Advanced Models for Software Reliability Prediction (2011)
Dr. Zigmund Bluvband, ALD Ltd., Israel
Dr. Sergey Porotsky, ALD Ltd., Israel
This article describes the advanced parametric models for assessment and prediction of software reliability, based on statistics of bugs at the initial stage of testing. The parametric model approach, commonly associated with reliability issues, deals with the evaluation of the amount of bugs in the code.
Computed parameter values inserted into the model allow to estimate:
(a) number of bugs remaining in the product,
(b) time required to detect the remaining bugs.
Many models are developed for similar purpose: Duane Reliability Growth Model, Goel Model, Weibull Model, Classical S-shaped Model, Ohba S-shaped Model, etc.
Computed parameter values inserted into the model allow to estimate:
(a) number of bugs remaining in the product,
(b) time required to detect the remaining bugs.
Many models are developed for similar purpose: Duane Reliability Growth Model, Goel Model, Weibull Model, Classical S-shaped Model, Ohba S-shaped Model, etc.