Analysis of a Software Reliability Growth Model with Logistic Testing-Effort Function
ISSRE '97 Proceedings of the Eighth International Symposium on Software Reliability Engineering
Accounting for Realities When Estimating the Field Failure Rate of Software
ISSRE '01 Proceedings of the 12th International Symposium on Software Reliability Engineering
A Software Cost Model for Quantifying the Gain with Considerations of Random Field Environments
IEEE Transactions on Computers
Some successful approaches to software reliability modeling in industry
Journal of Systems and Software - Special issue: Automated component-based software engineering
Software error detection model with applications
Journal of Systems and Software
Anisotropic Laplace trend to enhance software reliability growth modelling
MOAS'07 Proceedings of the 18th conference on Proceedings of the 18th IASTED International Conference: modelling and simulation
Mining software repositories for comprehensible software fault prediction models
Journal of Systems and Software
Evaluation of software development projects using a fuzzy multi-criteria decision approach
Mathematics and Computers in Simulation
Journal of Systems and Software
Considering environmental function in reliability growth modeling from testing to operation
SEA '07 Proceedings of the 11th IASTED International Conference on Software Engineering and Applications
Quasi-renewal time-delay fault-removal consideration in software reliability modeling
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans - Special section: Best papers from the 2007 biometrics: Theory, applications, and systems (BTAS 07) conference
Anisotropic Laplace trend to enhance software reliability growth modelling
MS '07 The 18th IASTED International Conference on Modelling and Simulation
Information Sciences: an International Journal
A multi-risks group evaluation method for the informatization project under linguistic environment
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Hi-index | 0.00 |
For both in-house development and outsourcing development environments, knowing the field failure rate of an integrated software system prior to field deployment provides guidance for better decision-makings in balancing reliability, time-to-market and development cost. This paper demonstrates a field failure rate prediction methodology that starts with analyzing system test data and field data (of previous releases or products) using software reliability growth models (SRGMs). A typical issue associated with predicting field failure rate based on test data is that potentially the test environment might not match exactly up the field environment. We discuss how to address the mismatch of the operational profiles of the test and filed environments. Two other practical issues in predicting field failure rates include that fault removals in the field are usually non-instantaneous and fixes of certain faults reported in the field can be deferred. Non-instantaneous fault removal and fault fix deferral becomes more realistic as the current software development environment shifts to a new trend of leveraging third-party, off-the-shelf, and semi-custom hardware and software and having the suppliers focus on development of highest-value applications and system integration. In such an environment, removing a fault might require a longer time and fix deferrals of certain faults becomes more possible in particular for the faults whose fixes will result in changes to other software components. In this paper, we illustrate how to incorporate these issues into field failure rate prediction. Confidence intervals of the predicted failure rate are also included to account for variations in the parameter estimation. Sensitivity analyses are conducted to estimate the uncertainties in the field failure rate prediction.