A software reliability model incorporating fault removal efficiency and it’s release policy

• Published in: Computational statistics Vol. 39; no. 6; pp. 3137 - 3155
• Main Authors: Samal, Umashankar, Kumar, Ajay
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.09.2024; Springer Nature B.V
• Subjects: Automation; Costs; Debugging; Economic Theory/Quantitative Economics/Mathematical Methods; Efficiency; Failure; Growth models; Mathematics and Statistics; Original Paper; Probability and Statistics in Computer Science; Probability Theory and Stochastic Processes; Reliability analysis; Software development; Software industry; Software reliability; Software testing; Statistics; Software cost model; Non-homogenous Poisson process; Software reliability; Fault removal efficiency
• ISSN: 0943-4062; 1613-9658
• DOI: 10.1007/s00180-023-01430-9

For software developers as well as software product users, fault removal efficiency is crucial. Developers can estimate the amount of work required by evaluating the proportion of addressed faults. At the same time, the level of trust in utilizing the software product can be determined by customers, based on this information. The proposed software reliability growth model considers fault removal efficiency relevant to contemporary scenarios characterized by automated testing and debugging tools. A comparison between the proposed model and other existing models is conducted by utilizing two data sets from software testing. Additionally, the best release plans are created by considering warranty costs, risk costs, and error removal costs while still meeting reliability requirements.