Software Reliability Assessment via Non-Parametric Maximum Likelihood Estimation

• SAITO Yasuhiro

  Department of Information Engineering, Graduate School of Engineering, Hiroshima University

• DOHI Tadashi

  Department of Information Engineering, Graduate School of Engineering, Hiroshima University

Abstract

In this paper we consider two non-parametric estimation methods for software reliability assessment without specifying the fault-detection time distribution, where the underlying stochastic process to describe software fault-counts in the system testing is given by a non-homogeneous Poisson process. The resulting data-driven methodologies can give the useful probabilistic information on the software reliability assessment under the incomplete knowledge on fault-detection time distribution. Throughout examples with real software fault data, it is shown that the proposed methods provide more accurate estimation results than the common parametric approach.

Journal

• IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences

  IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E98.A (10), 2042-2050, 2015

  The Institute of Electronics, Information and Communication Engineers

Keywords

• software reliability
• non-parametric maximum likelihood estimation
• non-homogeneous Poisson process
• software failure rate
• software intensity function

Details

• CRID: 1390001206309987200
• NII Article ID: 130005100661
• DOI: 10.1587/transfun.e98.a.2042
• ISSN: 17451337
• ISSN: 09168508
• Web Site: https://www.jstage.jst.go.jp/article/transfun/E98.A/10/E98.A_2042/_pdf
• Text Lang: en
• Data Source:
  • JaLC
  • Crossref
  • CiNii Articles
• Abstract License Flag: Disallowed