惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

Apple Machine Learning Research
Apple Machine Learning Research
aimingoo的专栏
aimingoo的专栏
酷 壳 – CoolShell
酷 壳 – CoolShell
博客园 - 聂微东
Engineering at Meta
Engineering at Meta
N
Netflix TechBlog - Medium
Blog — PlanetScale
Blog — PlanetScale
大猫的无限游戏
大猫的无限游戏
Vercel News
Vercel News
D
DataBreaches.Net
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
WordPress大学
WordPress大学
L
LangChain Blog
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
F
Fortinet All Blogs
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知
J
Java Code Geeks
Recent Announcements
Recent Announcements
Jina AI
Jina AI
G
Google Developers Blog
腾讯CDC
博客园_首页
博客园 - 【当耐特】

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
Automatic Detection of GUI Design Smells: The Case of Blo...
Valéria Lelli, Arnaud Blouin, Benoit Baudry, Fabien Coulon, Oliv · 2017-03-26 · via cs.SE updates on arXiv.org

Graphical User Interfaces (GUIs) intensively rely on event-driven programming: widgets send GUI events, which capture users' interactions, to dedicated objects called controllers. Controllers implement several GUI listeners that handle these events to produce GUI commands. In this work, we conducted an empirical study on 13 large Java Swing open-source software systems. We study to what extent the number of GUI commands that a GUI listener can produce has an impact on the change-and fault-proneness of the GUI listener code. We identify a new type of design smell, called Blob listener that characterizes GUI listeners that can produce more than two GUI commands. We show that 21 % of the analyzed GUI controllers are Blob listeners. We propose a systematic static code analysis procedure that searches for Blob listener that we implement in InspectorGuidget. We conducted experiments on six software systems for which we manually identified 37 instances of Blob listener. InspectorGuidget successfully detected 36 Blob listeners out of 37. The results exhibit a precision of 97.37 % and a recall of 97.59 %. Finally, we propose coding practices to avoid the use of Blob listeners.