{"title":"软件测试用例生成工具和技术:回顾","authors":"A. Verma, Ankur Choudhary, S. Tiwari","doi":"10.33889/ijmems.2023.8.2.018","DOIUrl":null,"url":null,"abstract":"Software Industry is evolving at a very fast pace since last two decades. Many software developments, testing and test case generation approaches have evolved in last two decades to deliver quality products and services. Testing plays a vital role to ensure the quality and reliability of software products. In this paper authors attempted to conduct a systematic study of testing tools and techniques. Six most popular e-resources called IEEE, Springer, Association for Computing Machinery (ACM), Elsevier, Wiley and Google Scholar to download 738 manuscripts out of which 125 were selected to conduct the study. Out of 125 manuscripts selected, a good number approx. 79% are from reputed journals and around 21% are from good conference of repute. Testing tools discussed in this paper have broadly been divided into five different categories: open source, academic and research, commercial, academic and open source, and commercial & open source. The paper also discusses several benchmarked datasets viz. Evosuite 10, SF100 Corpus, Defects4J repository, Neo4j, JSON, Mocha JS, and Node JS to name a few. Aim of this paper is to make the researchers aware of the various test case generation tools and techniques introduced in the last 11 years with their salient features.","PeriodicalId":44185,"journal":{"name":"International Journal of Mathematical Engineering and Management Sciences","volume":null,"pages":null},"PeriodicalIF":1.3000,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Software Test Case Generation Tools and Techniques: A Review\",\"authors\":\"A. Verma, Ankur Choudhary, S. Tiwari\",\"doi\":\"10.33889/ijmems.2023.8.2.018\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Software Industry is evolving at a very fast pace since last two decades. Many software developments, testing and test case generation approaches have evolved in last two decades to deliver quality products and services. Testing plays a vital role to ensure the quality and reliability of software products. In this paper authors attempted to conduct a systematic study of testing tools and techniques. Six most popular e-resources called IEEE, Springer, Association for Computing Machinery (ACM), Elsevier, Wiley and Google Scholar to download 738 manuscripts out of which 125 were selected to conduct the study. Out of 125 manuscripts selected, a good number approx. 79% are from reputed journals and around 21% are from good conference of repute. Testing tools discussed in this paper have broadly been divided into five different categories: open source, academic and research, commercial, academic and open source, and commercial & open source. The paper also discusses several benchmarked datasets viz. Evosuite 10, SF100 Corpus, Defects4J repository, Neo4j, JSON, Mocha JS, and Node JS to name a few. Aim of this paper is to make the researchers aware of the various test case generation tools and techniques introduced in the last 11 years with their salient features.\",\"PeriodicalId\":44185,\"journal\":{\"name\":\"International Journal of Mathematical Engineering and Management Sciences\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.3000,\"publicationDate\":\"2023-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Mathematical Engineering and Management Sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.33889/ijmems.2023.8.2.018\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Mathematical Engineering and Management Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.33889/ijmems.2023.8.2.018","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
Software Test Case Generation Tools and Techniques: A Review
Software Industry is evolving at a very fast pace since last two decades. Many software developments, testing and test case generation approaches have evolved in last two decades to deliver quality products and services. Testing plays a vital role to ensure the quality and reliability of software products. In this paper authors attempted to conduct a systematic study of testing tools and techniques. Six most popular e-resources called IEEE, Springer, Association for Computing Machinery (ACM), Elsevier, Wiley and Google Scholar to download 738 manuscripts out of which 125 were selected to conduct the study. Out of 125 manuscripts selected, a good number approx. 79% are from reputed journals and around 21% are from good conference of repute. Testing tools discussed in this paper have broadly been divided into five different categories: open source, academic and research, commercial, academic and open source, and commercial & open source. The paper also discusses several benchmarked datasets viz. Evosuite 10, SF100 Corpus, Defects4J repository, Neo4j, JSON, Mocha JS, and Node JS to name a few. Aim of this paper is to make the researchers aware of the various test case generation tools and techniques introduced in the last 11 years with their salient features.
期刊介绍:
IJMEMS is a peer reviewed international journal aiming on both the theoretical and practical aspects of mathematical, engineering and management sciences. The original, not-previously published, research manuscripts on topics such as the following (but not limited to) will be considered for publication: *Mathematical Sciences- applied mathematics and allied fields, operations research, mathematical statistics. *Engineering Sciences- computer science engineering, mechanical engineering, information technology engineering, civil engineering, aeronautical engineering, industrial engineering, systems engineering, reliability engineering, production engineering. *Management Sciences- engineering management, risk management, business models, supply chain management.