ReqToCode: Embedding Requirements Traceability as a Structural Property of the Codebase
- URL: http://arxiv.org/abs/2603.13999v1
- Date: Sat, 14 Mar 2026 16:00:09 GMT
- Title: ReqToCode: Embedding Requirements Traceability as a Structural Property of the Codebase
- Abstract summary: This paper introduces ReqToCode, an approach that prevents trace degradation by embedding traceable system elements directly into the system.<n>We describe the approach, its architectural principles, the Traceable lifecycle, and illustrate it with a generic example spanning requirement definition, artifact generation, code integration, and build-time validation.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Requirements traceability in safety-critical software development remains largely dependent on external documentation maintained separately from the systems it describes. This separation introduces structural fragility: traces degrade silently as requirements, code, and tests evolve independently across tools, repositories, and revisions. Recent advances in LLM-based traceability focus on recovering broken links after the fact - an inherently retrospective approach. This paper introduces ReqToCode, an approach that prevents trace degradation by embedding traceable system elements directly into the codebase, making traceability a compile-time verifiable property of the system rather than an external documentation task. Central to the approach is the concept of the Traceable - a language-native, generated code element that represents a single requirement and carries its metadata. Developers reference Traceables in implementation and test code, creating hard, bidirectional links that are validated automatically during the build process. When requirements change, the system responds through a graduated lifecycle - from deprecation warnings to build failures - providing teams with actionable signals rather than abrupt breakage. We describe the approach, its architectural principles, the Traceable lifecycle, and illustrate it with a generic example spanning requirement definition, artifact generation, code integration, and build-time validation.
Related papers
- 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) - Integration-First Structural Coverage for Embedded Software:Trace-Based Evidence, Hybrid Runtime Analysis, and Cross-Variant Consolidation [42.52742840006677]
We describe an integrationfirst coverage strategy that treats integration and system tests as the baseline measurement.<n>We also describe Hyper Coverage, a consolidation layer that merges evidence across test levels, test runs, variants and build configurations.
arXiv Detail & Related papers (2026-08-13T14:46:33Z) - Formal Verification of Agentic Systems over Operational Data [59.98246281888422]
Agentic systems driven by large language models (LLMs) are increasingly deployed in real-world where they act on persistent operational data.<n>Existing approaches do not provide such system-level guarantees.<n>We study here the verification of agentic systems comprising a single LLM and a tool orchestration harness over relational operational data.
arXiv Detail & Related papers (2026-08-04T13:01:30Z) - Securing LLM Agents Need Intent-to-Execution Integrity [49.490963596514185]
We argue that securing LLM agents requires defining an end-to-end correctness property that specifies when an agent's execution faithfully reflects the user's intent.<n>We observe that LLM agents are structurally analogous to compilers, where security violations correspond to mis-executions that do not preserve user intent.<n>We derive four integrity properties that must hold simultaneously: emphTool Integrity, emphInstruction Integrity, emphJudgment Integrity, and emphData Flow Integrity.
arXiv Detail & Related papers (2026-05-16T12:53:31Z) - DocSync: Agentic Documentation Maintenance via Critic-Guided Reflexion [0.0]
DocSync is an agentic workflow that frames documentation maintenance as a structurally grounded, iterative generation task.<n>We empirically evaluate a resource-constrained implementation of DocSync-using a LoRA-adapted small language model.<n>Our findings demonstrate that this AST-aware agentic approach substantially outperforms standard encoder-decoder baselines.
arXiv Detail & Related papers (2026-05-04T02:41:33Z) - ADEMA: A Knowledge-State Orchestration Architecture for Long-Horizon Knowledge Synthesis with LLMAgents [16.053669481561354]
ADEMA is a knowledge-state orchestration architecture for long-horizon knowledge synthesis.<n>This paper presents ADEMA as a knowledge-state orchestration architecture for long-horizon knowledge synthesis.
arXiv Detail & Related papers (2026-04-28T16:54:48Z) - CodeTracer: Towards Traceable Agent States [40.51936201889185]
We present CodeTracer, a tracing architecture that parses heterogeneous run artifacts through evolving extractors.<n>CodeTracer reconstructs the full state transition history as a hierarchical trace tree with persistent memory.<n>It performs failure onset localization to pinpoint the failure origin and its downstream chain.
