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VLA Foundry: A Unified Framework for Training Vision-Language-Action Models Evaluating LLM-Generated Obfuscated XSS Payloads for Machine Learning-Based Detection Do Agents Dream of Root Shells? Partial-Credit Evaluation of LLM Agents in Capture the Flag Challenges Refute-or-Promote: An Adversarial Stage-Gated Multi-Agent Review Methodology for High-Precision LLM-Assisted Defect Discovery From Particles to Perils: SVGD-Based Hazardous Scenario Generation for Autonomous Driving Systems Testing Choose Your Own Adventure: Non-Linear AI-Assisted Programming with EvoGraph Human-Machine Co-Boosted Bug Report Identification with Mutualistic Neural Active Learning LLMSniffer: Detecting LLM-Generated Code via GraphCodeBERT and Supervised Contrastive Learning Neurosymbolic Repo-level Code Localization CodeMMR: Bridging Natural Language, Code, and Image for Unified Retrieval Symbolic Guardrails for Domain-Specific Agents: Stronger Safety and Security Guarantees Without Sacrificing Utility Verification Modulo Tested Library Contracts The Semi-Executable Stack: Agentic Software Engineering and the Expanding Scope of SE Scaling Test-Time Compute for Agentic Coding AI-Assisted Requirements Engineering: An Empirical Evaluation Relative to Expert Judgment From Procedural Skills to Strategy Genes: Towards Experience-Driven Test-Time Evolution Atropos: Improving Cost-Benefit Trade-off of LLM-based Agents under Self-Consistency with Early Termination and Model Hotswap Vibe-Coding: Feedback-Based Automated Verification with no Human Code Inspection, a Feasibility Study Benchmarks for Trajectory Safety Evaluation and Diagnosis in OpenClaw and Codex: ATBench-Claw and ATBench-Codex Bounded Autonomy for Enterprise AI: Typed Action Contracts and Consumer-Side Execution AIPC: Agent-Based Automation for AI Model Deployment with Qualcomm AI Runtime Analyzing Chain of Thought (CoT) Approaches in Control Flow Code Deobfuscation Tasks Asking What Matters: Reward-Driven Clarification for Software Engineering Tasks Prompt-Driven Code Summarization: A Systematic Literature Review LinuxArena: A Control Setting for AI Agents in Live Production Software Environments LLMs taking shortcuts in test generation: A study with SAP HANA and LevelDB Large Language Models to Enhance Business Process Modeling: Past, Present, and Future Trends CollabCoder: Plan-Code Co-Evolution via Collaborative Decision-Making for Efficient Code Generation Sentiment analysis for software engineering: How far can zero-shot learning (ZSL) go? Learning from Change: Predictive Models for Incident Prevention in a Regulated IT Environment
From Forced Working-From-Home to Working-From-Anywhere: T...
Darja Smite, Nils Brede Moe, Eriks Klotins, Javier Gonzalez-Huer · 2021-01-21 · via cs.SE updates on arXiv.org

The COVID-19 outbreak has admittedly caused a major disruption worldwide. The interruptions to production, transportation, and mobility have clearly had a significant impact on the well-functioning of the global supply and demand chain. But what happened to the companies developing digital services, such as software. Were they interrupted as much or at all? And how has the enforced Working-From-Home mode impacted their ability to continue to deliver software? We hear that some managers are concerned that their engineers are not working effectively from home, or even lack the motivation to work in general, that teams lose touch and that managers do not notice when things go wrong. In this article, we share our findings from monitoring the situation in an international software company with engineers located in Sweden, USA, and the UK. We analyzed different aspects of productivity, such as developer satisfaction and well-being, activity, communication and collaboration, efficiency and flow based on the archives of commit data, calendar invites, and Slack communication, as well as the internal reports of WFH experiences and 18 interviews. We find that company engineers continue committing code and carry out their daily duties without significant disruptions, while their routines have gradually adjusted to the new norm with new emerging practices and various changes to the old ones. In a way, our message is that there is no news, which is good news. Yet, the experiences gained with the WFH of such scale have already made significant changes in the software industry's future, work from anywhere being an example of major importance.