Impact of Artificial Intelligence on Software Engineering Phases and Activities (2013-2024): A Quantitative Analysis Using Zero-Truncated Poisson Model

Durrani U. K., Akpinar M., BEKTAŞ H., Saleh M.

IEEE Access, cilt.13, ss.95535-95547, 2025 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 13
  • Basım Tarihi: 2025
  • Doi Numarası: 10.1109/access.2025.3574462
  • Dergi Adı: IEEE Access
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, INSPEC, Directory of Open Access Journals
  • Sayfa Sayıları: ss.95535-95547
  • Anahtar Kelimeler: AI, artificial intelligence, deep learning, expert systems, integration, machine learning, natural language processing, optimization algorithms, planning, quantitative analysis, requirement engineering, software deployment, software development, software engineering, software maintenance, software testing, zero-truncated Poisson model
  • İstanbul Üniversitesi Adresli: Evet

Özet

This paper presents the results of a quantitative analysis derived from data collected in our earlier systematic literature review, focusing on integrating Artificial Intelligence (AI) techniques across various phases of Software Engineering (SE). Employing a Zero-Truncated Poisson (ZTP) model, we analyzed 120 selected research papers to assess the impact of AI methodologies on SE phases. The findings indicate significant improvements attributable to AI in different phases of SE. Specifically, AI techniques have been found to enhance the accuracy of the planning, requirement engineering, and development phases and improve the efficiency of the requirement engineering and design phases. Notably, AI's integration has markedly improved the accuracy and efficiency of the requirement engineering phase, underscoring AI's critical role in advancing SE practices. This study contributes to a deeper understanding of the quantitative impact of AI on SE, providing valuable insights for practitioners and researchers in understanding AI technologies to enhance SE phases.