{"title":"Counterexample classification","authors":"Cole Vick, Eunsuk Kang, Stavros Tripakis","doi":"10.1007/s10270-023-01118-0","DOIUrl":null,"url":null,"abstract":"<p>In model checking, when a model fails to satisfy the desired specification, a typical model checker provides a <i>counterexample</i> that illustrates how the violation occurs. In general, there exist many diverse counterexamples that exhibit distinct violating behaviors, which the user may wish to examine before deciding how to repair the model. Unfortunately, (1) the number of counterexamples may be too large to enumerate one by one, and (2) many of these counterexamples are redundant, in that they describe the same type of violating behavior. In this paper, we propose a technique called <i>counterexample classification</i>. The goal of classification is to cover the space of all counterexamples into a finite set of <i>counterexample classes</i>, each of which describes a distinct type of violating behavior for the given specification. These classes are then presented as a summary of possible violating behaviors in the system, freeing the user from manually having to inspect or analyze numerous counterexamples to extract the same information. We have implemented a prototype of our technique on top of an existing formal modeling and verification tool, the Alloy Analyzer, and evaluated the effectiveness of the technique on case studies involving the well-known Needham–Schroeder and TCP protocols with promising results.</p>","PeriodicalId":49507,"journal":{"name":"Software and Systems Modeling","volume":"34 1","pages":""},"PeriodicalIF":2.0000,"publicationDate":"2023-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Software and Systems Modeling","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1007/s10270-023-01118-0","RegionNum":3,"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
In model checking, when a model fails to satisfy the desired specification, a typical model checker provides a counterexample that illustrates how the violation occurs. In general, there exist many diverse counterexamples that exhibit distinct violating behaviors, which the user may wish to examine before deciding how to repair the model. Unfortunately, (1) the number of counterexamples may be too large to enumerate one by one, and (2) many of these counterexamples are redundant, in that they describe the same type of violating behavior. In this paper, we propose a technique called counterexample classification. The goal of classification is to cover the space of all counterexamples into a finite set of counterexample classes, each of which describes a distinct type of violating behavior for the given specification. These classes are then presented as a summary of possible violating behaviors in the system, freeing the user from manually having to inspect or analyze numerous counterexamples to extract the same information. We have implemented a prototype of our technique on top of an existing formal modeling and verification tool, the Alloy Analyzer, and evaluated the effectiveness of the technique on case studies involving the well-known Needham–Schroeder and TCP protocols with promising results.
期刊介绍:
We invite authors to submit papers that discuss and analyze research challenges and experiences pertaining to software and system modeling languages, techniques, tools, practices and other facets. The following are some of the topic areas that are of special interest, but the journal publishes on a wide range of software and systems modeling concerns:
Domain-specific models and modeling standards;
Model-based testing techniques;
Model-based simulation techniques;
Formal syntax and semantics of modeling languages such as the UML;
Rigorous model-based analysis;
Model composition, refinement and transformation;
Software Language Engineering;
Modeling Languages in Science and Engineering;
Language Adaptation and Composition;
Metamodeling techniques;
Measuring quality of models and languages;
Ontological approaches to model engineering;
Generating test and code artifacts from models;
Model synthesis;
Methodology;
Model development tool environments;
Modeling Cyberphysical Systems;
Data intensive modeling;
Derivation of explicit models from data;
Case studies and experience reports with significant modeling lessons learned;
Comparative analyses of modeling languages and techniques;
Scientific assessment of modeling practices