T. Ishio, R. Kula, Tetsuya Kanda, D. Germán, Katsuro Inoue
{"title":"软件成分:Java软件发布中第三方组件复用的检测","authors":"T. Ishio, R. Kula, Tetsuya Kanda, D. Germán, Katsuro Inoue","doi":"10.1145/2901739.2901773","DOIUrl":null,"url":null,"abstract":"A software product is often dependent on a large number of third-party components.To assess potential risks, such as security vulnerabilities and license violations, a list of components and their versions in a product is important for release engineers and security analysts.Since such a list is not always available, a code comparison technique named Software Bertillonage has been proposed to test whether a product likely includes a copy of a particular component or not.Although the technique can extract candidates of reused components, a user still has to manually identify the original components among the candidates.In this paper, we propose a method to automatically select the most likely origin of components reused in a product, based on an assumption that a product tends to include an entire copy of a component rather than a partial copy.More concretely, given a Java product and a repository of jar files of existing components, our method selects jar files that can provide Java classes to the product in a greedy manner.To compare the method with the existing technique, we have conducted an evaluation using randomly created jar files including up to 1,000 components.The Software Bertillonage technique reports many candidates; the precision and recall are 0.357 and 0.993, respectively.Our method reports a list of original components whose precision and recall are 0.998 and 0.997.","PeriodicalId":6621,"journal":{"name":"2016 IEEE/ACM 13th Working Conference on Mining Software Repositories (MSR)","volume":"373 1","pages":"339-350"},"PeriodicalIF":0.0000,"publicationDate":"2016-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"19","resultStr":"{\"title\":\"Software Ingredients: Detection of Third-Party Component Reuse in Java Software Release\",\"authors\":\"T. Ishio, R. Kula, Tetsuya Kanda, D. Germán, Katsuro Inoue\",\"doi\":\"10.1145/2901739.2901773\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A software product is often dependent on a large number of third-party components.To assess potential risks, such as security vulnerabilities and license violations, a list of components and their versions in a product is important for release engineers and security analysts.Since such a list is not always available, a code comparison technique named Software Bertillonage has been proposed to test whether a product likely includes a copy of a particular component or not.Although the technique can extract candidates of reused components, a user still has to manually identify the original components among the candidates.In this paper, we propose a method to automatically select the most likely origin of components reused in a product, based on an assumption that a product tends to include an entire copy of a component rather than a partial copy.More concretely, given a Java product and a repository of jar files of existing components, our method selects jar files that can provide Java classes to the product in a greedy manner.To compare the method with the existing technique, we have conducted an evaluation using randomly created jar files including up to 1,000 components.The Software Bertillonage technique reports many candidates; the precision and recall are 0.357 and 0.993, respectively.Our method reports a list of original components whose precision and recall are 0.998 and 0.997.\",\"PeriodicalId\":6621,\"journal\":{\"name\":\"2016 IEEE/ACM 13th Working Conference on Mining Software Repositories (MSR)\",\"volume\":\"373 1\",\"pages\":\"339-350\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-05-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"19\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE/ACM 13th Working Conference on Mining Software Repositories (MSR)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2901739.2901773\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE/ACM 13th Working Conference on Mining Software Repositories (MSR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2901739.2901773","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Software Ingredients: Detection of Third-Party Component Reuse in Java Software Release
A software product is often dependent on a large number of third-party components.To assess potential risks, such as security vulnerabilities and license violations, a list of components and their versions in a product is important for release engineers and security analysts.Since such a list is not always available, a code comparison technique named Software Bertillonage has been proposed to test whether a product likely includes a copy of a particular component or not.Although the technique can extract candidates of reused components, a user still has to manually identify the original components among the candidates.In this paper, we propose a method to automatically select the most likely origin of components reused in a product, based on an assumption that a product tends to include an entire copy of a component rather than a partial copy.More concretely, given a Java product and a repository of jar files of existing components, our method selects jar files that can provide Java classes to the product in a greedy manner.To compare the method with the existing technique, we have conducted an evaluation using randomly created jar files including up to 1,000 components.The Software Bertillonage technique reports many candidates; the precision and recall are 0.357 and 0.993, respectively.Our method reports a list of original components whose precision and recall are 0.998 and 0.997.