A Redesigning Software Procedure in Improved Software Management using Machine Learning

Abstract

SPR is a software engineering process that improves organizational efficiency in responding to quality outcome challenges, change management and productivity improvement, product quality and competitive advantage. To include improvements to the required considerations and agreements of SEM, SPR, implements, inherits and explores the architecture of procedure change. Machine learning is a key part of SPR in software development organizations. The objective of this paper is to integrate automation technology such as ML into the SDLC of software product development and to increase the conceptual focus on its life cycle development and highlight ML methods in SPM, and how to execute ML in SEM methods. ML algorithms for empirical analysis and discussion of the specific performance and reuse of tasks that we have attempted to achieve in SEM. An observed study of software methods involves the control system of self determining software implementation. In the current period, ML gives better validity in few SEM areas. The main aim of this research is the practical as well as systematic study and also literature survey to advance the wanted standard software, between their qualified evaluation of existing procedures and their carry for SQE.