Search: “software”

Leveraging System-Level Observations to Inform Bayesian Learning of Model Parameters for Quantitative Verification

arXiv:2608.03489v1 Announce Type: cross Abstract: Combining Bayesian learning and quantitative verification is a powerful toolset for analysing key quantitative properties of software systems, like re

applicationsarxiv-cs-ai

5 Aug 2026

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Agents

Studying, Identifying, and Fixing Hidden Technical Debt in AI-Intensive Cyber-Physical Systems

DGX agent

arXiv:2608.02638v1 Announce Type: cross Abstract: Artificial Intelligence (AI) components are increasingly pervasive in several software systems, including Cyber-Physical Systems (CPSs). AI-CPS are us

agentsarxiv-cs-ai

5 Aug 2026

RAG Strategies for Natural Language-Based SQL Query and REST API Call Generation

arXiv:2602.07086v2 Announce Type: replace-cross Abstract: Enterprise software systems commonly expose business functionality through both relational databases and REST APIs. Accessing these interfaces

applicationsarxiv-cs-cl

Statistical comparisons of time-series feature sets on classification tasks

arXiv:2608.01586v1 Announce Type: cross Abstract: In recent years, numerous open-source software libraries have been developed for computing sets of features from univariate time series. The type and

SWE-Touch: Benchmarking Coding Agents When Users Touch the Code

arXiv:2608.02499v1 Announce Type: cross Abstract: Real-world software development requires coding agents to operate in shared workspaces where users may inspect and modify code during an ongoing task,

agentsarxiv-cs-cl

TELLER: Non-intrusive Cross-Layer Root-Cause Analysis for LLM Inference

arXiv:2608.01975v1 Announce Type: cross Abstract: Large language model (LLM) inference has evolved from an offline workload into a continuously operated software service, yet root-cause analysis remai

local-aiarxiv-cs-cl

Who Is Responsible? Self-Adaptation Under Multiple Concurrent Uncertainties With Unknown Sources in Complex ROS-Based Systems

arXiv:2504.20477v4 Announce Type: replace Abstract: Robotic systems increasingly operate in dynamic, unpredictable environments, where tightly coupled sensors and software modules increase the probabi

researcharxiv-cs-ro

A Model-Driven Approach for Developing Families of Reinforcement Learning Environments

arXiv:2606.20324v2 Announce Type: replace-cross Abstract: Virtual training environments are software-intensive systems in which reinforcement learning (RL) agents learn, adapt, and demonstrate meaning

local-aiarxiv-cs-lg

Analysing User Reviews to Identify User Concerns Around Permissions in AI Apps

arXiv:2607.29343v1 Announce Type: new Abstract: Artificial intelligence is increasingly embedded in everyday software, making its integration into mobile apps inevitable. However, AI mobile app develo

RePaCA: Leveraging Reasoning Large Language Models for Static Automated Patch Correctness Assessment

arXiv:2507.22580v2 Announce Type: replace-cross Abstract: Automated Program Repair (APR) seeks to automatically correct software bugs without requiring human intervention. However, existing tools tend

Sensitivity Analysis of GRU, LSTM and Transformer Encoder in Classification of Automated Driving Systems

arXiv:2607.28665v1 Announce Type: cross Abstract: Automated driving systems (ADSs) are becoming ubiquitous. Future Software Defined Vehicles (SDVs) may be able to run multiple ADSs, both native and af

Unanticipated Effects of Generative AI on Expertise Pathways and Performance Perception in System Administration

arXiv:2607.28650v1 Announce Type: cross Abstract: While industry discourse often emphasizes immediate productivity gains and frames GenAI primarily as a tool for automation, the integration of GenAI i

Fewer Clarifications, Better Code: Benchmarking Cross-Session Personalized Ambiguity Adaptation in Coding Assistants

arXiv:2607.26611v1 Announce Type: new Abstract: AI-assisted coding increasingly translates informal user intent into executable software, yet coding requests often contain ambiguities that recur in us

31 Jul 2026

ThreatForest: Multi-Agent Attack Tree Generation with Pluggable TTP Framework Mapping

arXiv:2607.27528v1 Announce Type: cross Abstract: Threat modeling is essential for secure software development, yet manual analysis of cloud-native architectures is slow and demands scarce security ex

agentsarxiv-cs-cl

31 Jul 2026

Kernel Forge: An Agent Harness for LLM-based Generation and Optimization of CUDA Kernels

arXiv:2607.24762v1 Announce Type: new Abstract: Machine learning models are increasingly embedded in everyday software, and most of their runtime is spent in a small set of compute kernels such as mat

