| # Paper plan |
|
|
| Status: completed through E07. This file preserves the pre-execution plan; the |
| realized design, deviations, evidence inventory, and release gates are recorded |
| in `paper/main.tex` and `paper/reproducibility_manifest.md`. |
|
|
| ## Working title |
|
|
| **Beyond Grep: A Controlled Study of Repository-Navigation Harnesses for Local |
| LLM Coding Agents** |
|
|
| ## Candidate contribution |
|
|
| The paper should make a narrower, defensible claim than “better harnesses make |
| agents better.” The intended contribution is a controlled empirical |
| decomposition of navigation architecture—retrieval source, structural |
| expansion, interaction policy, tool interface, and context packing—under a |
| fixed local coding model on repositories larger than the model's usable |
| context. |
|
|
| Potential publishable outputs are: |
|
|
| 1. an open, immutable harness-treatment catalog with focused factorial blocks; |
| 2. paired evidence connecting localization quality to end-to-end repair; |
| 3. accuracy/latency/token trade-off curves rather than success alone; |
| 4. robustness results for stale indexes and plausible lexical distractors; and |
| 5. a reproducible local inference and telemetry protocol. |
|
|
| Novelty depends on the completed literature review and should not be asserted |
| until adjacent agent, code-retrieval, repository-level repair, and tool-use |
| benchmarks have been systematically compared. |
|
|
| ## Prespecified hypotheses |
|
|
| - H1: lexical, syntax, and dense retrieval each improve file recall over exact |
| search, but their effects are not purely additive. |
| - H2: one-hop graph expansion improves multi-file task localization; two hops |
| increase noise and cost more often than they improve resolution. |
| - H3: iterative querying improves hard-task localization but consumes more |
| tokens and wall time. |
| - H4: structural skeleton packing outperforms whole-file packing at small fixed |
| context budgets. |
| - H5: improved file/function recall mediates part, but not all, of the effect on |
| repair success. |
| - H6: adaptive routing can approach full-stack accuracy with lower retrieval |
| and context cost. |
|
|
| These hypotheses must be revised or preregistered before looking at the held-out |
| confirmatory results. |
|
|
| ## Manuscript structure |
|
|
| 1. **Abstract:** problem, controlled design, task/model scope, main effect sizes. |
| 2. **Introduction:** why context overflow turns navigation into a systems and |
| reasoning bottleneck; research questions and contributions. |
| 3. **Related work:** code search and embeddings, repository-level program |
| repair, LLM tool use, agent benchmarks, context selection, code graphs. |
| 4. **Method:** treatment dimensions, fixed model, task construction, execution |
| controls, metrics, and statistical analysis. |
| 5. **Experiments:** repository/task statistics, E01-E05, compute and local |
| serving details. |
| 6. **Results:** prespecified contrasts, confidence intervals, cost-quality |
| frontiers, subgroup and robustness analyses. |
| 7. **Discussion:** mechanisms, practical recommendations, failure cases, and |
| where complex harnesses do not pay for themselves. |
| 8. **Threats and ethics:** contamination, generalization, annotation quality, |
| local hardware/quantization effects, licensing, and energy/compute reporting. |
| 9. **Reproducibility statement:** configs, commits, prompts, manifests, raw event |
| schemas, analysis code, exclusions, and environment lockfiles. |
|
|
| ## Milestones and release gates |
|
|
| 1. Complete executable baseline H000 and validate task isolation. |
| 2. Select repositories and construct a clean development task set. |
| 3. Implement and unit-test retrieval sources, fusion, packing, and telemetry. |
| 4. Freeze embedding query/chunk policies, index profiles, model variant, prompts, and budgets. |
| 5. Run a small pilot; perform failure analysis and power simulation. |
| 6. Freeze protocol, task split, configs, analysis, and exclusion rules. |
| 7. Run confirmatory cells without treatment-specific intervention. |
| 8. Reproduce tables from raw artifacts, then write and internally audit the |
| paper. |
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|