arXiv Detail & Related papers (2026-04-13T15:52:03Z) - Understanding by Reconstruction: Reversing the Software Development Process for LLM Pretraining [66.89012795621349]
Large Language Models (LLMs) often struggle with the deep, long-horizon reasoning required for complex software engineering.<n>We propose a novel paradigm: understanding via reconstruction.<n>We introduce a framework that synthesizes latent agentic trajectories using a multi-agent simulation.
arXiv Detail & Related papers (2026-03-11T09:23:20Z) - Context Before Code: An Experience Report on Vibe Coding in Practice [1.7327102304628392]
This paper presents an experience report on "vibe coding" under production constraints.<n>We build a multi-project agent learning platform designed for sustained, production-oriented use.<n>We identify recurring architectural "non-delegation zones" where conversational code generation remains insufficient for production reliability.
arXiv Detail & Related papers (2026-03-10T20:20:33Z) - His2Trans: A Skeleton First Framework for Self Evolving C to Rust Translation with Historical Retrieval [45.246293154277886]
His2Trans is a framework that combines a deterministic, build-aware skeleton with self-evolving knowledge extraction to support stable, incremental migration.<n> Experiments on industrial OpenHarmony modules show that His2Trans reaches a 99.75% incremental compilation pass rate.
arXiv Detail & Related papers (2026-03-03T05:42:08Z) - Veri-Sure: A Contract-Aware Multi-Agent Framework with Temporal Tracing and Formal Verification for Correct RTL Code Generation [4.723302382132762]
silicon-grade correctness remains bottlenecked by: (i) limited test coverage and reliability of simulation-centric evaluation, (ii) regressions and repair hallucinations, and (iii) semantic drift as intent is reinterpreted across agent handoffs.<n>We propose Veri-Sure, a multi-agent framework that establishes a design contract to align agents' intent and uses a patching mechanism guided by static dependency slicing to perform precise, localized repairs.
arXiv Detail & Related papers (2026-01-27T16:10:23Z) - In Line with Context: Repository-Level Code Generation via Context Inlining [11.065371614078723]
In this paper, we introduce InlineCoder, a novel framework for repository-level code generation.<n>InlineCoder enhances the understanding of repository context by inlining the unfinished function into its call graph.
arXiv Detail & Related papers (2026-01-01T15:56:24Z) - A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code [49.09545217453401]
Propensity Smelly Score (PSC) is a metric that estimates the likelihood of generating particular smell types.<n>We identify how generation strategy, model size, model architecture and prompt formulation shape the structural properties of generated code.<n> PSC helps developers interpret model behavior and assess code quality, providing evidence that smell propensity signals can support human judgement.
arXiv Detail & Related papers (2025-11-19T19:18:28Z) - Training Language Models to Generate Quality Code with Program Analysis Feedback [66.0854002147103]
Code generation with large language models (LLMs) is increasingly adopted in production but fails to ensure code quality.<n>We propose REAL, a reinforcement learning framework that incentivizes LLMs to generate production-quality code.
arXiv Detail & Related papers (2025-05-28T17:57:47Z) - Bomfather: An eBPF-based Kernel-level Monitoring Framework for Accurate Identification of Unknown, Unused, and Dynamically Loaded Dependencies in Modern Software Supply Chains [0.0]
Inaccuracies in dependency-tracking methods undermine the security and integrity of modern software supply chains.<n>This paper introduces a kernel-level framework leveraging extended Berkeley Packet Filter (eBPF) to capture software build dependencies transparently in real time.
arXiv Detail & Related papers (2025-03-03T22:32:59Z) - Large Language Models as Realistic Microservice Trace Generators [48.730974361862366]
This paper proposes a first-of-a-kind approach that relies on training a large language model (LLM) to generate synthetic workload traces.<n>We show that TraceLLM produces diverse, realistic traces under varied conditions, outperforming existing approaches in both accuracy and validity.<n>TraceLLM adapts to downstream trace-related tasks, such as predicting key trace features and infilling missing data.
arXiv Detail & Related papers (2024-12-16T12:48:04Z) - Commit0: Library Generation from Scratch [77.38414688148006]
Commit0 is a benchmark that challenges AI agents to write libraries from scratch.<n>Agents are provided with a specification document outlining the library's API as well as a suite of interactive unit tests.<n> Commit0 also offers an interactive environment where models receive static analysis and execution feedback on the code they generate.
arXiv Detail & Related papers (2024-12-02T18:11:30Z)
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.