29 Jul 2026

Learning from 53.6K Real-World Developer Edits of AI-Generated Code

arXiv:2607.25130v1 Announce Type: cross Abstract: Imperfections in AI-generated code require that software developers modify the generated code manually, or by re-prompting an AI programming assistant

29 Jul 2026

Towards an Agent Operating System - Lessons from Classical and Cloud OS

arXiv:2607.25076v1 Announce Type: new Abstract: Every major wave of platform software follows the same arc: an initial period of experimentation with competing frameworks and ad-hoc implementations, f

29 Jul 2026

Bit-Accurate FPGA Evaluation of Learned Feature Gating in a Fixed-Point Fourier-Feature Automatic Modulation Classifier

arXiv:2607.24568v1 Announce Type: new Abstract: Learned feature reweighting can improve automatic modulation classification (AMC) in software, but the same operation introduces additional arithmetic a

28 Jul 2026

ParBench: A Benchmark for Reliable Evaluation of LLM Parallel Code Translation

arXiv:2607.22588v1 Announce Type: new Abstract: Modern compute-intensive software must migrate across a changing ecosystem of accelerators, programming APIs, compiler stacks, and portability layers, i

28 Jul 2026

The Illusion of Secure LLM Code: Closing the Security Gap via Iterative Reprompting

arXiv:2607.23710v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly integrated into software development workflows, yet their ability to autonomously generate secure authen

applicationsarxiv-cs-ai

28 Jul 2026

IssueTrojanBench: Benchmarking AI Coding Agents Against Malicious Issue Requests

arXiv:2607.20759v1 Announce Type: cross Abstract: AI coding agents powered by LLMs are increasingly integrated into real-world software development, where they generate, edit, and execute code with au

24 Jul 2026

Towards an Automated Test of LLM Security Knowledge

arXiv:2607.18496v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly used for a range of software, hardware and human-centered security tasks. Consequently, LLM perf

24 Jul 2026

Alipay-PIBench: A Realistic Payment Integration Benchmark for Coding Agents

arXiv:2607.14573v3 Announce Type: replace Abstract: Payment integration is a demanding repository-level software task: agents must select a suitable product, implement coordinated client-server flows,

23 Jul 2026

CEO-Bench: Can Agents Play the Long Game?

arXiv:2606.18543v2 Announce Type: replace Abstract: Language model agents are becoming proficient executors at isolated, short-horizon tasks such as software engineering and customer service. Yet real

23 Jul 2026

CURED: Creating, Understanding, and Repairing Errors Demonstrator

arXiv:2607.20140v1 Announce Type: new Abstract: Detecting and cleaning errors in tabular data is a prerequisite for data intense software applications. Recent research at the intersection of Machine L

23 Jul 2026

Faithful Autoformalization of Natural Language Assertions

arXiv:2607.13303v1 Announce Type: cross Abstract: Formal contracts are essential for software testing and verification, yet writing them remains labor-intensive and error-prone. LLMs offer a promising

researcharxiv-cs-ai

Rethinking Penetration Testing for AI-Enabled Systems: From Resource Compromise to Behavioral Objective Violation

arXiv:2607.14006v1 Announce Type: cross Abstract: Penetration testing traditionally evaluates whether adversaries can exploit weaknesses in software, infrastructure, configurations, or operational con

SemaDiff: Identifying Semantic-Changing Commits with Generated Code and Tests

arXiv:2607.13111v1 Announce Type: cross Abstract: Distinguishing semantic-preserving commits from changing ones remains an open challenge in software repository mining. While existing approaches detec

local-aiarxiv-cs-ai

Tutorials

The Hitchhiker's Guide to Monoculture

arXiv:2607.13077v1 Announce Type: cross Abstract: Large language models (LLMs) often produce homogeneous outputs, raising concerns that AI coding assistants may lead to convergence in the software art

tutorialsarxiv-cs-ai

Agentic Service-Oriented Computing: A Manifesto for the Next Frontier of Service-Oriented Computing

arXiv:2607.12619v1 Announce Type: new Abstract: The rapid emergence of LLM-powered autonomous and semi-autonomous agents is reshaping software systems from static, request-response components into goa

Code-MUE: Measuring Code LLMs' Uncertainty through Execution-based Semantic Interaction Graphs

arXiv:2607.12273v1 Announce Type: cross Abstract: As Code Large Language Models (LLMs) become central to modern software engineering, their inherent stochasticity poses significant real-world risks, w

Git-Assistant: Planning-Based Support for Updating Git Repositories

arXiv:2607.09224v2 Announce Type: replace-cross Abstract: Version control systems are essential for collaborative software development, yet tools like git remain challenging for many practitioners. Re

