{"title":"人机配对编程的程序段测试","authors":"Lei Rao, Shaoying Liu, A. Liu","doi":"10.1142/s0218194024500281","DOIUrl":null,"url":null,"abstract":"Human–Machine Pair Programming (HMPP) is a promising technique in the software development process, which means that software construction can be done in the manner that humans are responsible for developing the program while computer is responsible for monitoring the program in real-time and reporting errors. The Java runtime exceptions in the current version of the software under construction can only be effectively detected by means of its execution. Traditional software testing techniques are suitable for testing completed programs but face a challenge in building a suitable testing environment for testing the partial programs produced during HMPP. In this paper, we put forward a novel technique, called Program Segment Testing (PST) for automatically identifying errors caused by runtime exceptions to support HMPP. We first introduce the relevant involved in this technique to detect index out of bounds exceptions, a representative of runtime exceptions. Then we discuss the methodology of this technique in detail and illustrate its workflow with a simple case study. Finally, we carry out an experiment to evaluate this technique and compare it with three existing fault detection techniques using several programs to demonstrate its effectiveness.","PeriodicalId":50288,"journal":{"name":"International Journal of Software Engineering and Knowledge Engineering","volume":null,"pages":null},"PeriodicalIF":0.6000,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Program Segment Testing for Human–Machine Pair Programming\",\"authors\":\"Lei Rao, Shaoying Liu, A. Liu\",\"doi\":\"10.1142/s0218194024500281\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Human–Machine Pair Programming (HMPP) is a promising technique in the software development process, which means that software construction can be done in the manner that humans are responsible for developing the program while computer is responsible for monitoring the program in real-time and reporting errors. The Java runtime exceptions in the current version of the software under construction can only be effectively detected by means of its execution. Traditional software testing techniques are suitable for testing completed programs but face a challenge in building a suitable testing environment for testing the partial programs produced during HMPP. In this paper, we put forward a novel technique, called Program Segment Testing (PST) for automatically identifying errors caused by runtime exceptions to support HMPP. We first introduce the relevant involved in this technique to detect index out of bounds exceptions, a representative of runtime exceptions. Then we discuss the methodology of this technique in detail and illustrate its workflow with a simple case study. Finally, we carry out an experiment to evaluate this technique and compare it with three existing fault detection techniques using several programs to demonstrate its effectiveness.\",\"PeriodicalId\":50288,\"journal\":{\"name\":\"International Journal of Software Engineering and Knowledge Engineering\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.6000,\"publicationDate\":\"2024-07-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Software Engineering and Knowledge Engineering\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1142/s0218194024500281\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Software Engineering and Knowledge Engineering","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1142/s0218194024500281","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
Program Segment Testing for Human–Machine Pair Programming
Human–Machine Pair Programming (HMPP) is a promising technique in the software development process, which means that software construction can be done in the manner that humans are responsible for developing the program while computer is responsible for monitoring the program in real-time and reporting errors. The Java runtime exceptions in the current version of the software under construction can only be effectively detected by means of its execution. Traditional software testing techniques are suitable for testing completed programs but face a challenge in building a suitable testing environment for testing the partial programs produced during HMPP. In this paper, we put forward a novel technique, called Program Segment Testing (PST) for automatically identifying errors caused by runtime exceptions to support HMPP. We first introduce the relevant involved in this technique to detect index out of bounds exceptions, a representative of runtime exceptions. Then we discuss the methodology of this technique in detail and illustrate its workflow with a simple case study. Finally, we carry out an experiment to evaluate this technique and compare it with three existing fault detection techniques using several programs to demonstrate its effectiveness.
期刊介绍:
The International Journal of Software Engineering and Knowledge Engineering is intended to serve as a forum for researchers, practitioners, and developers to exchange ideas and results for the advancement of software engineering and knowledge engineering. Three types of papers will be published:
Research papers reporting original research results
Technology trend surveys reviewing an area of research in software engineering and knowledge engineering
Survey articles surveying a broad area in software engineering and knowledge engineering
In addition, tool reviews (no more than three manuscript pages) and book reviews (no more than two manuscript pages) are also welcome.
A central theme of this journal is the interplay between software engineering and knowledge engineering: how knowledge engineering methods can be applied to software engineering, and vice versa. The journal publishes papers in the areas of software engineering methods and practices, object-oriented systems, rapid prototyping, software reuse, cleanroom software engineering, stepwise refinement/enhancement, formal methods of specification, ambiguity in software development, impact of CASE on software development life cycle, knowledge engineering methods and practices, logic programming, expert systems, knowledge-based systems, distributed knowledge-based systems, deductive database systems, knowledge representations, knowledge-based systems in language translation & processing, software and knowledge-ware maintenance, reverse engineering in software design, and applications in various domains of interest.