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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
Overcoming Obstacles: Challenges of Gender Inequality in ...
Angelica Pereira Souza, Anderson Uchôa, Edna Dias Canedo, Julian · 2025-05-03 · via cs.SE updates on arXiv.org

Context: Gender inequality is a widely discussed issue across various sectors, including Information Technology and Communication (ICT). In Brazil, women represent less than 18% of ICT students in higher education. Prior studies highlight gender-related barriers that discourage women from staying in ICT. However, they provide limited insights into their perceptions as undergraduate students and the factors influencing their participation and confidence. Goal: This study explores the perceptions of women undergraduate students in ICT regarding gender inequality. Method: A survey of 402 women from 18 Brazilian states enrolled in ICT courses was conducted using a mixed-method approach, combining quantitative and qualitative analyses. Results: Women students reported experiencing discriminatory practices from peers and professors, both inside and outside the classroom. Gender stereotypes were found to undermine their self-confidence and self-esteem, occasionally leading to course discontinuation. Conclusions: Factors such as lack of representation, inappropriate jokes, isolation, mistrust, and difficulty being heard contribute to harmful outcomes, including reduced participation and reluctance to take leadership roles. Addressing these issues is essential to creating a safe and respectful learning environment for all students.