Abstract
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 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.
Original language | English |
---|---|
Title of host publication | Proceedings - 29th IEEE International Symposium on Software Reliability Engineering Workshops, ISSREW 2018 |
Editors | Roberto Natella, Sudipto Ghosh, Nuno Laranjeiro, Robin Poston, Bojan Cukic |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 89-94 |
Number of pages | 6 |
ISBN (Electronic) | 9781538694435 |
DOIs | |
Publication status | Published - 2018 Nov 16 |
Event | 29th IEEE International Symposium on Software Reliability Engineering Workshops, ISSREW 2018 - Memphis, United States Duration: 2018 Oct 15 → 2018 Oct 18 |
Other
Other | 29th IEEE International Symposium on Software Reliability Engineering Workshops, ISSREW 2018 |
---|---|
Country/Territory | United States |
City | Memphis |
Period | 18/10/15 → 18/10/18 |
Keywords
- Fault Analysis
- Project Monitoring
- Software Reliability Growth Model
ASJC Scopus subject areas
- Software
- Safety, Risk, Reliability and Quality