Improved EM algorithm in software reliability growth models. (7th September 2020)

• Record Type: Journal Article
• Authors: Sudharson, D.; Prabha, D.
• Is Part Of: International journal of powertrains. Volume 9:Number 3(2020)
• Page Start: 186
• Page End: 199
• Publication Date: 2020-09-07
• Subjects: fault identification -- EM algorithm -- k-means algorithm -- Gaussian function; Motor vehicles -- Power trains -- Periodicals; 629.25
• Languages: English
• ISSNs: 1742-4267

Abstract

The important issue in software reliability management includes evaluation, measurement and prediction about errors in the model. In critical applications the requirement of software reliability is considered as important issues as the low reliability decreases the application performance. Several factors that affects the reliability such as consistency, test coverage, complexity, operational realism, etc. In this complexity leads to faults in the model as it is also related to reliability so that once we start to develop and design the application complexity must take into an account. In delivering some high reliability software products these above factors must be included so that the expectation about product to the user community increases. This research work describes about an efficient model for identifying the faults in the software products using improved EM algorithm using Gaussian function. The improved EM function includes k-means algorithm together to perform the task.