Engineering Confidence: AI-Ready, Evidence-Driven, Human-Centered Software

The Software Engineering Research Lab (SERL) at Blekinge Institute of Technology studies how modern software is actually built - and how to make that work safer, faster, and more learnable. Two complementary directions anchor SERL's research portfolio: using AI to improve software engineering activities, and engineering AI-intensive systems so they are dependable in production. The portfolio blends methods, tools, and organizational practices into an operable whole that scales from startups to large, hybrid organizations.

Edited by: Prof. Tony Gorschek

Artificial Intelligence and Software Engineering

AI-assisted workflows shaping software development outcomes and collaboration.

Edited by: Prof. Nauman bin Ali

Engineering Practices

Consolidated insights on practical engineering workflows and delivery quality improvements.

Edited by: Dr. Eriks Klotins

Quality

Measurable software quality practices across reviews, testing, and technical debt.

Edited by: Prof. Jürgen Börstler

Requirements Engineering

Requirements engineering methods for quality, traceability, and compliance-aware delivery.

Edited by: Prof. Daniel Mendez

Research methodologies

Research methodology advances that strengthen quality, reproducibility, and ethical empirical practice.

Edited by: Dr. Davide Fucci

Security

Security and privacy become continuous, measurable delivery practices without slowing teams.

Edited by: Dr. Oleksandr Adamov

Testing

Practical, AI-assisted, risk-guided testing helps teams deliver faster, more reliable software.

Edited by: Dr. Emil Alegroth

Ways of Working

Hybrid software teams perform best when flexible work is backed by clear alignment, trust, and scalable coordination.

Edited by: Prof. Darja Smite