All Eyes on the Reviewer: Understanding the Impact of GenAI on Mental Workload and Performance in Code Reviews

In order to achieve high-quality software, organizations use code reviews as an established quality assurance instrument in software development. With GenAI, organizations get the possibility to improve the time-consuming and cognitively demanding process of code review by assisting code reviewers with defect and improvement suggestions. As tools to support software development become more widely adopted, our research investigates the scenarios in which GenAI support helps reviewers perform better and addresses the relevance of mental workload in code reviews. As a result of our online experiment with 123 software developers, we can show that GenAI-assistance increases performance efficiency and effectiveness while decreasing the mental workload of reviewers when complex code is reviewed. This indicates that not only performance but also the human factor is important in the utilization of GenAI and the complexity of tasks should be considered.

Publication Details

Journal
TUbilio (Technical University of Darmstadt)
Published
2024-12-15
Primary Topic
Software Engineering Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

All Eyes on the Reviewer: Understanding the Impact of GenAI on Mental Workload and Performance in Code Reviews

TUbilio (Technical University of Darmstadt)
Software Engineering Research
article

All Eyes on the Reviewer: Understanding the Impact of GenAI on Mental Workload and Performance in Code Reviews

article en

Abstract

In order to achieve high-quality software, organizations use code reviews as an established quality assurance instrument in software development. With GenAI, organizations get the possibility to improve the time-consuming and cognitively demanding process of code review by assisting code reviewers with defect and improvement suggestions. As tools to support software development become more widely adopted, our research investigates the scenarios in which GenAI support helps reviewers perform better and addresses the relevance of mental workload in code reviews. As a result of our online experiment with 123 software developers, we can show that GenAI-assistance increases performance efficiency and effectiveness while decreasing the mental workload of reviewers when complex code is reviewed. This indicates that not only performance but also the human factor is important in the utilization of GenAI and the complexity of tasks should be considered.

TUbilio (Technical University of Darmstadt)
Industry, innovation and infrastructure
Openalex Percentile: Top 32%
Software Engineering Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

All Eyes on the Reviewer: Understanding the Impact of GenAI on Mental Workload and Performance in Code Reviews · TUbilio (Technical University of Darmstadt) (2024) | TGRS Research Map | TGRS