cs.SE · 2026-09-09 · No. 110

Software Engineering, 2026-09-09.

3 new papers in cs.SE. Titles, authors, abstracts. Links to arXiv. Want this in your inbox every morning? Subscribe →

01 — The papers

3 entries
  1. 01

    It Is Not My Code Anymore

    Augusto Camargo

    cs.SE · cs.AI

    AI-assisted programming raises distinct questions about who produces code, who feels ownership of it, and who is responsible when it fails. This research note examines these distinctions through a hypothetical enrollment failure and a selective reading of the literature. Identifying the producer of a defective expression does not, by itself, determine the duties of reviewers, release decision-makers, or service operators. Collective ownership...

    arxiv.org/abs/2609.09022 · PDF

  2. 02

    The Unreliable Progress Bar: Can LLM Agents Reliably Report Task Progress Throughout Execution?

    Boyang Wang, Yunhan Wang, Yalun Wu

    cs.SE · cs.AI · cs.CL

    Recent large language models can emit task-progress signals that agent frameworks use to decide whether a task should continue or stop, yet whether a model can reliably report its task progress at every stage of a task, and where and how its reports fail, has not been studied systematically. We evaluate this ability on the public benchmark $τ^2$-bench and on StageIF, a controlled testbed in which reporting checkpoints are placed across the...

    arxiv.org/abs/2609.08589 · PDF

  3. 03

    AttnCompress: Dynamic Attention-Guided Trajectory Compression for Software Engineering Agents

    Zhengran Zeng, Yixin Li, Rui Xie, Wei Ye, Shikun Zhang

    cs.SE · cs.AI

    The transition from human-centric assistance to Autonomous Software Engineering (ASE) agents has enabled the resolution of complex real-world SE tasks. However, the trial-and-error nature of these agents generates lengthy interaction trajectories, creating severe bottlenecks in terms of context window limits and cost. While context compression offers a potential remedy, prior approaches suffer from static pruning strategies and granularity...

    arxiv.org/abs/2609.08318 · PDF

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