• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

Computer Engineering & Science ›› 2025, Vol. 47 ›› Issue (7): 1244-1261.

• Software Engineering • Previous Articles     Next Articles

Survey of fuzzing test case generation techniques

LIU Hui1,2,HOU Tongding1,2,ZHAO Bo3,4,GUO Hanbin1,2   

  1. (1.School of Computer and Information Engineering,Henan Normal University,Xinxiang 453007;
    2.Key Laboratory of Artificial Intelligence and Personalized Learning in Education of Henan Province,Xinxiang 453007;
    3.State Key Laboratory of Mathematical Engineering and Advanced Computing,Zhengzhou 450001;
    4.School of Cyberspace Security,PLA Strategic Support Force Information Engineering University,Zhengzhou 450001,China)
  • Received:2024-01-18 Revised:2024-03-29 Online:2025-07-25 Published:2025-08-25

Abstract: Fuzzing test is one of the mainstream software vulnerability detection technologies and has been widely applied across various fields.In recent years,significant progress has been made in the research of fuzzing test case generation techniques.Firstly,this paper reviews the development of fuzzing test case generation technology,classifying and summarizing relevant research while providing a comprehensive comparison.Secondly,based on an in-depth study of fuzzing test case generation techniques,this paper establishs a framework for constructing test cases through both generation-based and mutation-based approaches.Subsequently,this paper categorizes fuzzing test case construction techniques,delving into the process by which fuzzers extract features from program structure and semantics and combine feedback information to generate test cases.Furthermore,this paper classifies and elaborates  on the challenges and tasks faced by existing fuzzing test case generation techniques in four key areas:browsers,network protocols,compilers,and operating systems,followed by a systematic summary and comparative analysis.Finally,this paper discusses the limitations and potential solutions of current fuzzing test case generation techniques from multiple perspectives and outlines promising future research directions in this field.

Key words: fuzzing test, test case generation, seed optimization strategy, vulnerability mining, software security