A 2030 Roadmap for Software Engineering
Artikel i vetenskaplig tidskrift, 2025

The landscape of software engineering has dramatically changed in recent years. The impressive advances of artificial intelligence are just the latest and most disruptive innovation that has remarkably changed the software engineering research and practice. This special issue shares a roadmap to guide the software engineering community in this confused era. This roadmap is the outcome of a 2-day intensive discussion at the 2030 Software Engineering workshop. The roadmap spotlights and discusses seven main landmarks in the new software engineering landscape: artificial intelligence for software engineering, human aspects of software engineering, software security, verification and validation, sustainable software engineering, automatic programming, and quantum software engineering. This editorial summarizes the core aspects discussed in the 37 papers that comprise the seven sections of the special issue and guides the interested readers throughout the issue. This roadmap is a living body that we will refine with follow-up workshops that will update the roadmap for a series of forthcoming ACM TOSEM special issues.

Sustainable software engineering

AI for verification and validation

security and software engineering

Automatic Programming

A roadmap for software engineering

Human factor in software engineering

AI and software engineering

Quantum software engineering

Large language models for software engineering

generative AI for software engineering

Författare

Mauro Pezzè

Universita' degli Studi di Milano-Bicocca

Constructor Institute

Universita della Svizzera italiana

Silvia Abrahao

Universitat Politecnica de Valencia (UPV)

Birgit Penzenstadler

Göteborgs universitet

Chalmers, Data- och informationsteknik, Interaktionsdesign och Software Engineering

Denys Poshyvanyk

College of William and Mary

Abhik Roychoudhury

Universiti Kebangsaan Singapura (NUS)

Tao Yue

Beihang University

ACM Transactions on Software Engineering and Methodology

1049-331X (ISSN) 15577392 (eISSN)

Vol. 34 5 118

Ämneskategorier (SSIF 2025)

Programvaruteknik

DOI

10.1145/3731559

Mer information

Senast uppdaterat

2025-06-19