SWE-Craft: Graph-Guided Task Synthesis for Weak Spots in Coding Agents

Executable software engineering (SWE) tasks provide controlled environments for studying and improving coding agents. Existing perturbation-based synthesis scales task generation but offers limited control over the engineering practice represented in the resulting data. We study target-conditioned SWE task synthesis: a supplied capability target specifies desired model behavior or reasoning and guides task design before construction. In our experiments, model-assisted analysis and human synthesis of base-model trajectories motivate these targets. We introduce SWE- Craft, which uses a source-linked code property graph to explore functional modules across functions and files. A task design agent matches repository behavior to a capability target and specifies required and preserved behaviors. The task specification then guides separate construction and validation of executable bug- fixing, feature-addition, and feature-enhancement tasks. Quality-screened teacher trajectories provide supervision for fine-tuning. In a source-blinded LLM audit, SWE-Craft scores 93.16 out of 100 for alignment with a shared task profile, compared with 53.36 for SWE-smith and 42.67 for BugPilot. Fine-tuning Ling-3.0- flash on 1,500 trajectories achieves 46.88% and 68.00% Pass@1 on SWE-bench Pro and SWE-bench Multilingual, outperforming SWE-smith by 2.74 and 3.55 percentage points, and BugPilot by 2.05 and 3.00 points, respectively