Work

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

Year: 2025

Type: article

Abstract: 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.

Source: IEEE Access

DOI: 10.1109/access.2025.3574462

Authors: Usman Khan Durrani, Mustafa Akpinar, Hakan Bektas, Mohammed Saleh

Institutions: Higher Colleges of Technology, Istanbul University

Language: English

Topic: Software Engineering Techniques and Practices

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $2,075