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The success of the software system depends on many factors among which the selection of the most suitable Software development life cycle (SDLC) model is the significant one. SDLC represents a framework to develop a software system through planning, analysis, design, implementation, testing, deployment, and maintenance. These activities are carried out in different series of steps and depend on the context and characteristics of the software project. In this research, we proposed a system to analyze software charter documents to extract useful information using NLP techniques. Then the most suitable SDLC model will be recommended for software practitioners to carry out the development process by using machine learning algorithms. We have applied 11 machine learning algorithms and achieved the highest accuracy of 90.90% with Naïve Bayes algorithm.

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A Machine Learning Based Decision Support System for SDLC Model Selection Using Software Project Charter Documents

  • 会议论文

  • 发表日期：

    2026年

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  • Mahira Gul,
  • Yawar Abbas Bangash,
  • Khawir Mahmood,
  • Muhammed Basheer Jasser,
  • Ali Afzalian Mand

摘要

The success of the software system depends on many factors among which the selection of the most suitable Software development life cycle (SDLC) model is the significant one. SDLC represents a framework to develop a software system through planning, analysis, design, implementation, testing, deployment, and maintenance. These activities are carried out in different series of steps and depend on the context and characteristics of the software project. In this research, we proposed a system to analyze software charter documents to extract useful information using NLP techniques. Then the most suitable SDLC model will be recommended for software practitioners to carry out the development process by using machine learning algorithms. We have applied 11 machine learning algorithms and achieved the highest accuracy of 90.90% with Naïve Bayes algorithm.