Asian Journal of Information Technology
ISSN: Online 1993-5994ISSN: Print 1682-3915
Abstract
Software is directly a key part of many safety-critical and life-critical function systems. People consistently need easy- and instinctive-to-use software but the colossal challenge for software engineers is how to advance software with high accuracy in a appropriate manner in a appropriate manner. To assure quality and to assess the authenticity of software products, many Software Reliability advance Models (SRGMs) have been expected in the past three decades. The constructive problem is that consistently these selected SRGMs by association or software professional disagree in their reliability forecast while no single exemplary can be trusted to administer consistently accurate results across assorted applications. Consequently, some investigator have expected to use combinational models for develop the prediction capability of operating system reliability. In this study, appreciate weighted-combination, namely adequate arithmetic combination are expected. To solve the dilemma of determining proper burden for model combinations, we farther study how to assimilate Enhanced Genetic conclusion (EGAs) with several efficient engineer into weighted assignments. analysis are performed based on absolute software breakdown data and numerical conclusion show that our expected models are malleable enough to depict assorted software development climate. Finally, some administration metrics are conferred to both assure software aspect and complete the optimal release approach of software amount under development.
How to cite this article:
G. Nandini and G. Sridevi. An Novel Approach On Software Reliability Growth Modelin Using the Data Mining Techniques.
DOI: https://doi.org/10.36478/ajit.2016.3556.3561
URL: https://www.makhillpublications.co/view-article/1682-3915/ajit.2016.3556.3561