CodeNib: A Multi-View Data System for Serving Repository Context to Coding Agents

• URL: http://arxiv.org/abs/2607.25431v1
• Date: Tue, 28 Jul 2026 08:25:30 GMT
• Title: CodeNib: A Multi-View Data System for Serving Repository Context to Coding Agents
• Abstract summary: Coding agents repeatedly search, navigate, and retain context from evolving repositories.<n> disconnected indexes, language servers, and task-local histories force repeated discovery and obscure lifecycle costs.<n>CodeNib builds reusable lexical, dense, and structural views per repository commit.
• Score: 5.400196370175265
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Coding agents repeatedly search, navigate, and retain context from evolving repositories, but disconnected indexes, language servers, and task-local histories force repeated discovery and obscure lifecycle costs. CodeNib builds reusable lexical, dense, and structural views per repository commit, maps outputs to repository-relative source ranges, maintains selected views across edits, and serves ranked search, symbol navigation, and bounded context through one runtime. Across 100 snapshots, we map quality-cost frontiers across the repository-context lifecycle. When outputs match an independent rebuild, graph and vector updates are $8.7\times$ and $25.4\times$ faster at the median. On the static-navigation subset matching normalized live-server locations (63% of 1,000 requests), the median per-request live/static latency ratio is $4.7\times$. Across five models, selected context policies preserve localization with 50--87% fewer trajectory tokens than paired grep/read. Together, these results support multi-view repository-context serving with explicit, operation-specific validity boundaries.

