Impacts of networking effects on software reliability growth processes: A multi‐attribute utility theory approach

Abstract

Software reliability growth models, which are based on nonhomogeneous Poisson processes, are widely adopted tools when describing the stochastic failure behavior and measuring the reliability growth in software systems. Faults in the systems, which eventually cause the failures, are usually connected with each other in complicated ways. Considering a group of networked faults, we raise a new model to examine the reliability of software systems and assess the model's performance from real-world data sets. Our numerical studies show that the new model, capturing networking effects among faults, well fits the failure data. We also formally study the optimal software release policy using the multi-attribute utility theory (MAUT), considering both the reliability attribute and the cost attribute. We find that, if the networking effects among different layers of faults were ignored by the software testing team, the best time to release the software package to the market would be much later while the utility reaches its maximum. Sensitivity analysis is further delivered. KEYWORDS multi-attribute utility theory, networking effects, nonhomogeneous poisson processes, software release policy, software reliability growth model 1952

Modelling reliability growth for multi‐version open source software considering varied testing and debugging factors

“…Various frameworks have been proposed that give reliability assessment of the safety‐critical systems using Bayesian update methodology 47 . A modified NHPP model has also been proposed for OSS reliability modelling and analysis and based on this model and multi‐attribute utility theory, optimal version updating for OSS has been examined resulting in a new decision model 44,46 . A framework to model the failure occurrence in OSS is developed to check the reliability growth 49 .…”

“…47 A modified NHPP model has also been proposed for OSS reliability modelling and analysis and based on this model and multi-attribute utility theory, optimal version updating for OSS has been examined resulting in a new decision model. 44,46 A framework to model the failure occurrence in OSS is developed to check the reliability growth. 49 A new SRGM is developed by considering generalized Pareto distribution for fault introduction rate for OSS.…”

“…Various methods to evaluate the reliability of the software have been studied and presented in literature 1,2 . One of the methods which have been applied widely is Software Reliability Growth Models 1–3,33,44 . There are numerous frameworks under which SRGMs can be developed, the Non‐Homogeneous Poisson Process being the effective one 1 .…”

“…1,2 One of the methods which have been applied widely is Software Reliability Growth Models. [1][2][3]33,44 There are numerous frameworks under which SRGMs can be developed, the Non-Homogeneous Poisson Process being the effective one. 1 With the help of NHPP, many critical decisions regarding reliability prediction, resource allocation, cost analysis, testing time etc.…”

Entropy based enhanced particle swarm optimization on multi‐objective software reliability modelling for optimal testing resources allocation

“…Roy et al [7] studied an NHPP based S-shaped software reliability growth model incorporating imperfect debugging with a new exponentially increasing fault content function. Yi et al [8] presented NHPP based software reliability growth models with stochastic failure behaviour for a group of networked faults. Kumar et al [9] investigated NHPP based software reliability models undertakes the estimation and prediction of the failure phenomenon.…”