How students use generative AI for software testing: An observational study [0.03%]
关于学生如何使用生成式人工智能进行软件测试的观察研究
Baris Ardic,Quentin Le Dilavrec,Andy Zaidman
Baris Ardic
The integration of generative AI tools like ChatGPT into software engineering workflows opens up new opportunities to boost productivity in tasks such as unit test engineering. However, these AI-assisted workflows can also significantly alt...
Is common sense all you need? Using expert defined rules to identify vulnerability patches instead of machine learning [0.03%]
常识够用吗？用专家定义的规则来识别漏洞补丁而不是使用机器学习
Aurora Papotti,Serena Elisa Ponta,Antonino Sabetta et al.
Aurora Papotti et al.
Goal: Machine learning (ML) has been proposed to identify security fixing commits with mixed success. We evaluate a different alternative in which expert-defined common sense rules with power-law weights are used to ident...
Less is more: usefulness of data flow diagrams and large language models for security threat validation [0.03%]
少即是多：数据流图和大型语言模型在安全威胁验证中的作用
Winnie Bahati Mbaka,Katja Tuma
Winnie Bahati Mbaka
The arrival of recent cybersecurity standards has raised the bar for security assessments in organizations, but existing techniques require a high manual effort. Threat analysis and risk assessment are used to identify security threats for ...
SecMLOps: A comprehensive framework for integrating security throughout the machine learning operations lifecycle [0.03%]
SecMLOps：一种在机器学习操作生命周期中全面集成安全性的框架
Xinrui Zhang,Pincan Zhao,Jason Jaskolka et al.
Xinrui Zhang et al.
Machine Learning (ML) has emerged as a pivotal technology in the operation of large and complex systems, driving advancements in fields such as autonomous vehicles, healthcare diagnostics, and financial fraud detection. Despite its benefits...
Tools and benchmarks evolve: what is their impact on parameter tuning in SBSE experiments? [0.03%]
工具和基准在软件工程实验中的影响分析与发展
Amid Golmohammadi,Man Zhang,Andrea Arcuri
Amid Golmohammadi
In this article, we explore the impact of tool development and its evolution in Search-Based Software Engineering (SBSE) research. As a research tool evolves throughout the years, experiments with novel techniques might require reevaluation...
AI support for data scientists: An empirical study on workflow and alternative code recommendations [0.03%]
基于工作流和备选代码建议的数据科学家人工智能助手实证研究
Dhivyabharathi Ramasamy,Cristina Sarasua,Abraham Bernstein
Dhivyabharathi Ramasamy
Despite the popularity of AI assistants for coding activities, there is limited empirical work on whether these coding assistants can help users complete data science tasks. Moreover, in data science programming, exploring alternative paths...
Analyzing and mitigating (with LLMs) the security misconfigurations of Helm charts from Artifact Hub [0.03%]
分析并利用LLM缓解Artifact Hub中Helm图表的安全配置问题
Francesco Minna,Fabio Massacci,Katja Tuma
Francesco Minna
Helm is a package manager that allows defining, installing, and upgrading applications with Kubernetes (K8s), a popular container orchestration platform. A Helm chart is a collection of files describing all dependencies, resources, and para...
A comprehensive study of machine learning techniques for log-based anomaly detection [0.03%]
基于日志的异常检测的机器学习技术综合研究
Shan Ali,Chaima Boufaied,Domenico Bianculli et al.
Shan Ali et al.
Growth in system complexity increases the need for automated techniques dedicated to different log analysis tasks such as Log-based Anomaly Detection (LAD). The latter has been widely addressed in the literature, mostly by means of a variet...
An empirical study of fault localisation techniques for deep neural networks [0.03%]
深度神经网络故障定位技术实证研究
Nargiz Humbatova,Jinhan Kim,Gunel Jahangirova et al.
Nargiz Humbatova et al.
With the increased popularity of Deep Neural Networks (DNNs), increases also the need for tools to assist developers in the DNN implementation, testing and debugging process. Several approaches have been proposed that automatically analyse ...
On the effects of program slicing for vulnerability detection during code inspection [0.03%]
关于代码审查时切片对漏洞检测的影响研究
Aurora Papotti,Katja Tuma,Fabio Massacci
Aurora Papotti
Slicing is a fault localization technique that has been proposed to support debugging and program comprehension. Yet, its empirical effectiveness during code inspection by humans has received limited attention. The goal of our study is two-...