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    National Tsing Hua University Institutional Repository > 電機資訊學院 > 資訊工程學系 > 期刊論文 >  Evaluation and Application of Bounded Generalized Pareto Analysis to Fault Distributions in Open Source Software


    Please use this identifier to cite or link to this item: http://nthur.lib.nthu.edu.tw/dspace/handle/987654321/82436


    Title: Evaluation and Application of Bounded Generalized Pareto Analysis to Fault Distributions in Open Source Software
    Authors: C. Y. Huang;C. S. Kuo;S. P. Luan
    教師: 黃慶育
    Date: 2014
    Publisher: Institute of Electrical and Electronics Engineers
    Relation: IEEE Transactions on Reliability, IEEE, Volume 63, Issue 1, March 2014, Pages 309-319
    Keywords: Fault distribution
    Pareto principle
    Weibull model
    open source software
    software quality
    software reliability
    software testing
    Abstract: In general, one of the most important aspects of software development and project management is how to make predictions and assessments of quality and reliability for developed products. Project data usually will be systematically collected and analyzed during the process of software development. Practically, it would be helpful if developers could identify the most error-prone modules early so that they can optimize testing-resource allocation and increase fault detection effectiveness accordingly. In the past, many research studies revealed the applicability of the Pareto principle to software systems, and some of them reported that the Pareto distribution (PD) model can be used to predict the fault distribution of software. In this paper, a special form of the Generalized PD model, named the Bounded Generalized Pareto distribution (BGPD) model, is further proposed to investigate the fault distributions of Open Source Software (OSS). It can be seen that the BGPD model eliminates the issue which occurred in the classical PD model. Three methods of parameter estimation will be presented, and related experiments are performed based on real OSS failure data. Experimental results show that the BGPD model presents high fitness to the actual failure data of OSS. Finally, the possibility of using early limited fault data to predict the later software fault distribution is also studied. Numerical results indicate that the BGPD model can be trusted to consistently produce accurate estimates of fault predictions during the early stages of development. The findings can provide an effective foundation for managing the necessary activities of software development and testing.
    Relation Link: http://www.ieee.org/
    URI: http://nthur.lib.nthu.edu.tw/dspace/handle/987654321/82436
    Appears in Collections:[資訊工程學系] 期刊論文
    [資訊系統與應用研究所] 期刊論文

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