Applied & Human-Centered · Computer Science & AI
Software Engineering
The newest papers in Software Engineering that ReadSearch has read, newest first. Each links to its own page, with its authors, date, where it was published and the original.
1,466 papers, from 31 August 2026 to 5 November 2026: 1,451 arXiv preprints and 15 OpenAlex records.
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A Heckler in the Hidden State: Correctness Signals in Diffusion Language Models
Diffusion language models generate code by repeatedly updating a partially masked sequence.GitHarness: Git Init Your Harness Working Memory for Perpetual User Requirements
LLM-based agents increasingly collaborate with users on long-horizon tasks, accumulating evidence, code, and drafts through extensive search, reasoning, and execution.XRepoSkill: Learning Transferable Skills for Software Engineering Agents
Software engineering agents increasingly use reusable skills distilled from prior experience to resolve repository-level issues, yet such skills often fail to transfer across repositories.Cross-Organizational SysML Model Integration: A Survey of Challenges and AI-Supported Tasks
Cross-organizational collaboration is widely regarded as a key promise of SysML-based Model-Based Systems Engineering (MBSE), yet practitioners still face persistent challenges when exchanging and…GitCF: Reducing Incomplete Changes by Exploiting Multiple Similarities Among Commits
Software developers often struggle to identify all locations that their changes affect, and incomplete changes frequently result from these omissions.LoLBench: Evaluating Coding Agents with Long-Horizon Proposals on Large Software Systems
Modern coding agents can deliver increasingly large repository-level changes, and recent benchmarks reflect this by emphasizing long-horizon tasks with large reference implementations.CRJudgeBench: Can AI Detect Plausible but Invalid Code Reviews?
Large language models can generate plausible code-review comments, but such comments may contain technically incorrect claims that mislead developers.SafeLLM4SE: Statistical Evaluation and Reporting for LLM-based Software Engineering Systems
Large language models (LLMs) are increasingly used for software engineering tasks, yet their stochastic behavior challenges the validity, reproducibility, and comparability of their evaluations.Do Agent Benchmarks Do What They Say? An Executable-Contract Audit of Tool-Using Agent Environments
Tool-using agents are entering settings where a wrong action carries real cost, and the benchmarks certifying them grade what each simulated tool call reports having done, assuming the tool did what…Mubric: Mutation Testing-Guided Rubric Generation for LLM Evaluation
Rubric-based evaluation is widely used to assess LLM-based systems by decomposing response quality into task-specific scoring criteria.Complexity-Aware Evaluation of LLM Comprehension
Large language models (LLMs) are increasingly used for software engineering tasks that require understanding existing source code, including behavior prediction, function explanation, debugging, and…Exploring Emotional Intelligence in Software Testing
Emotional Intelligence (EI) is the ability to recognise, understand, and manage one's own and others' emotions.Profiling the Energy Consumption of Serverless Functions with Joule Profiler
Cloud providers and customers have widely adopted serverless computing as a convenient paradigm for deploying and executing functions on demand.Independent Verification Paths Are Not Independent: A Case Study of Common-Mode Failure in a Satellite Catalogue Pipeline
A common safeguard for a data pipeline is redundant computation: derive each published number by two routes built on different technology and refuse to exit when they disagree.Beyond Productivity: Measuring Developers' Cognitive Load During GenAI-Supported Software Development
Generative AI (GenAI) is changing software development workflows and how developers work.Retrieve, Reproduce, Reveal: Dissecting Retrieval-Augmented Software Vulnerability Detection
Retrieval-Augmented Generation (RAG) is increasingly used to enhance Large Language Model (LLM)-based software vulnerability detection by grounding predictions in retrieved vulnerability knowledge…Is manual software optimization a thing of the past?
Scientific software is increasingly required to process larger datasets while maintaining acceptable execution times.AgentBug-Smith: Automatically Reproducing Real-World Harness Bugs in Agentic Systems
Agent harness bugs exhibit unique characteristics and remain challenging for state-of-the-art software agents to repair.Merged, Not Measured: An Empirical Study of Performance Issues Fixed by Coding Agents
Coding agents open pull requests (PRs) that claim to speed up software, but studies of human performance fixes say little about how maintainers respond to such a fix or whether its claim holds.A Function-level Dataset of Vulnerable and Fixed Source Code in JavaScript and TypeScript
JavaScript and TypeScript are widely used in modern web development, making their security critical; however, automated vulnerability detection is often constrained by the availability of…