Genetic Programming for Software Evolution: a Novel Lifecycle Approach

EasyChair Preprint no. 13100

Abstract

This study proposes a novel software development lifecycle (SDLC) approach based on genetic programming (GP) principles. It explores how GP algorithms can facilitate software evolution, adaptation, and optimization over successive generations. Through a combination of theoretical analysis and practical experimentation, the research evaluates the feasibility and effectiveness of GP-based SDLC models. It aims to provide insights into harnessing evolutionary mechanisms for improving software quality and performance.

Keyphrases: feasibility analysis, Genetic Programming, Lifecycle Approach, Optimization, software evolution

@Booklet{EasyChair:13100,
  author = {Takara Nakai and Wahaj Ahmed},
  title = {Genetic Programming for Software Evolution: a Novel Lifecycle Approach},
  howpublished = {EasyChair Preprint no. 13100},

  year = {EasyChair, 2024}}