Loreley: Repository-Scale Program Evolution with Quality-Diversity Search

TL;DR - Loreley applies quality-diversity search to repository-scale software evolution by retaining and reusing complete Git states rather than following one edit sequence or repeatedly restarting. It successfully preserved stepping-stone branches, but did not demonstrate better final performance within a 48-job budget.

• Candidates are Git commits created in isolated worktrees and scored by a project-defined evaluator.
• A controlled Zstandard experiment evaluated 1,008 candidates across Loreley, sequential champion editing, and independent root proposals.
• At 48 jobs, Loreley scored 0.135% below sequential editing and 0.320% above independent proposals; neither comparison established a QD advantage.
• Non-incumbent states contributed to four of seven final Loreley winners by primary-parent ancestry, showing that archive reuse occurred even without a proven endpoint benefit.