{"title":"生成格式良好的q#量子模糊测试程序的初步研究","authors":"Miguel Trinca, J. Ferreira, Rui Abreu","doi":"10.1109/ICSTW55395.2022.00033","DOIUrl":null,"url":null,"abstract":"Generative Sequence-To-Sequence models have been proposed for the task of generating well-formed programs, an important task for fuzz testing tools such as compilers. In this paper, we propose a Sequence-to-Sequence model to generate well-formed Q# Quantum programs. The ratio of syntactically valid programs among 1,000 Q# files generated by our model is 79.6%. In addition, we also contribute with a dataset of 1,723 Q# files taken from publicly available repositories on GitHub, which can be used by the growing community of Quantum Software Engineering.","PeriodicalId":147133,"journal":{"name":"2022 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A Preliminary Study on Generating Well-Formed Q# Quantum Programs for Fuzz Testing\",\"authors\":\"Miguel Trinca, J. Ferreira, Rui Abreu\",\"doi\":\"10.1109/ICSTW55395.2022.00033\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Generative Sequence-To-Sequence models have been proposed for the task of generating well-formed programs, an important task for fuzz testing tools such as compilers. In this paper, we propose a Sequence-to-Sequence model to generate well-formed Q# Quantum programs. The ratio of syntactically valid programs among 1,000 Q# files generated by our model is 79.6%. In addition, we also contribute with a dataset of 1,723 Q# files taken from publicly available repositories on GitHub, which can be used by the growing community of Quantum Software Engineering.\",\"PeriodicalId\":147133,\"journal\":{\"name\":\"2022 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW)\",\"volume\":\"64 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSTW55395.2022.00033\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSTW55395.2022.00033","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Preliminary Study on Generating Well-Formed Q# Quantum Programs for Fuzz Testing
Generative Sequence-To-Sequence models have been proposed for the task of generating well-formed programs, an important task for fuzz testing tools such as compilers. In this paper, we propose a Sequence-to-Sequence model to generate well-formed Q# Quantum programs. The ratio of syntactically valid programs among 1,000 Q# files generated by our model is 79.6%. In addition, we also contribute with a dataset of 1,723 Q# files taken from publicly available repositories on GitHub, which can be used by the growing community of Quantum Software Engineering.
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