Software Reliability Assessment Models Incorporating Software Defect Correlation
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    Abstract:

    Mostly, defect correlation is caused by the defect detected capability masked by other defects. Defect correlation affects the result of the test and makes the results in accurate and distorts the estimated results of software reliability assessment models. From the standpoint of defects themselves, this paper makes a detailed analysis of defect correlation and gives the reasons of the software testing and reliability assessment out of action. By applying the generalized correlation to improve the existing reliability assessment models, this paper puts forward the P-NHPP (phase-nonhomogeneous poisson process) reliability model to make the reliability assessment parameters more coordinated with the actual defect number. Experimental results show that P-NHPP is better and has a fairly accurate prediction capability.

    Reference
    [1] Xie M. Software Reliability Modeling. World Scientific Publishing Company, 1991. 9?20.
    [2] Lyu MR. Hand Book of Software Reliability Engineering. McGraw-Hill, 1996. 71?118.
    [3] Wang Q, Wu SJ, Li MS. Software defect prediction. Journal of Software, 2008,19(7):1565?1580 (in Chinese with English abstract). http://www.jos.org.cn/1000-9825/19/1565.htm [doi: 10.3724/SP.J.1001.2008.01565]
    [4] Katerina GP, Trivedi KS. Failure correlation in software reliability models. IEEE Trans. on Reliability, 2000,49(1):37?48. [doi: 10.1109/24.855535]
    [5] Jing T, Jiang CH, Hu DB, Bai CG, Cai KY. An approach for detecting correlated software defects. Journal of Software, 2005,16(1): 17?28 (in Chinese with English abstract). http://www.jos.org.cn/1000-9825/16/17.htm [doi: 10.1360/jos160017e]
    [6] Hamlet D. Are we testing for true reliability? IEEE Software, 1992,9(4):21?27. [doi: 10.1109/52.143097]
    [7] Sahinoglu M. Compound-Poisson software reliability model. IEEE Trans. on Software Engineering, 1992,18(7):624?630. [doi: 10.1109/32.148480]
    [8] Tomek LA, Muppala JK, Trivedi KS. Modeling correlation in software recovery blocks. IEEE Trans. on Software Engineering, 1993,19(11):1071?1086. [doi: 10.1109/32.256854]
    [9] Chen S, Mills S. A binary Markov process model for random testing. IEEE Trans. on Software Engineering, 1996,22(3):218?223. [doi: 10.1109/32.489081]
    [10] Bishop PG, Pullen FD. PODS revisited—A study of software failure behavior. In: Proc. of the IEEE Int’l Symp. on Fault Tolerant Computing. 1988. 2?8. [doi: 10.1109/FTCS.1988.5289]
    [11] 2002. http://software.ccidnet.com/pub/disp/Article?columnID=375&articleID=25560&pageNO=1
    [12] Miu HK, Li G, Zhu GM. Software Engineer Language—Z. Shanghai: Shanghai Scientific and Technology Literature Publishing House, 1999 (in Chinese).
    [13] Rothermel G, Untch RH, Harrold MJ. Prioritizing test cases for regression testing. IEEE Trans. on Software Engineering, 2001, 27(10):929?948. [doi: 10.1109/32.962562]
    [14] Pham H, Nordmann L, Zhang XM. A general imperfect-software-debugging model with S-shaped fault-detection rate. IEEE Trans. on Reliability, 1999,48(2):169?175. [doi: 10.1109/24.784276]
    [15] Yamada S. Software reliability models and their applications: A survey. In: Proc. of the Int’l Seminar on Software Reliability of Man-Machine Systems. Kyoto: Kyoto University, 2000. 56?80.
    [16] Huang CY, Lin CT, Kuo SY, Lyu MR, Sue CC. Software reliability growth models incorporating fault dependency with various debugging time lags. In: Proc. of the 28th Annual Int’l Computer Software and Applications Conf. 2004. 186?191. [doi: 10.1109/CMPSAC.2004.1342826]
    [17] Zhao M, Xie M. On the log-power NHPP software reliability model. In: Proc. of the 3rd Int’l Symp. on Software Reliability Engineering. North Carolina: Research Triangle Park, 1992. 14?22. [doi: 10.1109/ISSRE.1992.285862]
    [18] Kapur PK, Garg RB, Kumar S. Contributions to Hardware and Software Reliability. World Scientific Publishing Company, 1999. 96?109.
    [19] Goel AL, Okumoto K. Time-Dependent error-detection rate model for software and other performance measures. IEEE Trans. on Reliability, 1979,28(3):206?221. [doi: 10.1109/TR.1979.5220566]
    [20] Yamada S, Ohba M, Osaki S. S-Shaped software reliability growth modeling for software error detection. IEEE Trans. on Reliability, 1983, 32(5): 475?484. [doi: 10.1109/TR.1983.5221735]
    [21] Goel AL. Software reliability models: Assumptions, limitations, and applicability. IEEE Trans. on Software Engineering, 1985, SE-11(12):1411?1423. [doi: 10.1109/TSE.1985.232177]
    [22] Jeske DR, Zhang XM, Pham L. Adjust software failure rates that are estimated from test data. IEEE Trans. on Reliability, 2005, 54(1):107?114. [doi: 10.1109/TR.2004.842531]
    [23] Zhao J, Liu HW, Cui G, Yang XZ. A software reliability growth model considering testing environment and actual operation environment. Journal of Computer Research and Development, 2006,43(5):881?887 (in Chinese with English abstract). [doi: 10.1360/crad20060517]
    [24] Hutchins M, Foster H, Goradia T, Ostrand T. Experiments on the effectiveness of dataflow-and controlflow-based test adequacy criteria. In: Proc. of the 16th Int’l Conf. on Software Engineering. 1994. 191?200.
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徐高潮,刘新忠,胡亮,付晓东,董玉双.引入关联缺陷的软件可靠性评估模型.软件学报,2011,22(3):439-450

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  • Received:March 30,2009
  • Revised:July 21,2009
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