aiqbench analysis
This paper proposes the Spec Growth Engine, a framework designed to mitigate context explosion and silent spec-code drift in AI-assisted software development by enforcing machine-readable contracts and scoping agent reasoning. By integrating established software engineering principles like information hiding into a lightweight architecture, it aims to prevent costly divergence between evolving code and static specifications without relying on heavy-weight legacy frameworks.
The Spec Growth Engine: Spec-Anchored, Code-Coupled, Drift-Enforced Architecture for AI-Assisted Software Development
arXiv:2606.27045v2 Announce Type: replace-cross Abstract: AI coding agents dramatically accelerate implementation speed but introduce two structural failure modes that existing spec-driven approaches do not fully solve: (1) context explosion -- the agent must reason over an entire repository at once, degrading output quality as the context window fills; and (2) silent spec-code drift -- code evolves, the specification does not, and the divergence becomes invisible until it is costly to repair. We present the Spec Growth Engine, a lightweight framework that addresses both failure modes through a machine-readable spec graph whose nodes carry explicit contract/design separation, a Spine context assembler that scopes agent context to an ownership path, a vertical-slice growth protocol that enforces hardest-first ordering, and a drift gate that makes spec-code divergence a blocking merge condition. The design synthesises well-established software engineering principles (Parnas information hiding, C4, ADRs, Walking Skeleton, Reflexion Models, Fitness Functions) into a lean, code-coupled, machine-enforced whole -- without the overhead of heavy-weight frameworks such as RUP or MDA.
Abstract:AI coding agents dramatically accelerate implementation speed but introduce two structural failure modes that existing spec-driven approaches do not fully solve: (1) context explosion -- the agent must reason over an entire repository at once, degrading output quality as the context window fills; and (2) silent spec-code drift -- code evolves, the specification does not, and the divergence becomes invisible until it is costly to repair. We present the Spec Growth Engine, a lightweight framework that addresses both failure modes through a machine-readable spec graph whose nodes carry explicit contract/design separation, a Spine context assembler that scopes agent context to an ownership path, a vertical-slice growth protocol that enforces hardest-first ordering, and a drift gate that makes spec-code divergence a blocking merge condition. The design synthesises well-established software engineering principles (Parnas information hiding, C4, ADRs, Walking Skeleton, Reflexion Models, Fitness Functions) into a lean, code-coupled, machine-enforced whole -- without the overhead of heavy-weight frameworks such as RUP or MDA.
15 pages. Code: this https URL. Implementation: arXiv:2610.11725
Software Engineering (cs.SE); Artificial Intelligence (cs.AI)
arXiv:2606.27045 [cs.SE]
(or arXiv:2606.27045v2 [cs.SE] for this version)
https://doi.org/10.48550/arXiv.2606.27045 Focus to learn more arXiv-issued DOI via DataCite
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Full text under the publisher's open licence · 262 words
