<b>MSR'2026 Mining Challenge:</b>

Name: MSR'2026 Mining Challenge:
Creator: Heydarnoori, Abbas
Published: 2025-12-31T00:00:00+08:00

Figshare2025-12-31 更新2026-04-08 收录

AI辅助软件测试

测试故障模式分析

数据链接：

https://figshare.com/articles/dataset/_b_MSR_2026_Mining_Challenge_b_/30978772/1 数据链接链接失效反馈

官方服务：

资源简介：

<b>MSR'2026 Mining Challenge:</b> AI-Generated Test Failures in Action: An Empirical Analysis of Failure and Recovery Patterns

提供机构：

Heydarnoori, Abbas

创建时间：

2025-12-31

Replication Package for: Understanding LLM-Driven Test Oracle Generation - AIWare 2025

AI辅助软件测试

测试预言生成

Understanding LLM-Driven Test Oracle GenerationAuthors: Adam Bodicoat, Gunel Jahangirova, Valerio TerragniAIware 2025 – 2nd ACM International Conference on AI-powered Software(19–20 Nov 2025, Seoul, S

Figshare2025-10-29 更新50

ICEIS 2025 - Support Documentation for Study Execution - "Exploring the Use of ChatGPT for the Generation of User Story Based Test Cases: An Experimental Study"

AI辅助软件测试

测试用例生成

This is the dataset and documents used for the study execution provided by the authors. In this raw data, you can find the scripts used by the evaluators and the TAM form submitted by them during the

Figshare2025-02-13 更新20

Supportive generation of Test Scenarios in INGenious using scriptless AI-agents

AI辅助软件测试

低代码测试自动化

TESTAR is a scriptless, automated, open-source testing tool developed by the Universitat Politècnica de València and the Open Universiteit of the Netherlands. INGenious is an open-source Low-Code/No-

Zenodo2026-06-01 更新10

LLMShot: Reducing snapshot testing maintanence via LLMs

UI快照测试自动化

AI辅助软件测试

Replication Package for: LLMShot: Reducing snapshot testing maintanence via LLMs This package replicates the study presented in the paper "LLMShot: Reducing Snapshot Testing Maintenance via LLMs". Th

Zenodo2025-07-14 更新30

Replication Package for "Improving LLM-Driven Test Generation by Learning from Mocking Information" (AIST 2026)

AI辅助软件测试

测试生成

Improving LLM-Driven Test Generation by Learning from Mocking Information (AIST 2026) — Replication Package Authors:Jamie Lee*, Flynn Teh*, Hengcheng Zhu†, Mengzhen Li‡, Mattia Fazzini‡, Valerio Terr

Zenodo2026-04-10 更新10

<b>MSR'2026 Mining Challenge:</b>

资源简介：

相关数据集