人机配对编程的程序段测试

IF 0.6 4区 计算机科学 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Lei Rao, Shaoying Liu, A. Liu
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引用次数: 0

摘要

人机结对编程(HMPP)是软件开发过程中一项很有前途的技术,它意味着可以采用人负责开发程序,计算机负责实时监控程序并报告错误的方式来构建软件。当前版本的在建软件中的 Java 运行时异常只能通过执行来有效检测。传统的软件测试技术适用于测试已完成的程序,但要构建一个合适的测试环境来测试 HMPP 过程中产生的部分程序,则面临着挑战。本文提出了一种名为程序段测试(PST)的新技术,用于自动识别运行时异常引起的错误,以支持 HMPP。我们首先介绍了该技术检测索引越界异常(运行时异常的代表)所涉及的相关内容。然后,我们详细讨论了该技术的方法,并通过一个简单的案例研究说明了其工作流程。最后,我们进行了一项实验来评估这项技术,并使用几个程序将其与现有的三种故障检测技术进行比较,以证明其有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.
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来源期刊
CiteScore
1.90
自引率
11.10%
发文量
71
审稿时长
16 months
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.
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