mlsanityData to 14 Oct 2026

Automated Code Review Using Large Language Models at Ericsson: An Experience Report

arXiv 2507.19115 ↗First posted 25 Jul 2025cs.SE cs.AIcited by 5

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Abstract (arXiv)

Code review is one of the primary means of assuring the quality of released software along with testing and static analysis. However, code review requires experienced developers who may not always have the time to perform an in-depth review of code. Thus, automating code review can help alleviate the cognitive burden on experienced software developers allowing them to focus on their primary activities of writing code to add new features and fix bugs. In this paper, we describe our experience in using Large Language Models towards automating the code review process in Ericsson. We describe the development of a lightweight tool using LLMs and static program analysis. We then describe our preliminary experiments with experienced developers in evaluating our code review tool and the encouraging results.

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 4 of its 13 references that are in the map. First posted on arXiv 25 Jul 2025.

Builds on

4 of 13 references.

References · 4

  1. 2023Large Language Models for Code Analysis: Do LLMs Really Do Their Job?cited by 45
  2. 2024A Survey on Evaluating Large Language Models in Code Generation Taskscited by 44
  3. 2024Fine-Tuning and Prompt Engineering for Large Language Models-based Code Review Automationcited by 23
  4. 2024AI-powered Code Review with LLMs: Early Resultscited by 22

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 4.

5 papers.