2019/03/27 by Mohammad Jafar Mashhadi, Mashhadi, Mohammad Jafar, Hadi Hemmati +1
Computer Science · #FOS: Computer and information sciences #Software Engineering (cs.SE) #Software Engineering Research #Software System Performance and Reliability #Software Testing and Debugging Techniques
paper · pdf · doi:10.48550/arxiv.1903.11242
openalex publication_date 2019/03/27 · openalex created_date 2022/07/29 · openalex updated_date 2026/07/28
Dynamic model inference techniques have been the center of many research\nprojects recently. There are now multiple open source implementations of\nstate-of-the-art algorithms, which provide basic abstraction and merging\ncapabilities. Most of these tools and algorithms have been developed with one\nparticular application in mind, which is program comprehension. The outputs\nmodels can abstract away the details of the program and represent the software\nbehavior in a concise and easy to understand form. However, one application\ncontext that is less studied is using such inferred models for debugging, where\nthe behavior to abstract is a faulty behavior (e.g., a set of execution traces\nincluding a failed test case). We tried to apply some of the existing model\ninference techniques (implemented in a promising tool called MINT) in a\nreal-world industrial context to support program comprehension for debugging.\nOur initial experiments have shown many limitations both in terms of\nimplementation as well as the algorithms. The paper will discuss the root cause\nof the failures and proposes ideas for future improvement.\n