Theory software reliability its application

View on IEEE. Save to Library Save. Create Alert Alert. Share This Paper. Background Citations. Methods Citations. Results Citations. Figures, Tables, and Topics from this paper. Software reliability testing Mean time between failures Run time program lifecycle phase Scheduling computing Software development Software testing.

Citation Type. Has PDF. Publication Type. More Filters. Software reliability modeling: accounting for program size variation due to integration or design changes. Software reliability measurement. Reliability of Process Control Software. A coverage based model for software reliability estimation. Incorporating fault debugging activities into software reliability models: a simulation approach. View 1 excerpt, cites methods. Stochastic reliability growth: A model with applications to computer software faults and hardware design faults.

Evaluation Rev. Highly Influenced. View 6 excerpts, cites background. An assumption commonly made in early models of software reliability is that the failure rate of a program is a constant multiple of the number of faults remaining. This implies that all faults have … Expand. Skip to Main Content.

A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity. Use of this web site signifies your agreement to the terms and conditions. A theory of software reliability and its application Abstract: The theory permits the estimation, in advance of a project, of the amount of testing in terms of execution time required to achieve a specified reliability goal [stated as a mean time to failure MTTF ].

Execution time can then be related to calendar time, permitting a schedule to be developed. Estimates of execution time and calendar time remaining until the reliability goal is attained can be continually remade as testing proceeds, based only on the length of the execution time intervals between failures. The current MTTF and the number of errors remaining can also be estimated. Maximum likelihood estimation is employed, and confidence intervals are also established.