{"title":"Rule-Based Test Input Generation from Bytecode","authors":"Weifeng Xu, Tao Ding, Dianxiang Xu","doi":"10.1109/SERE.2014.24","DOIUrl":null,"url":null,"abstract":"Search-based test generators, such as those using genetic algorithms and alternative variable methods, can automatically generate test inputs. They typically rely on fitness functions to calculate fitness scores for guiding the search process. This paper presents a novel rule-based testing (RBT) approach to automated generation of test inputs from Java byte code without using fitness functions. It extracts tagged paths from the control flow graph of given byte code, analyzes and monitors the predicates in the tagged paths at runtime, and generates test inputs using predefined rules. Our case studies show that RBT has outperformed the test input generators using genetic algorithms and alternative variable methods.","PeriodicalId":248957,"journal":{"name":"2014 Eighth International Conference on Software Security and Reliability","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 Eighth International Conference on Software Security and Reliability","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SERE.2014.24","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
Search-based test generators, such as those using genetic algorithms and alternative variable methods, can automatically generate test inputs. They typically rely on fitness functions to calculate fitness scores for guiding the search process. This paper presents a novel rule-based testing (RBT) approach to automated generation of test inputs from Java byte code without using fitness functions. It extracts tagged paths from the control flow graph of given byte code, analyzes and monitors the predicates in the tagged paths at runtime, and generates test inputs using predefined rules. Our case studies show that RBT has outperformed the test input generators using genetic algorithms and alternative variable methods.