software-engineering

Documents about software-engineering

• MultiMend: Multilingual Program Repair with Context Augmentation and Multi-Hunk Patch Generation#139121arXiv (OAI)
• Fine-Tuning Code Language Models to Detect Cross-Language Bugs#155621arXiv (OAI)
• Towards Explorative IRBL: Combining Semantic Retrieval with LLM-driven Iterative Code Exploration#158757arXiv (OAI)
• QCP: A Practical Separation Logic-based C Program Verification Tool#163128arXiv (OAI)
• GitBugs: Bug Reports for Duplicate Detection, Retrieval Augmented Generation, Triage, and More#179144arXiv (OAI)
• Exposing Go's Hidden Bugs: A Novel Concolic Framework#183244arXiv (OAI)
• Concolic Testing on Individual Fairness of Neural Network Models#189341arXiv (OAI)
• Design and Development of MATLAB-based software for running a 3-point bending fatigue testing apparatus#208568Figshare
• Java Preparation for 6.170#3298MIT OpenCourseWare
• Pedixplorer: a Bioconductor package to streamline pedigree design and visualization#231685HAL (France)
• Reconciling performance and efficient use of hardware resources : the case of configurable software services#137374HAL (France)
• Program Encryption Toolkit: A Tool for Digital Logic Education and Undergraduate Research#199476OpenAlex
• Identifying Industry-Preferred Automation Software in Engineering: An Indeed-Based Analysis to Inform Engineering Technology Curriculum Design#203058ODU Digital Commons
• Sentiment analysis for software engineering: How far can zero-shot learning (ZSL) go?#14067arXiv CS
• STAR: Software Tools for Academics and Researchers#67371MIT OpenCourseWare
• Are Sparse Autoencoders Useful for Java Function Bug Detection?#128387arXiv (OAI)
• CodeFlowBench: A Multi-turn, Iterative Benchmark for Complex Code Generation#144281arXiv (OAI)
• Semantic Reverse Engineering Legacy Software Applications with ChatGPT, Gemini AI, and Claude AI#168425arXiv CS
• Test Case Generation for Simulink Models: An Experience from the E-Bike Domain#179109arXiv (OAI)
• Effective LLM Code Refinement via Property-Oriented and Structurally Minimal Feedback#189291arXiv (OAI)
• Introduction to C Memory Management and C++ Object-Oriented Programming#3359MIT OpenCourseWare
• Agility, Innovation and Risk: A Systematic Literature Review on New Software Product Development and Organisational Capabilities#248679Springer Nature OA
• The Architecture of Open Source Applications, Volume I#2409AOSA Book
• The Architecture of Open Source Applications, Volume II#2410AOSA Book
• Geant4 developments and applications#7156OpenAlex
• CODEPROMPTZIP: Code-specific Prompt Compression for Retrieval-Augmented Generation in Coding Tasks with LMs#131291arXiv (OAI)
• SEW: Self-Evolving Agentic Workflows for Automated Code Generation#141744arXiv (OAI)
• Are Decoder-Only Large Language Models the Silver Bullet for Code Search?#158645arXiv (OAI)
• Does AI Code Review Lead to Code Changes? A Case Study of GitHub Actions#173349arXiv (OAI)
• Learning to Ask: When LLM Agents Meet Unclear Instruction#179078arXiv (OAI)
• Case Studies and Reflections on Agentic Software Engineering for Rapid Development of Digital Music Instruments#217809Goldsmiths Research Online
• AI Engineering Orchestrator : A Dual-Lens Framework for Streamline AI Development Pipelines#157580HAL (France)
• Efficient Black-Box Fault Localization for System-Level Test Code Using Large Language Models#139192arXiv (OAI)
• Raw Pointer Rewriting with LLMs for Translating C to Safer Rust#153057arXiv (OAI)
• EyeMulator: Improving Code Language Models by Mimicking Human Visual Attention#153122arXiv (OAI)
• What Prompts Don't Say: Understanding and Managing Underspecification in LLM Prompts#173293arXiv (OAI)
• Advances in Artificial Intelligence forDiabetes Prediction: Insights from a Systematic Literature Review#179105arXiv (OAI)
• Reversa: A Reverse Documentation Engineering Framework for Converting Legacy Software into Operational Specifications for AI Agents#200524arXiv CS
• Human-Assisted AI: What AI Is, How It Fails, and Why Your Engineering Discipline Is Your Best Defense#14519DataCite
• Human-Assisted AI: What AI Is, How It Fails, and Why Your Engineering Discipline Is Your Best Defense#14520DataCite
• OpenClassGen: A Large-Scale Corpus of Real-World Python Classes for LLM Research#128373arXiv (OAI)
• Snakemake Hackathon 2026#136481OSF
• A PennyLane-Centric Dataset to Enhance LLM-based Quantum Code Generation using RAG#149227arXiv (OAI)
• ReGA: Model-Based Safeguard for LLMs via Representation-Guided Abstraction#153079arXiv (OAI)
• Scaling up requirements engineering - exploring the challenges of increasing size and complexity in market-driven software development#178000Lund University Publications
• AI Failures in the Eyes of the Downstream Developer: A First Look at Concerns, Practices, and Challenges#183218arXiv (OAI)
• Understanding the Human-LLM Dynamic: A Literature Survey of LLM Use in Programming Tasks#189212arXiv (OAI)
• Foundational Design Principles and Patterns for Building Robust and Adaptive GenAI-Native Systems#158777arXiv (OAI)
• AdaDec: A Uncertainty-Guided Lookahead Decoding Framework for LLM-Based Code Generation#163149arXiv (OAI)
• The Ultimate Configuration Management Tool? Lessons from a Mixed Methods Study of Ansible's Challenges#183228arXiv (OAI)