Related papers

• RepoAtlas: Guiding Coding Agents via Evolving Multimodal Repository Views [14.618487825419328]
  We present textbfRepoAtlas, a training-free module that maintains evolving multimodal repository views.<n>RepoAtlas combines evidence from the issue with the agent's current exploration state to select a task-relevant region under a fixed budget.<n>We evaluate RepoAtlas on SWE-bench Verified, where it improves the resolve rate by 2.4 points while reducing input tokens and model calls by 5.8% and 7.8% on average.
  arXiv  Detail & Related papers  (2026-09-15T10:11:51Z)
• Beyond Repository Boundaries: Cross-Repository Graph Retrieval for Code Generation [15.95046921483187]
  CrossCoder is a cross-repository code generation framework that explicitly incorporates external libraries into the retrieval context.<n>We show that CrossCoder consistently improves both functional correctness (up to 6.3% on pass@1) and robustness to dependency-version changes.
  arXiv  Detail & Related papers  (2026-09-09T10:14:14Z)
• Terminal-Universe: Turning Agent Trajectories into Scalable Terminal Environments [89.86581796261123]
  We introduce Terminal-Universe, a framework which turns each trajectory into a reusable environment.<n>Terminal-Universe replays the file operations recorded in a trajectory to restore each file before the agent modified it, yielding a partial workspace.<n>We also scale the tasks along two axes: breadth and depth.
  arXiv  Detail & Related papers  (2026-09-03T17:41:05Z)
• Adaptive Critical Token-Aware Retrieval for Repository-Level Code Generation [53.85136813868056]
  ACToR is an adaptive critical token-aware retrieval framework for repository-level code generation.<n>We show that ACToR consistently outperforms state-of-the-art methods on repository-level benchmarks.
  arXiv  Detail & Related papers  (2026-09-01T17:59:39Z)
• OctoLong: Mid-Training On Cross-Repository Code Contexts Enhances Long-Context Modeling [48.07406452417886]
  Existing long-context corpora are dominated by books, academic articles, and code repositories.<n>We introduce OctoLong, a context engineering pipeline that instruments an AST, a language server backend, and a package manager.<n>We train OctoLong-Instruct, a suite of capable long-context open LMs, derived from base models ranging in size from 600M to 14B parameters.<n>Our training ablations and experimental evaluations against 18 state-of-the-art open-weight long-context LMs show that supplanting just 12% of traditional context-extension corpora with OctoLong data yields substantial gains
  arXiv  Detail & Related papers  (2026-08-05T17:58:15Z)
• FastContext: Training Efficient Repository Explorer for Coding Agents [29.359764163872473]
  Large Language Model (LLM) coding agents have achieved strong results on software engineering tasks.<n> repository exploration remains a major bottleneck: locating relevant code consumes substantial token budget and pollutes the agent's context with irrelevant snippets.<n>We present FastContext, a dedicated exploration subagent that separates repository exploration from solving.
  arXiv  Detail & Related papers  (2026-06-12T03:23:59Z)
• Rethinking RAG in Long Videos: What to Retrieve and How to Use It? [56.38819694781005]
  We introduce V-RAGBench, a benchmark of $langle$query, evidence chunk, answer$rangle$ triplets that enables faithful, decoupled evaluation of retrieval and generation.<n>We also present CARVE, a method that runs parallel retrievers across configurations and employs chunk-adaptive reranking to identify the winning configuration for each chunk.
  arXiv  Detail & Related papers  (2026-06-11T10:05:49Z)
• LARGER: Lexically Anchored Repository Graph Exploration and Retrieval [9.90137784523552]
  repository-level coding agents must first localize the files and symbols relevant to a task.<n>Existing approaches often require separate graph tools or stages that fragment the agent's interaction loop.<n>We introduce LARGER, a lexically anchored active-set retrieval framework that starts from lexical matches, aligns them to graph anchors, and performs confidence-filtered local expansion within the agent's existing search loop.
  arXiv  Detail & Related papers  (2026-05-08T05:03:46Z)
• ClawMark: A Living-World Benchmark for Multi-Turn, Multi-Day, Multimodal Coworker Agents [77.22389710754452]
  We introduce bench, a benchmark for coworker agents built around multi-turn multi-day tasks.<n>The current release contains 100 tasks across 13 professional scenarios, executed against five stateful sandboxed services.<n>The strongest model reaches 75.8 weighted score, but the best strict Task Success is only 20.0%, indicating that partial progress is common.
  arXiv  Detail & Related papers  (2026-04-26T16:05:02Z)
• Repository Intelligence Graph: Deterministic Architectural Map for LLM Code Assistants [0.0]
  Repository aware coding agents often struggle to recover build and test structure.<n>We introduce the Repository Intelligence Graph (RIG), a deterministic, evidence backed architectural map that represents buildable components, aggregators, runners, tests, external packages, and package managers.<n>We evaluate three commercial agents (Claude Code, Cursor, Codex) on eight repositories spanning low to high build complexity, including the real world MetaFFI project.
  arXiv  Detail & Related papers  (2026-01-15T06:42:45Z)
• VLM2GeoVec: Toward Universal Multimodal Embeddings for Remote Sensing [59.73939718087177]
  Single-encoder vision-language model trained contrastively to embed interleaved inputs in a unified vector space.<n>VLM2GeoVec unifies scalable retrieval with region-level spatial reasoning, enabling cohesive multimodal analysis in remote sensing.
  arXiv  Detail & Related papers  (2025-12-12T11:39:35Z)
• MutaGReP: Execution-Free Repository-Grounded Plan Search for Code-Use [92.28400093066212]
  MutaGReP is an approach to search for plans that decompose a user request into natural language steps grounded in a large code repository.<n>Our plans use less than 5% of the 128K context window for GPT-4o but rival the coding performance of GPT-4o with a context window filled with the repo.
  arXiv  Detail & Related papers  (2025-02-21T18:58:17Z)
• Repository-level Code Search with Neural Retrieval Methods [25.222964965449286]
  We define the task of repository-level code search as retrieving the set of files from the current state of a code repository that are most relevant to addressing a user's question or bug.<n>The proposed approach combines BM25-based retrieval over commit messages with neural reranking using CodeBERT to identify the most pertinent files.<n> Experiments on a new dataset created from 7 popular open-source repositories demonstrate substantial improvements of up to 80% in MAP, MRR and P@1 over the BM25 baseline.
  arXiv  Detail & Related papers  (2025-02-10T21:59:01Z)
• Long Code Arena: a Set of Benchmarks for Long-Context Code Models [75.70507534322336]
  Long Code Arena is a suite of six benchmarks for code processing tasks that require project-wide context. These tasks cover different aspects of code processing: library-based code generation, CI builds repair, project-level code completion, commit message generation, bug localization, and module summarization. For each task, we provide a manually verified dataset for testing, an evaluation suite, and open-source baseline solutions.
  arXiv  Detail & Related papers  (2024-06-17T14:58:29Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.