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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
Beyond the Binary: Motivations, Challenges, and Strategie...
Isabella Graßl · 2026-03-25 · via cs.SE updates on arXiv.org

When software is designed by people from diverse identities and experiences, it is more likely to be inclusive and address a broader range of user needs. However, for transgender and non-binary students in software engineering, the path to becoming such creators may be marked by unique challenges. While existing research explores gender minorities in professional software engineering, limited attention has been given to their educational journey, a key phase for ensuring equal opportunities and preventing exclusion in the tech workforce. This study aims to address this gap by investigating the experiences of transgender and non-binary students in software engineering, with a particular focus on their motivations for entering the field, the obstacles they encounter, and potential strategies for fostering greater inclusivity within their academic environments. Based on 13 semi-structured interviews with transgender and non-binary students across the globe, we found that gender identity plays an indirect role in their decision to pursue software engineering. Key factors include the appeal of remote work and a personal desire to create more inclusive technologies. Although the participants did not report direct discrimination within their universities, many described experiencing verbal insults, judgment, intolerance, and hostility, all of which negatively impacted their mental health. These challenges often stem from socio-cultural norms and a lack of representation. Despite these obstacles, the students remain committed to their choice of study but call for greater institutional support, structural changes, and increased representation. From these findings, we suggest concrete steps to support students, regardless of gender identity.