Ai-assisted assessment of coding practices in modern code review
M Vijayvergiya, M Salawa, I Budiselić… - Proceedings of the 1st …, 2024 - dl.acm.org
Modern code review is a process in which an incremental code contribution made by a code
author is reviewed by one or more peers before it is committed to the version control system …
author is reviewed by one or more peers before it is committed to the version control system …
How much does AI impact development speed? An enterprise-based randomized controlled trial
E Paradis, K Grey, Q Madison, D Nam… - arxiv preprint arxiv …, 2024 - arxiv.org
How much does AI assistance impact developer productivity? To date, the software
engineering literature has provided a range of answers, targeting a diversity of outcomes …
engineering literature has provided a range of answers, targeting a diversity of outcomes …
Software Security Analysis in 2030 and Beyond: A Research Roadmap
As our lives, our businesses, and indeed our world economy become increasingly reliant on
the secure operation of many interconnected software systems, the software engineering …
the secure operation of many interconnected software systems, the software engineering …
CRScore: Grounding Automated Evaluation of Code Review Comments in Code Claims and Smells
The task of automated code review has recently gained a lot of attention from the machine
learning community. However, current review comment evaluation metrics rely on …
learning community. However, current review comment evaluation metrics rely on …
Leveraging Reviewer Experience in Code Review Comment Generation
Modern code review is a ubiquitous software quality assurance process aimed at identifying
potential issues within newly written code. Despite its effectiveness, the process demands …
potential issues within newly written code. Despite its effectiveness, the process demands …
Too Noisy To Learn: Enhancing Data Quality for Code Review C
C Liu, HY Lin, P Thongtanunam - arxiv preprint arxiv:2502.02757, 2025 - arxiv.org
Code review is an important practice in software development, yet it is time-consuming and
requires substantial effort. While open-source datasets have been used to train neural …
requires substantial effort. While open-source datasets have been used to train neural …
Agentic Bug Reproduction for Effective Automated Program Repair at Google
R Cheng, M Tufano, J Cito, J Cambronero… - arxiv preprint arxiv …, 2025 - arxiv.org
Bug reports often lack sufficient detail for developers to reproduce and fix the underlying
defects. Bug Reproduction Tests (BRTs), tests that fail when the bug is present and pass …
defects. Bug Reproduction Tests (BRTs), tests that fail when the bug is present and pass …
CoDocBench: A Dataset for Code-Documentation Alignment in Software Maintenance
One of the central tasks in software maintenance is being able to understand and develop
code changes. Thus, given a natural language description of the desired new operation of a …
code changes. Thus, given a natural language description of the desired new operation of a …
Trust Calibration in IDEs: Paving the Way for Widespread Adoption of AI Refactoring
M Borg - arxiv preprint arxiv:2412.15948, 2024 - arxiv.org
In the software industry, the drive to add new features often overshadows the need to
improve existing code. Large Language Models (LLMs) offer a new approach to improving …
improve existing code. Large Language Models (LLMs) offer a new approach to improving …
How is Google using AI for internal code migrations?
S Nikolov, D Codecasa, A Sjovall, M Tabachnyk… - arxiv preprint arxiv …, 2025 - arxiv.org
In recent years, there has been a tremendous interest in using generative AI, and particularly
large language models (LLMs) in software engineering; indeed there are now several …
large language models (LLMs) in software engineering; indeed there are now several …