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J4  2011, Vol. 45 Issue (9): 1553-1557    DOI: 10.3785/j.issn.1008-973X.2011.09.007
    
Improvement of reassignment strategy in defects removal
based on queuing theory and simulation
WANG Fan,YANG Xiao-hu
College of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China
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Abstract  

Aimed at the unreasonable assumptions of defects removal process in current software reliability research, the defects removal in testing process was simulated by queuing theory. The defects occurrence process was approximately represented as non-homogeneous Poisson process, and the defects removal capability of a project team was represented by n independent single sever with multiple (M/M/1) queues. The impact of different defects reassignment to software testing was discussed, then an improved dynamic defects reassignment strategy was proposed. This strategy can effectively balance the utilization of developers, decrease the mean time of waiting and removing for defects, and help project managers to adjust testing plan and resource allocation.



Published: 01 September 2011
CLC:  TP 311.5  
Cite this article:

WANG Fan,YANG Xiao-hu. Improvement of reassignment strategy in defects removal
based on queuing theory and simulation. J4, 2011, 45(9): 1553-1557.

URL:

https://www.zjujournals.com/eng/10.3785/j.issn.1008-973X.2011.09.007     OR     https://www.zjujournals.com/eng/Y2011/V45/I9/1553


基于排队论和模拟的缺陷移除重分配策略改进

针对目前软件可靠性研究中对于缺陷移除过程中的不合理假设,应用排队论来模拟软件测试过程中的缺陷移除过程, 利用非齐次泊松过程可以近似地模拟缺陷的发现过程,n个独立的单队多服务台(M/M/1)队列用来表示项目组移除缺陷的能力.讨论了不同的缺陷重分配策略对于软件测试的影响,提出一个改进的动态调度的缺陷重分配策略,该策略可以更好地平衡开发人员的利用率,缩短缺陷的平均等待和移除时间,从而帮助项目经理调整人员配置和测试计划.

[1] GOEL A L,OKUMOTO K. Timedependent errordetection rate model for software reliability and other performance measures [J]. IEEE Transactions on Reliability, 1979, 28(3): 206-211.
[2] YAMADA S, OHBA M, OSAKI S. Sshaped reliability growth modeling for software error detection [J]. IEEE Transactions on Reliability, 1983, 32(5): 475-478.
[3] OHBA M. Infection Sshaped software reliability growth model [C]∥ Stochastic Models in Reliability Theory: Proceedings of a Symposium. Nagoya,Japan: Springer Verlag, 1984: 144-162.
[4] GOKHALE S S, MULLEN R E. Queuing models for feld defect resolution process [C]∥ ISSRE’06. Raleigh, USA: [s. n.], 2006: 353-362.
[5] DOHI T, OSAKI S, TRIVEDI K S. An infnite server queueing approach for describing software reliability growth: unifed modeling and estimation framework [C]∥ APSEC2004. Busan,Korea: [s. n.], 2004: 110-119.

[6] HUANG W C, HUANG C Y, SUE C C. Software reliability prediction and assessment using both finite and infnite server queueing approaches [C]∥ PRDC’06. Riverside, USA: [s. n.],2006: 194-201.
[7] GOKHALE S S, LYU M R T. A simulation approach to structurebased software reliability analysis [J]. IEEE Transactions on Software Engineering, 2005, 31(8): 643-656.
[8] WANG F, YANG Xiaohu, ZHU Xiaochun, et al. Simulation of the defect removal process with queuing theory [C]∥ ESEM2009. Lake Buena Vista,USA: [s. n.], 2009: 473-476.
[9] RUBINSTEIN R Y, KROESE D P. Simulation and the Monte Carlo method [M]. 2rd ed. [S. 1.]: WileyInterscience, 2007:71-72.
[10] XIE M. Software reliability modeling [M]. [S. 1.]: World Scientic Pub Co Inc, 1991:88-92.
[11] LYU M R. Handbook of software reliability engineering [M].New York: IEEE Computer Society Press and McGrawHill Book Company, 1996:80-82.

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