Impact of Machine Learning on Software Development Life Cycle

被引：0

作者：

Navaei, Maryam ^{[1
]}

Tabrizi, Nasseh ^{[1
]}

机构：

[1] East Carolina Univ, Dept Comp Sci, East 5th St, Greenville, NC 27858 USA

来源：

PROCEEDINGS OF THE 18TH INTERNATIONAL CONFERENCE ON EVALUATION OF NOVEL APPROACHES TO SOFTWARE ENGINEERING, ENASE 2023 | 2023年

关键词：

Software Engineering; Software Development Life Cycle; Artificial Intelligence; Machine Learning; Machine Learning Algorithms;

D O I：

10.5220/0011997200003464

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

This research concludes an overall summary of the publications so far on the applied Machine Learning (ML) techniques in different phases of Software Development Life Cycle (SDLC) that includes Requirement Analysis, Design, Implementation, Testing, and Maintenance. We have performed a systematic review of the research studies published from 2015-2023 and revealed that Software Requirements Analysis phase has the least number of papers published; in contrast, Software Testing is the phase with the greatest number of papers published.

引用

页码：718 / 726

页数：9

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