A software reliability growth model for component-based software incorporating debugging delay and imperfect debugging

作     者：张策 Cui Gang Meng Fanchao Liu Hongwei Bian Yali 

作者机构：School of Computer Science and TechnologyHarbin Institute of Technology School of Computer Science and TechnologyHarbin Institute of Technology at Weihai 

出 版 物：《High Technology Letters》 (高技术通讯（英文版）)

年 卷 期：2015年第21卷第1期

页      面：54-62页

核心收录：

学科分类：08[工学] 0835[工学-软件工程] 081202[工学-计算机软件与理论] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：Supported by the National High Technology Research and Development Program of China(No.2008AA01A201) the National Natural Science Foundation of China(No.60503015) the National Key R&D Program of China(No.2013BA17F02) the Shandong Province Science and Technology Program of China(No.2011GGX10108,2010GGX10104) 

主　　题：software reliability component-based software (CBS) debugging delay imper- fect debugging queuing theory 

摘      要：In view of the problems and the weaknesses of component-based software （ CBS ） reliability modeling and analysis, and a lack of consideration for real debugging circumstance of integration tes- ting, a CBS reliability process analysis model is proposed incorporating debugging time delay, im- perfect debugging and limited debugging resources. CBS integration testing is formulated as a multi- queue muhichannel and finite server queuing model （MMFSQM） to illustrate fault detection process （FDP） and fault correction process （FCP）. A unified FCP is sketched, given debugging delay, the diversities of faults processing and the limitations of debugging resources. Furthermore, the impacts of imperfect debugging on fault detection and correction are explicitly elaborated, and the expres- sions of the cumulative number of fault detected and corrected are illustrated. Finally, the results of numerical experiments verify the effectiveness and rationality of the proposed model. By comparison, the proposed model is superior to the other models. The proposed model is closer to real CBS testing process and facilitates software engineer＇ s quantitatively analyzing, measuring and predicting CBS reliability. K