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dc.contributor.authorYeh, Chao-Chunen_US
dc.contributor.authorLu, Han-Linen_US
dc.contributor.authorYeh, Jia-Junen_US
dc.contributor.authorHuang, Shih-Kunen_US
dc.date.accessioned2018-08-21T05:56:24Z-
dc.date.available2018-08-21T05:56:24Z-
dc.date.issued2017-01-01en_US
dc.identifier.issn2376-6816en_US
dc.identifier.urihttp://hdl.handle.net/11536/146163-
dc.description.abstractSymbolic Execution is a widely used technique for program testing and analysis. When a program executes a trace symbolically, it simulates all possible paths. This results in an exponential growth of the number of states within the problem, which is commonly referred to as "path explosion." We therefore propose novel strategies that only require limited resources to give priority to more valuable paths. In this paper, we utilize a method based on the Monte Carlo tree search (MCTS) strategy to resolve the problem. We then compare the proposed MCTS-based strategy with other methods such as depth-first search (DFS) and breadth-first search (BFS). We also perform different scales of experiments based on time and space resource constraints. For smaller test cases, we found that MCTS performs on average 1.4 times better than BFS and DFS in terms of the block discovery rate. In addition, for larger test cases, MCTS performs on average 2.8 times better than DFS and BFS in terms of the block discovery rate.en_US
dc.language.isoen_USen_US
dc.subjectMonte Carlo tree searchen_US
dc.subjectupper-confidence bounds for treesen_US
dc.subjectsymbolic executionen_US
dc.subjectpath explorationen_US
dc.subjectsoftware testingen_US
dc.titlePath Exploration Based on Monte Carlo Tree Search for Symbolic Executionen_US
dc.typeProceedings Paperen_US
dc.identifier.journal2017 CONFERENCE ON TECHNOLOGIES AND APPLICATIONS OF ARTIFICIAL INTELLIGENCE (TAAI)en_US
dc.citation.spage33en_US
dc.citation.epage37en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.department資訊技術服務中心zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.contributor.departmentInformation Technology Services Centeren_US
dc.identifier.wosnumberWOS:000434087700009en_US
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