Sunday 1 January 2017

Fault Prediction Techniques using DMM and GGA

Vol. 9  Issue 1
Year:2014
Issue:Jul-Sep
Title:Fault Prediction Techniques using DMM and GGA
Author Name:P. Patchaiammal and R. Thirumalaiselvi
Synopsis:
Software Engineering has new methodologies, technologies, applications and processes. Machine learning involves computer programming solutions that are experienced based learning to improve performance at some task. The overlap between machine learning and software engineering has seen the development of machine learning application to address various problems in software engineering. Faults in software engineering systems are major problems that need to be resolved. Fault prediction in software is significant because it can help in directing test effort, reducing cost, and increasing the quality of software and its reliability. In this study, the authors have analyzed various fault prediction techniques and proposed a new model named DMM (Decision Making Model) based on decision logic to develop the prediction hypothesis by introducing a new algorithm called GGA (Genetic Gain Algorithm) for fault prediction.

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