报告详情
Human-AI Comparative Evaluation of Test Case Generation in Scenario-Oriented Software Testing
编号：142
访问权限：仅限参会人
更新：2025-12-23 13:18:11 浏览：109次
拓展类型2
报告开始：2025年12月30日 12:05（Asia/Amman）
报告时间：10min
所在会场：[S9] Track 5: Emerging Trends of AI/ML [S9-1] Track 5: Emerging Trends of AI/ML
摘要
This research evaluates the effectiveness of AI-generated test cases (using GPT-4) against test cases constructed using conventional manual testing approaches in scenario-driven software testing. Manual test cases developed by applying established black-box testing methods, while GPT-4 generated test cases through structured prompts. Three scenarios—easy, moderate, and complex—used to conduct the evaluation under equivalent conditions. The primary comparisons in the present study evaluated defect detection capability, test coverage, efficiency of execution, and scenario relevance. The results indicate that AI-generated test cases provide better coverage, are faster to generate, and more effectively detect edge case faults; notably when evaluating the complex scenario. Procedural/manual testing found to be stronger in contextual reasoning and for safety critical interpretation. Overall, this research concludes that AI-generated testing is a complement to procedural/manual testing methods not a replacement. The results support a "hybrid" testing approach for modern software testing and quality assurance.
关键词
Artificial Intelligence,GPT-4; Software Testing; Test Case Generation; Scenario-Driven Testing; Quality Assurance
报告人
Rawan Habarneh
Student zarqa university稿件作者
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重要日期
-
会议日期
12月29日
2025
至12月31日
2025
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12月30日 2025
报告提交截止日期
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02月10日 2026
初稿截稿日期
-
02月10日 2026
注册截止日期
主办单位
国际科学联合会
承办单位
扎尔卡大学
联系方式
- Miss AsianComNet
- as******@usssociety.org
历届会议
-
2024年10月24日 泰国 Bangkok
2024亚洲通讯与网络会议
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