Software reliability analysis models
IBM Journal of Research and Development
Software reliability: measurement, prediction, application
Software reliability: measurement, prediction, application
Handbook of software reliability engineering
Handbook of software reliability engineering
Software reliability prediction incorporating information from a similar project
Journal of Systems and Software
Software Reliability
Software Engineering: A Practitioner's Approach
Software Engineering: A Practitioner's Approach
A Unified Scheme of Some Nonhomogenous Poisson Process Models for Software Reliability Estimation
IEEE Transactions on Software Engineering
Optimal Software Release Policy Based on Cost and Reliability with Testing Efficiency
COMPSAC '99 23rd International Computer Software and Applications Conference
Pragmatic Study of Parametric Decomposition Models for Estimating Software Reliability Growth
ISSRE '98 Proceedings of the The Ninth International Symposium on Software Reliability Engineering
Software Reliability Modeling and Cost Estimation Incorporating Testing-Effort and Efficiency
ISSRE '99 Proceedings of the 10th International Symposium on Software Reliability Engineering
A stochastic software reliability model with imperfect-debugging and change-point
Journal of Systems and Software
Software Reliability Engineering: More Reliable Software Faster and Cheaper
Software Reliability Engineering: More Reliable Software Faster and Cheaper
Considering fault removal efficiency in software reliability assessment
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Journal of Systems and Software
An integration of fault detection and correction processes in software reliability analysis
Journal of Systems and Software - Special issue: Selected papers from the 4th source code analysis and manipulation (SCAM 2004) workshop
Using Software Reliability Growth Models in Practice
IEEE Software
Journal of Systems and Software
Bayesian updating of optimal release time for software systems
Software Quality Control
Software reliability analysis and assessment using queueing models with multiple change-points
Computers & Mathematics with Applications
Software quality assurance using software reliability growth modelling: state of the art
International Journal of Business Information Systems
An approach for early prediction of software reliability
ACM SIGSOFT Software Engineering Notes
A history-based cost-cognizant test case prioritization technique in regression testing
Journal of Systems and Software
Hi-index | 0.00 |
In this paper, a scheme for constructing software reliability growth model based on Non-Homogeneous Poisson Process is proposed. The main focus is to provide a method for software reliability modeling, which considers both testing-effort and change-point. In the vast literature, most researchers assume a constant detection rate per fault in deriving their software reliability models. They suppose that all faults have equal probability of being detected during the software testing process, and the rate remains constant over the intervals between fault occurrences. In reality, the fault detection rate strongly depends on the skill of test teams, program size, and software testability. Therefore, it may not be smooth and can be changed. On the other hand, sometimes we have to detect more additional faults in order to reach the desired reliability objective during testing. It is advisable for project managers to purchase new automated test tool, technology or additional manpower. These approaches can provide a conspicuous improvement in software testing and productivity. In this case, the fault detection rate will be changed during the software development process. Therefore, here we incorporate both generalized logistic testing-effort function and change-point parameter into software reliability modeling. New theorems are proposed and software testing data collected from real application are utilized to illustrate the proposed model. Experimental results show that the proposed framework to incorporate both testing-effort and change-point for SRGM has a fairly accurate prediction capability.