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

arXiv: https://arxiv.org/abs/2507.19115 · HTML: https://mlsanity.com/paper/2507.19115/

## 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 (most cited first, 4 of 4)

- [Large Language Models for Code Analysis: Do LLMs Really Do Their Job?](https://mlsanity.com/paper/2310.12357/) (2023)
- [A Survey on Evaluating Large Language Models in Code Generation Tasks](https://mlsanity.com/paper/2408.16498/) (2024)
- [Fine-Tuning and Prompt Engineering for Large Language Models-based Code Review Automation](https://mlsanity.com/paper/2402.00905/) (2024)
- [AI-powered Code Review with LLMs: Early Results](https://mlsanity.com/paper/2404.18496/) (2024)

## Built on by (most cited first, 5 of 5)

- [Trust Me, I Know This Function: Hijacking LLM Static Analysis using Bias](https://mlsanity.com/paper/2508.17361/) (2025)
- [Needle in the Repo: A Benchmark for Maintainability in AI-Generated Repository Edits](https://mlsanity.com/paper/2603.27745/) (2026)
- [Agents with Feelings? Personality and Emotion in Multi-Agent Software Teams](https://mlsanity.com/paper/2607.05659/) (2026)
- [Using Agentic AI for contextualized and multifaceted code review at Ericsson](https://mlsanity.com/paper/2609.15877/) (2026)
- [Complexity-Aware Evaluation of LLM Comprehension](https://mlsanity.com/paper/2609.37405/) (2026)

## 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.