cs.SE · 2026-08-24 · No. 94

Software Engineering, 2026-08-24.

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

01 — The papers

6 entries
  1. 01

    AI with Authority, from Application to Silicon

    Jason Hickey

    cs.SE · cs.AI · cs.AR · cs.LO

    For sixty years, machine verification has been a major cost overhead, affordable only for exceptional artifacts. Here we report that generative AI inverts this relationship: at AI speed, machine verification is not only economical but essential to productivity --- it is the incorruptible referee that lets one person safely direct autonomous machine work at scale. In five weeks, one researcher on consumer AI subscriptions directed a small...

    arxiv.org/abs/2608.21356 · PDF

  2. 02

    Specification Portability Across LLM Development Agents: Cross-Agent Compatibility in Specification-Driven Software Migration

    Oleg Grynets, Oleksii Ilchuk, Dariia Zatulna, Vasyl Lyashkevych

    cs.SE · cs.AI · cs.LO

    This paper investigates cross-agent specification portability using Oracle-to-PostgreSQL migration as a controlled software transformation task. The study combines two experimental stages. First, a specification-first migration pipeline was evaluated on 1,006 PL/SQL files, of which 623 were successfully regenerated and 380 generated scripts executed successfully in PostgreSQL 16. Second, cross-agent experiments were conducted on a dataset of...

    arxiv.org/abs/2608.21208 · PDF

  3. 03

    Trustworthy RAG: An Evaluation Agent for Detecting Misinformation and Knowledge Poisoning in Generative AI Systems

    Balkrishna Giri, Md Toufique Hasan, Jussi Rasku, Muhammad Waseem, Pekka Abrahamsson

    cs.SE · cs.AI · cs.CL · cs.CR · cs.IR

    Retrieval-Augmented Generation (RAG) grounds Large Language Model (LLM) outputs in external knowledge, but RAG systems usually trust whatever they retrieve, creating a Security-Reliability Gap: high semantic relevance does not guarantee factual truth. Adversaries exploit this through knowledge poisoning, inserting malicious documents to cause targeted misinformation. We propose an Evaluation Agent, middleware that combines Natural Language...

    arxiv.org/abs/2608.21095 · PDF

  4. 04

    BC-Bench: Evaluating Agentic Engineering in a Domain-Specific Language for ERP

    Haoran Sun, Klaus Marius Hansen

    cs.SE · cs.AI

    Agentic engineering systems have shown strong performance on general-purpose benchmarks, yet their effectiveness in enterprise resource planning (ERP) domain-specific languages (DSLs) remains underexplored. We introduce BC-Bench, a benchmark designed to evaluate agentic engineering on real-world tasks in AL, the DSL for Microsoft Dynamics 365 Business Central. BC-Bench comprises 101 manually curated tasks extracted from two Microsoft-owned...

    arxiv.org/abs/2608.20851 · PDF

  5. 05

    Temporal Validity on Real Software Histories: Eliminating Stale-Fact Errors in Code-Assistant Memory over GitHub Fixes

    Neeraj Yadav

    cs.SE · cs.AI · cs.CL · cs.LG

    Retrieval-augmented generation (RAG) has no model of time: when a fact changes across a coding session - a function is renamed, an endpoint moves, a dependency is bumped - RAG retrieves both the old and new value with near-identical similarity and cannot tell which is current, so it serves the superseded value. Paper 1 showed, on synthetic single-value benchmarks, that a deterministic (subject, relation, object) supersession memory eliminates...

    arxiv.org/abs/2608.20685 · PDF

  6. 06

    Testing and Evaluation of Agentic AI Systems In Military Command and Control

    Ulysse Richard, Heather Frase, Sarah Cao, Di Cooke, Sebastian Kwon, Adrianna Tan

    cs.SE · cs.AI · cs.CY

    Agentic AI systems are being procured for military command and control (C2) under public commitments to rigorous testing and human oversight. Whether such commitments can be discharged depends on their supporting assurance case, which requires three elements: claims specifying the conditions for acceptability, evidence bearing on those claims, and an argument connecting the two. Through a structured review of 240 documented Testing and...

    arxiv.org/abs/2608.20597 · PDF

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