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Three-Phase Evaluation of AI-Assisted Software Development Life Cycle

This paper presents an exploratory evaluation of how increasing levels of AI autonomy affect software development productivity, requirement adherence, and developer cognitive workload. A team of four developers reimplemented the same full-stack web application across three sequential phases: partial AI-assisted development using GitHub Copilot, an AI-exclusive workflow using GitHub Copilot, and an AI-exclusive workflow using AWS Kiro.

Three-Phase Evaluation of AI-Assisted Software Development Life Cycle

arXiv:2607. 05125v1 Announce Type: cross Abstract: This paper presents an exploratory evaluation of how increasing levels of AI autonomy affect software development productivity, requirement adherence, and developer cognitive workload.

From cloud to developers: Hugging Face and Microsoft Deepen Collaboration

Jas: AI-Paired Engineering as a Revival of N-Version Programming

arXiv:2606. 07828v1 Announce Type: cross Abstract: I report a case study in AI-paired software engineering: five working ports of a vector illustration application across Rust, Swift, OCaml, Python, and browser-based platforms, built by a single developer in approximately 120 evening hours.

Using LLMs in Software Design: An Empirical Study of GitHub and A Practitioner Survey

arXiv:2605.01392v2 Announce Type: replace-cross Abstract: Recent advancements in Large Language Models (LLMs) have demonstrated significant potential across software engineering tasks, including soft...

From Social Coding to Agentic Coding: Productivity and Relational Reconfiguration in Open-Source Communities

arXiv:2608. 03585v1 Announce Type: new Abstract: Open-source software communities are a form of digital public infrastructure that not only produces code, but also generates public knowledge and interpersonal relationships through visible collaboration.

EngiWorld: What Can Frontier Agents Deliver in Professional Engineering Environments?

EngiWorld is a new benchmark that tests autonomous agents across the full engineering design loop, covering 1,301 expert‑curated tasks in six domains (CAD, CAE, CAM, BIM, EDA, and 3D visualization) and 26 professional software platforms with both GUI and CLI interfaces. It introduces an artifact‑centric evaluation method that programmatically verifies geometric validity, physical feasibility, and rule compliance of both final and intermediate artifacts, scoring tasks continuously rather than with binary success. Initial tests of seven frontier models show a large capability gap, with the best model scoring only 44.3 on the EngiScore and just 3.6% of multi‑software attempts succeeding.

PlanCraft: Sketch, Refine, and Furnish for Architect-Inspired Progressive 3D Residential Scene Generation

PlanCraft introduces a progressive approach to 3D residential scene generation that mirrors how architects design: starting with rough sketches and refining them over time. It leverages a large dataset of real floor plans to train a SketchPlan module that generates partial sketches at various completion levels, a PlanCraft‑Diff module that sharpens these sketches into precise vector floor plans, and a PlanCraft‑Agent that furnishes rooms within the established spatial contract. The method outperforms existing 2D and 3D baselines, achieving a 61.1% lower FID and a 15‑point lead in expert‑rated spatial rationality, even with only 25% sketch completion.

Simplex rethinks software development with Codex

Simplex boosts software development with ChatGPT Enterprise and Codex, reducing design, build, and testing time while scaling AI-driven workflows.

BIM-Edit: Benchmarking Large Language Models for IFC-Based Building Information Modeling

arXiv:2606. 20146v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly applied to computer-aided design (CAD) to generate design artifacts from textual instructions.

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