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cs.SE updates on arXiv.org

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
Post-pandemic Resilience of Hybrid Software Teams
Ronnie de Souza Santos, Gianisa Adisaputri, Paul Ralph · 2023-03-11 · via cs.SE updates on arXiv.org

Background. The COVID-19 pandemic triggered a widespread transition to hybrid work models (combinations of co-located and remote work) as software professionals' demanded more flexibility and improved work-life balance. However, hybrid work models reduce the spontaneous, informal face-to-face interactions that promote group maturation, cohesion, and resilience. Little is known about how software companies can successfully transition to a hybrid workforce or the factors that influence the resilience of hybrid software development teams. Goal. The purpose of this study is to explore the relationship between hybrid work and team resilience in the context of software development. Method. Constructivist Grounded Theory was used, based on interviews of 26 software professionals. This sample included professionals of different genders, ethnicities, sexual orientations, and levels of experience. Interviewees came from eight different companies, 22 different projects, and four different countries. Consistent with grounded theory methodology, data collection, and analysis were conducted iteratively, in waves, using theoretical sampling, constant comparison, and initial, focused, and theoretical coding. Results. Software Team Resilience is the ability of a group of software professionals to continue working together effectively under adverse conditions. Resilience depends on the group's maturity. The configuration of a hybrid team (who works where and when) can promote or hinder group maturity depending on the level of intra-group interaction it supports. Conclusion. This paper presents the first study on the resilience of hybrid software teams. Software teams need resilience to maintain their performance in the face of disruptions and crises. Software professionals strongly value hybrid work; therefore, team resilience is a key factor to be considered in the software industry.