Predictive Analytics and Decision Support Systems in Software Development: a New Paradigm for SDLC Model Development

EasyChair Preprint no. 12856

Abstract

Predictive analytics and decision support systems (DSS) are revolutionizing the landscape of software development by offering advanced capabilities for forecasting project outcomes, optimizing resource allocation, and facilitating data-driven decision-making throughout the Software Development Life Cycle (SDLC). This research paper explores the integration of predictive analytics and DSS into SDLC model development, aiming to enhance project management practices, mitigate risks, and improve overall project success rates. Through a comprehensive review of existing literature, case studies, and practical insights, this paper elucidates the potential benefits, challenges, and future directions of leveraging predictive analytics and DSS in software development processes. By embracing this new paradigm, organizations can unlock greater efficiency, agility, and innovation in their software projects.

Keyphrases: data-driven decision making, Decision Support Systems, Predictive Analytics, project management, SDLC Models, software development

@Booklet{EasyChair:12856,
  author = {Wahaj Ahmed and Takara Nakai},
  title = {Predictive Analytics and Decision Support Systems in Software Development: a New Paradigm for SDLC Model Development},
  howpublished = {EasyChair Preprint no. 12856},

  year = {EasyChair, 2024}}