{"title":"使用深度强化学习生成API测试数据","authors":"Steyn Huurman, Xiaoying Bai, Thomas Hirtz","doi":"10.1145/3387940.3392214","DOIUrl":null,"url":null,"abstract":"Testing is critical to ensure the quality of widely-used web APIs. Automatic test data generation can help to reduce cost and improve overall effectiveness. This is commonly accomplished by using the powerful concept of search-based software testing (SBST). However, with web APIs growing larger and larger, SBST techniques face scalability challenges. This paper introduces a novel SBST based approach for generating API test data using deep reinforcement learning (DRL) as the search algorithm. By exploring the benefits of DRL in the context of scalable API test data generation, we show its potential as alternative to traditional search algorithms.","PeriodicalId":309659,"journal":{"name":"Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Generating API Test Data Using Deep Reinforcement Learning\",\"authors\":\"Steyn Huurman, Xiaoying Bai, Thomas Hirtz\",\"doi\":\"10.1145/3387940.3392214\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Testing is critical to ensure the quality of widely-used web APIs. Automatic test data generation can help to reduce cost and improve overall effectiveness. This is commonly accomplished by using the powerful concept of search-based software testing (SBST). However, with web APIs growing larger and larger, SBST techniques face scalability challenges. This paper introduces a novel SBST based approach for generating API test data using deep reinforcement learning (DRL) as the search algorithm. By exploring the benefits of DRL in the context of scalable API test data generation, we show its potential as alternative to traditional search algorithms.\",\"PeriodicalId\":309659,\"journal\":{\"name\":\"Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-06-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3387940.3392214\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3387940.3392214","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Generating API Test Data Using Deep Reinforcement Learning
Testing is critical to ensure the quality of widely-used web APIs. Automatic test data generation can help to reduce cost and improve overall effectiveness. This is commonly accomplished by using the powerful concept of search-based software testing (SBST). However, with web APIs growing larger and larger, SBST techniques face scalability challenges. This paper introduces a novel SBST based approach for generating API test data using deep reinforcement learning (DRL) as the search algorithm. By exploring the benefits of DRL in the context of scalable API test data generation, we show its potential as alternative to traditional search algorithms.