Empirical Study on Tendencies for Unstable Situations in Application Results of Software Reliability Growth Model accepted for IEEE ISSRE 2018 Industry Track (CORE Rank A)

Kiyoshi Honda, Hironori Washizaki, Yoshiaki Fukazawa, Masahiro Taga, Akira Matsuzaki and Takayoshi Suzuki, “Empirical Study on Tendencies for Unstable Situations in Application Results of Software Reliability Growth Model,” The 29th IEEE International Symposium on Software Reliability Engineering (ISSRE 2018), Industry Track, Memphis, USA, October 15-18, 2018 (CORE Rank A)

Monitoring the results of software reliability growth models (SRGMs) helps evaluate a project’s situation. SRGMs are used to measure the reliability of software by analyzing the relations between the number of detected bugs and the detection time to predict the number of remaining bugs within the software. Sometimes the SRGM results lead managers to make incorrect decisions because the results are temporary snapshots that change over time. In our previous study, we proposed a method to help evaluate a project’s qualities by monitoring the results of SRGM applications. We collected the number of detected bugs and the detection time in the test phases for cloud services provided by e-Seikatsu to real estate businesses. The datasets contain about 34 cloud service features. Our method provides correct answers for 29 features and incorrect answers for 5 features. In this paper, we classify the monitoring results of unstable features based on the tendencies of the results into four types to aid developers and managers to make appropriate decisions about the development status.