Interpretable and Verifiable Hardware Generation with LLM-Driven Stepwise Refinement

arXiv:2606.19387v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have achieved remarkable success in software development. However, they are susceptible to hallucinations, meanin

QwenPaw-Data: Bridging Facts, Methodology, and Execution for Autonomous Enterprise Data Analytics

arXiv:2607.11019v2 Announce Type: replace Abstract: Enterprise data analysis is emerging as a distinct frontier for autonomous agents. Compared with general-purpose interaction and software engineerin

Toward Localizing and Repairing Bias in Transformer Attention Heads

arXiv:2607.12863v1 Announce Type: cross Abstract: Transformer language models are increasingly used as software components, yet biased outputs remain difficult to localize and repair inside the model.

local-aiarxiv-cs-lg

Hardware

CTA-Pipelining: A Latency-Oriented Spatial Scaling Method for Multi-GPU Systems

arXiv:2607.07862v1 Announce Type: cross Abstract: The evolution of compute infrastructure has transformed multi-GPU systems into tightly integrated shared-memory structures. However, current software

hardwarearxiv-cs-lg

10 Jul 2026

DeepSWE: Measuring Frontier Coding Agents on Original, Long-Horizon Engineering Tasks

model-releasesarxiv-cs-lg

arXiv:2607.07946v1 Announce Type: cross Abstract: DeepSWE is a benchmark of 113 original, long-horizon software engineering tasks for evaluating coding agents. Most public agentic coding benchmarks fo

10 Jul 2026

Token-Flow Firewall: Semantic Runtime Auditing for Persistent AI Agents

arXiv:2607.08395v1 Announce Type: cross Abstract: Persistent AI agents extend large language models (LLMs) beyond single-turn interaction into long-lived software systems. Unlike traditional chat assi

local-aiarxiv-cs-cl

10 Jul 2026

Beyond Correctness: Enhancing Architectural Reasoning in Code LLMs via Scalable Labeling with Agentic Judgment

arXiv:2606.14948v2 Announce Type: replace-cross Abstract: LLMs have substantially improved software engineering yet real-world development requires architectural understanding. Such understanding is p

8 Jul 2026

Mitigating Errors in LLM-Generated Web API Invocations via Retrieval-Augmented Generation and Constrained Decoding

arXiv:2607.05936v1 Announce Type: cross Abstract: Integration of web APIs is a cornerstone of modern software systems, yet writing correct web API invocation code remains challenging due to complex an

applicationsarxiv-cs-lg

8 Jul 2026

A Retrieval-Augmented Framework for Detecting and Resolving Pragmatic Ambiguities in Natural Language Requirements

arXiv:2607.04436v1 Announce Type: cross Abstract: Natural language requirements (NLRs) are essential for bridging communication gaps among diverse stakeholders in software development. However, the in

Benchmarking API Drift in LLM-Generated Quantum Code Across Successive SDK Versions

arXiv:2607.04072v1 Announce Type: cross Abstract: Large language models can generate plausible quantum code, but it is unclear whether they can reliably target the specific software development kit (S

Beyond Task Completion: A Verification-vs.-Conformance Gap in Tool-Evolving Agents

arXiv:2604.00392v2 Announce Type: replace-cross Abstract: Agents that synthesize their own tools ship a second artifact alongside each answer: a software library that future tasks reuse, compose, and

Beyond the Need for Speed: Energy-Aware Code Generation via Simulation-Guided Reinforcement Learning

arXiv:2607.04577v1 Announce Type: new Abstract: Code models strictly prioritize functional correctness, leaving software energy efficiency as an unoptimized byproduct. Training models to generate ener

applicationsarxiv-cs-lg

CoACT: Action-Preserving Observation Compression for Coding Agents

arXiv:2607.02911v1 Announce Type: cross Abstract: LLM-based coding agents solve software-engineering tasks through iterative interactions with development environments, where returned observations acc

Don't Blame the Large Language Model: How Scaffolding Evolution Shapes Coding Agent Quality

arXiv:2607.03691v1 Announce Type: cross Abstract: Coding agents, autonomous systems that use large language models (LLMs) to resolve software engineering tasks, rely on agentic scaffolding: a middlewa

Evaluating LLM-Based Regression Test Generation

arXiv:2501.11086v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have shown tremendous promise in automated software engineering. In this paper, we investigate LLMs for just-in-t

researcharxiv-cs-ai

Latent Programming Horizons in Coding Agents

arXiv:2607.05188v1 Announce Type: new Abstract: A coding agent solving a software-engineering task spends dozens of steps reasoning, editing code, and running tests, yet little is known about what the

agentsarxiv-cs-lg