Beyond Isolated Tasks: A Framework for Evaluating Coding Agents on Sequential Software Evolution
This work addresses the need for more realistic evaluation of coding agents in software engineering, though it is incremental as it builds on existing datasets by adding sequential and health-focused metrics.
The authors tackled the problem that existing coding agent evaluations focus on isolated tasks, which inflates success rates by up to 20 percentage points compared to real-world sequential software development, and found that agents degrade repository health by generating code with higher cognitive complexity and technical debt.
Existing datasets for coding agents evaluate performance on isolated, single pull request (PR) tasks in a stateless manner, failing to capture the reality of real-world software development where code changes accumulate, technical debt accrues, and test suites grow over time. To bridge this gap, we introduce an automated coding task generation framework, which helps generate our dataset SWE-STEPS, that evaluates coding agents on long-horizon tasks through two realistic settings mirroring actual developer workflows: Conversational coding with iterative requests, and single-shot Project Requirement document (PRD)-based coding. Unlike existing datasets that evaluate agents on disjointed Pull Requests (PRs), our framework assesses performance across chains of dependent PRs, enabling evaluation of sequential execution, regression verification, and long-term repository health. We discover that widely used isolated PR evaluations yield inflated success rates, w.r.t. our settings - overshooting performance by as much as 20 percentage points - because they ignore the ``spillover'' effects of previous inefficient or buggy code. Furthermore, our analysis reveals that even when agents successfully resolve issues, they degrade repository health by generating code with higher cognitive complexity and technical debt compared to human developers, underscoring the necessity for multidimensional evaluation.