COPE: Recovering Long-Horizon Coding Tasks through Compression of Pull-Request Evolution

Repository-level coding tasks are commonly derived from historical development artifacts such as issues and pull-requests (PRs). However, such artifact boundaries reflect development workflow rather than the semantic boundaries of functionality, such that the resulting tasks often capture only fragments of a feature's complete behavioral contract. We introduce **COPE** (**C**ompression **O**f **P**ull-request **E**volution), a framework that treats PR evolution history as evidence for task construction rather than as a sequence to reproduce. COPE first identifies semantically related, possibly non-contiguous PRs that shape the same functionality. It then recovers the behavioral specification revealed across their evolution and poses it as a single executable task at an earlier repository state. Each task thus compresses requirements that emerged over multiple development stages into a longer semantic horizon, aligning with semantic boundaries of true software functionality. Using COPE, we construct 24,000 long-horizon coding tasks spanning 14,868 repositories and obtain 4,478 execution-verified trajectories as a training pool. Under the same training-token budget, models trained with COPE supervision outperform those trained with single-PR and other long-horizon supervision on representative software engineering benchmarks. In particular, with only 384 trajectories, COPE PR-Tree yields relative improvements of 21.3% on SWE-Bench Verified and 33.3% on SWE-Bench Multilingual over the base model. The COPE tasks and code will be made publicly available.