# A Roadmap on Modern Code Review: Challenges and Opportunities

arXiv: https://arxiv.org/abs/2405.18216 · HTML: https://mlsanity.com/paper/2405.18216/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 28 May 2024.

## Built on by (most cited first, 3 of 3)

- [Combining Large Language Models with Static Analyzers for Code Review Generation](https://mlsanity.com/paper/2502.06633/) (2025)
- [Previously on... Automating Code Review](https://mlsanity.com/paper/2508.18003/) (2025)
- [Using Agentic AI for contextualized and multifaceted code review at Ericsson](https://mlsanity.com/paper/2609.15877/) (2026)

## Abstract (arXiv)

Over the past decade, modern code review (MCR) has been established as a cornerstone of software quality assurance and a vital channel for knowledge transfer within development teams. However, the manual inspection of increasingly complex systems remains a cognitively demanding and resource-intensive activity, often leading to significant workflow bottlenecks. This paper presents a comprehensive roadmap for the evolution of MCR, consolidating over a decade of research (2013-2025) into a unified taxonomy comprising improvement techniques, which focus on the technical optimization and automation of downstream review tasks, and understanding studies, which investigate the underlying socio-technical mechanisms and empirical phenomena of the review process. By diagnosing the current landscape through a strategic SWOT analysis, we examine the transformative impact of generative AI and identify critical gaps between burgeoning AI capabilities and industrial realities. We envision a future where MCR evolves from a human-driven task into a symbiotic partnership between developers and intelligent systems. Our roadmap charts this course by proposing three pivotal paradigm shifts, Context-Aware Proactivity, Value-Driven Evaluation, and Human-Centric Symbiosis, aiming to guide researchers and practitioners in transforming MCR into an intelligent, inclusive, and strategic asset for the AI-driven future.