• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

计算机工程与科学

• 软件工程 • 上一篇    下一篇

SRGM下失效数据集效用与验证分析

张策1,伊文敏2,白睿1,盛晟1,徐早辉1,高天翼1,王瞰宇1,苏嘉尧1   

  1. (1.哈尔滨工业大学(威海)计算机科学与技术学院,山东 威海 264209;2.61660部队,北京 100089)

     
  • 收稿日期:2019-10-08 修回日期:2020-02-07 出版日期:2020-06-25 发布日期:2020-06-25
  • 基金资助:

    国家科技支撑计划(2014BAF07B02);国家自然科学基金(61473097);山东省重点研发计划(GG201703130116,GG201703040002);威海市科技发展计划(ITEAZMZ001807)

Utility and verification of failure data set in SRGM

ZHANG Ce1,YI Wen-min2,BAI Rui1,SHENG Sheng1,XU Zao-hui1,GAO Tian-yi1,WANG Kan-yu1,SU Jia-yao1#br#  
  

  1. (1.School of Computer Science and Technology,Harbin Institute of Technology (Weihai),Weihai 264209;
    2.Troop 61660,Beijing 100089,China)
  • Received:2019-10-08 Revised:2020-02-07 Online:2020-06-25 Published:2020-06-25

摘要:

针对软件可靠性增长模型SRGM研究中的参数拟合与性能评测对失效数据集FDS的依赖,对FDS在SRGM中的效用以及其对SRGM的影响进行深入研究,并给出FDS的不足与发布建议。首先给出了基于FDS的SRGM性能评测流程,提出一般化的不完美排错框架模型,对收集到的FDS进行结构化描述与归类分析。对7个典型的不完美排错相关的SRGM在公开发表的9个真实计算机工程系统FDSs上进行实验,从拟合与预测角度分析FDS与SRGM的关系及影响。从发布方与科研人员视角对当前FDS的不足进行分析,并据此给出了FDS的发布建议。研究结果表明,科研人员尚需要充分挖掘、分析FDS中待发布的更多测试信息,用以建立更为准确的SRGM。最后指出,描述新型软件结构以及含有更多数据量的FDS的缺乏已成为制约SRGM发展的主要客观事实。
 

关键词: 失效数据集, 软件可靠性增长模型, 非齐次泊松过程, 效用

Abstract:

Aiming at the dependence of parameter fitting and performance evaluation on the FDS (Failure Dataset) in SRGM (Software Reliability Growth Model), the function and the impact of FDS on SRGM are studied, and the drawbacks and release advice are proposed. Firstly, SRGM performance evaluation flowchart is sketched and the collected FDSs are described, classified and analyzed. Secondly, 7 typical imperfect debugging dependent of SRGMs are evaluated on 9 FDSs. Furthermore, the fitting and prediction impact of FDS on SRGM are analyzed. From the view of publisher and researcher, the deficiencies in FDS are pointed out and the suggestions on releasing FDS are given. The research result shows that the researchers need to fully mine the testing information in FDS and establish more accurate SRGMs. Finally, the lack of the FDSs describing the new type of software structure and containing a large amount of failure information has been the bottleneck to restrict the development of SRGM.

 

Key words: failure dataset, software reliability growth model (SRGM), non-homogeneous Poisson process, utility