Statistical Process Control Assessment for Open Source Software and Its Application  
Author Shigeru Yamada


Co-Author(s) Masakazu Yamaguchi


Abstract A software development paradigm for open source software (abbreviated as OSS) project has been rapidly spread in recent years. On the other hand, an effective method of quality management has not been established due to the unique development characteristics, and no testing phase. In this paper, we assume that the number of fault-detections observed on the bug tracking system tends to infinity, and discuss a method of statistical process control for OSS projects by applying the logarithmic Poisson execution time model as a software reliability growth model (abbreviated as SRGM) based on a nonhomogeneous Poisson process (abbreviated as NHPP). Then, we propose a control chart method based on the logarithmic Poisson execution time model for judging the statical stability state, and estimating the additional development time for attaining the objective software failure intensity, i.e., the instantaneous fault-detection rate per unit time. We also discuss an optimal software release problem for determining the optimum time when to stop OSS development and to transfer it to user operation. Further, numerical illustrations for statistical process control are shown by applying the actual fault-count data observed on the bug tracking system.


Keywords Open Source Software, Statistical Process Control (SPC), Control Chart, Software Reliability Growth Model (SRGM), Logarithmic Poisson Execution Time Model, Additional Development Time, Optimal Release
    Article #:  22162
Proceedings of the 22nd ISSAT International Conference on Reliability and Quality in Design
August 4-6, 2016 - Los Angeles, California, U.S.A.