Quo Vadis, Code Review? Exploring the Future of Code Review

TL;DR

This paper surveys developers' expectations for the future of code review, highlighting increased automation with AI and LLMs, and discusses socio-technical challenges related to trust and accountability.

Contribution

It provides empirical insights into how professionals foresee automation transforming code review and identifies emerging tensions with AI integration.

Findings

Practitioners expect stable or increased review time over five years.

Many anticipate automation, AI, and LLMs will play larger roles in code review.

Emerging tensions include issues of understanding, accountability, and trust in automated review.

Abstract

Context: Code review has long been a core practice in collaborative software engineering. As automation becomes increasingly embedded in development workflows, the role and functioning of code review are subject to change. Objective: This study explores how professional developers anticipate the evolution of code review and identifies emerging tensions reflected in these expectations. Method: We conducted a cross-sectional survey with 100 developers across five software-driven companies. The survey captured estimates of current review time and reviewed artifacts, as well as anticipated changes over a five-year horizon. Open-ended questions invited reflections on the future of code review. Quantitative responses were analyzed descriptively, and open-ended responses were independently coded by multiple researchers using thematic analysis to identify recurring patterns in participant responses. Results: Practitioners expect code review to remain essential, anticipating stable or increased time investment and a broader range of reviewed artifacts over the next five years. In open-ended responses, many participants explicitly referenced AI and large language models (LLMs), describing increasing automation in both code authoring and reviewing, including scenarios in which automated systems operate in both roles. Conclusion: Our analysis suggests emerging tensions concerning understanding, accountability, and trust in automation-mediated code review. These tensions provide early empirical signals of socio-technical challenges and position code review as a concrete setting for examining the implications of LLM integration in collaborative software engineering.