ACE: Automated Technical Debt Remediation with Validated Large Language Model Refactorings

The remarkable advances in AI and Large Language Models (LLMs) have enabled machines to write code, accelerating the growth of software systems. However, the bottleneck in software development is not writing code but understanding it; program understanding is the dominant activity, consuming approximately 70% of developers' time. This implies that improving existing code to make it easier to understand has a high payoff and - in the age of AI-assisted coding - is an essential activity to ensure that a limited pool of developers can keep up with ever-growing codebases.

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Publication Details

Published
2025-06-23
DOI
https://doi.org/10.1145/3696630.3730565
Primary Topic
Software Engineering Research
Type
article
Field-Weighted Citation Impact
0.00

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article

ACE: Automated Technical Debt Remediation with Validated Large Language Model Refactorings

Emma Söderberg, Markus Borg, Adam Tornhill, Nadim Hagatulah
Software Engineering Research
article

ACE: Automated Technical Debt Remediation with Validated Large Language Model Refactorings

Emma Söderberg, Markus Borg, Adam Tornhill, Nadim Hagatulah
article en

Abstract

The remarkable advances in AI and Large Language Models (LLMs) have enabled machines to write code, accelerating the growth of software systems. However, the bottleneck in software development is not writing code but understanding it; program understanding is the dominant activity, consuming approximately 70% of developers' time. This implies that improving existing code to make it easier to understand has a high payoff and - in the age of AI-assisted coding - is an essential activity to ensure that a limited pool of developers can keep up with ever-growing codebases.

Lund University (SE)
VINNOVA
Openalex Percentile: Top 73%
Software Engineering Research
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