag | 2 | 1547 | 138.94 |
| Marie-Claude Gaudel | 3 | 698 | 71.49 |
| Sandrine-Dominique Gouraud | 4 | 60 | 4.21 |