{"title":"Concurrent software fine-coarse-grained automatic modelling by Coloured Petri Nets for model checking","authors":"Wenjie Zhong, Jian-tao Zhou, Tao Sun","doi":"10.1049/sfw2.12084","DOIUrl":null,"url":null,"abstract":"<p>The state space explosion restricts the error detection of concurrent software. The abstraction can provide a solution to avoid state space explosion, but it is easy to ignore important details, resulting in inaccurate detection results. This paper proposes a methodology of fine-coarse-grained automatic modelling for Java source programs. By the principle that the execution details of property-unchecked, non-interactive, and unrelated statements do not affect the model checking results, we model coarse-grained model fragments for such statements, while fine-grained model fragments for property-checked, interactive, and related statements. Our method reduces the model and state space and ensures the error detection of the source program based on model checking. Moreover, we prove the equivalence of the fine-grained model, the coarse-grained model, and the program. Finally, this paper gives an experiment to verify the effectiveness of the proposed method.</p>","PeriodicalId":50378,"journal":{"name":"IET Software","volume":"17 1","pages":"55-75"},"PeriodicalIF":1.5000,"publicationDate":"2022-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/sfw2.12084","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IET Software","FirstCategoryId":"94","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1049/sfw2.12084","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
引用次数: 0
Abstract
The state space explosion restricts the error detection of concurrent software. The abstraction can provide a solution to avoid state space explosion, but it is easy to ignore important details, resulting in inaccurate detection results. This paper proposes a methodology of fine-coarse-grained automatic modelling for Java source programs. By the principle that the execution details of property-unchecked, non-interactive, and unrelated statements do not affect the model checking results, we model coarse-grained model fragments for such statements, while fine-grained model fragments for property-checked, interactive, and related statements. Our method reduces the model and state space and ensures the error detection of the source program based on model checking. Moreover, we prove the equivalence of the fine-grained model, the coarse-grained model, and the program. Finally, this paper gives an experiment to verify the effectiveness of the proposed method.
期刊介绍:
IET Software publishes papers on all aspects of the software lifecycle, including design, development, implementation and maintenance. The focus of the journal is on the methods used to develop and maintain software, and their practical application.
Authors are especially encouraged to submit papers on the following topics, although papers on all aspects of software engineering are welcome:
Software and systems requirements engineering
Formal methods, design methods, practice and experience
Software architecture, aspect and object orientation, reuse and re-engineering
Testing, verification and validation techniques
Software dependability and measurement
Human systems engineering and human-computer interaction
Knowledge engineering; expert and knowledge-based systems, intelligent agents
Information systems engineering
Application of software engineering in industry and commerce
Software engineering technology transfer
Management of software development
Theoretical aspects of software development
Machine learning
Big data and big code
Cloud computing
Current Special Issue. Call for papers:
Knowledge Discovery for Software Development - https://digital-library.theiet.org/files/IET_SEN_CFP_KDSD.pdf
Big Data Analytics for Sustainable Software Development - https://digital-library.theiet.org/files/IET_SEN_CFP_BDASSD.pdf