Zhanqi Cui , Haochen Jin , Xiang Chen , Rongcun Wang , Xiulei Liu
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引用次数: 0
Abstract
Fuzz testing is an automated testing technique that is recognized for its efficiency and scalability. Despite its advantages, the growing complexity and scale of software has made testing software adequately increasingly challenging. If fuzz testing can prioritize resources for modules with higher defect proneness, it can effectively enhance its defect detection performance. In this paper, we introduce DPFuzz, a tool for prioritizing the resource allocation of fuzz testing. DPFuzz guides fuzz testing by calculating the fitness score, which is based on the coverage of modules with different defect proneness. DPFuzz also demonstrates the practicability of using defect prediction in software quality assurance and has confirmed its excellent defect detection performance through experiments.
期刊介绍：
Science of Computer Programming is dedicated to the distribution of research results in the areas of software systems development, use and maintenance, including the software aspects of hardware design.
The journal has a wide scope ranging from the many facets of methodological foundations to the details of technical issues andthe aspects of industrial practice.
The subjects of interest to SCP cover the entire spectrum of methods for the entire life cycle of software systems, including
• Requirements, specification, design, validation, verification, coding, testing, maintenance, metrics and renovation of software;
• Design, implementation and evaluation of programming languages;
• Programming environments, development tools, visualisation and animation;
• Management of the development process;
• Human factors in software, software for social interaction, software for social computing;
• Cyber physical systems, and software for the interaction between the physical and the machine;
• Software aspects of infrastructure services, system administration, and network management.
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