activity
20112026
most citedGuiding Deep Learning System Testing using Surprise Adequacy

450 citations · 1.8k across the 77 of their papers we have counts for

collaborators
Showing 2025Show all

8 papers · 1 filter

cs.SE2025

Exploring the Garden of Forking Paths in Empirical Software Engineering Research: A Multiverse Analysis

Nathan Cassee, Robert Feldt

In empirical software engineering (SE) research, researchers have considerable freedom to decide how to process data, what operationalizations to use, and which statistical model t…

cs.SE2025

Tutorial Debriefing: Applied Statistical Causal Inference in Requirements Engineering

Julian Frattini, Hans-Martin Heyn, Robert Feldt +1

As any scientific discipline, the software engineering (SE) research community strives to contribute to the betterment of the target population of our research: software producers…

cs.SE2025

AI for Requirements Engineering: Industry adoption and Practitioner perspectives

Lekshmi Murali Rani, Richard Berntsson Svensson, Robert Feldt

The integration of AI for Requirements Engineering (RE) presents significant benefits but also poses real challenges. Although RE is fundamental to software engineering, limited re…

cs.SE2025★ 1 cited

The Factors Influencing Well-Being in Software Engineers: A Cross-Country Mixed-Method Study

Cristina Martinez Montes, Birgit Penzenstadler, Robert Feldt

The well-being of software engineers is increasingly under strain due to the high-stress nature of their roles, which involve complex problem-solving, tight deadlines, and the pres…

cs.SE2025

GateLens: A Reasoning-Enhanced LLM Agent for Automotive Software Release Analytics

Arsham Gholamzadeh Khoee, Shuai Wang, Robert Feldt +2

Ensuring reliable data-driven decisions is crucial in domains where analytical accuracy directly impacts safety, compliance, or operational outcomes. Decision support in such domai…

cs.SE2025★ 1 cited

Automating a Complete Software Test Process Using LLMs: An Automotive Case Study

Shuai Wang, Yinan Yu, Robert Feldt +1

Vehicle API testing verifies whether the interactions between a vehicle's internal systems and external applications meet expectations, ensuring that users can access and control v…

cs.SE2025

Adaptive Testing for LLM-Based Applications: A Diversity-based Approach

Juyeon Yoon, Robert Feldt, Shin Yoo

The recent surge of building software systems powered by Large Language Models (LLMs) has led to the development of various testing frameworks, primarily focused on treating prompt…

cs.SE2025★ 2 cited

An Empirical Study on Decision-Making Aspects in Responsible Software Engineering for AI

Lekshmi Murali Rani, Faezeh Mohammadi, Robert Feldt +1

Incorporating responsible practices into software engineering (SE) for AI is essential to ensure ethical principles, societal impact, and accountability remain at the forefront of…