arXiv:2608. 12355v1 Announce Type: cross Abstract: Recent progress in AI coding agent research has led to rapid improvements in agents' ability to autonomously perform complex software engineering tasks, from editing large codebases to executing long-horizon development workflows.
Spec-Driven Development (SDD) is a practice where developers and AI coding agents write specifications to guide software implementation, aiming to preserve the intent behind natural‑language instructions. This study analyzes SDD through Reddit discussions, interviews with 21 practitioners (including eight tool makers), and a large corpus of 470,795 spec files from 73,030 GitHub repositories. Findings reveal that while specs often include implementation details that aid agents, they also risk decay; tool-specific structures influence perception, and benefits vary between individuals and teams, with SDD mainly used for new features and involving higher planning and review costs.
arXiv:2605. 17548v2 Announce Type: replace-cross Abstract: Code review has evolved for decades, from informal peer checking to today's pull request (PR) workflows, yet it remains a largely manual and cognitively demanding process.
Kolab is a new dataset comprising over 115 hours of screen recordings from 50 professionals across 40 occupations who collaborate with AI agents on realistic, long‑horizon tasks. The dataset includes participants’ judgments of collaboration quality and output, revealing varied coordination patterns and the need for agents to anticipate how experts will use or modify their contributions. Analysis shows current state‑of‑the‑art models overestimate collaboration success and struggle to differentiate high‑ from low‑quality interactions, indicating a gap in understanding long‑horizon human‑agent teamwork.
Co-Design Bench is a new, reference‑free benchmark comprising 273 multimodal coding tasks derived from 26,314 real user sessions. It features two tracks—Multimodal Editing and Repository Editing—that test agents on localized edits with optional image, audio, video, or document inputs and coordinated repository changes across three capability dimensions: Grounded Understanding, UI Transformation, and Functional Implementation. The benchmark uses a judge‑then‑refute protocol with hidden expert‑authored acceptance criteria, and the best of ten model endpoints achieves an average of 69.9% criterion completion but fully satisfies only 26.4% of tasks, especially struggling with repository edits involving multiple change types.
arXiv:2606. 29727v1 Announce Type: new Abstract: Professional translation is often a team-based process: translators, reviewers, and project managers must coordinate terminology, legal force, and accountability across documents.
arXiv:2507. 16395v3 Announce Type: replace Abstract: Atomic commits, which address a single development concern, are a best practice in software development.
Long-horizon coding requires agents to maintain an evolving view of the project they are changing: what problem is currently being solved, what has already been learned or modified, which other artifa...
Professional translation is often a team-based process: translators, reviewers, and project managers must coordinate terminology, legal force, and accountability across documents. Yet many LLM-based translation tools treat human corrections as isolated edits.
arXiv:2410. 02091v4 Announce Type: replace-cross Abstract: Generative artificial intelligence (AI) facilitates content production and enhances ideation, with potentially important implications for developer productivity and participation in software development.
arXiv:2603.02050v5 Announce Type: replace-cross Abstract: Shared co-creative workspaces allow users to contribute while agents execute. Yet how users adjust their participation as their work and the...
arXiv:2605.29442v2 Announce Type: replace-cross Abstract: AI coding agents increasingly act directly within software environments, yet existing analyses of their failures rely on benchmark trajectori...