The success of open source software (OSS) is completely dependent on the work of volunteers who contribute their time and talents. The submission of patches is the major way that participants outside of the core group of developers make contributions. We argue that the process of patch submission and acceptance into the codebase is an important piece of the open source puzzle and that the use of patch-related data can be helpful in understanding how OSS projects work. We present our methods in identifying the submission and acceptance of patches and give results and evaluation in applying these methods to the Apache webserver, Python interpreter, Postgres SQL database, and (with limitations) MySQL database projects. In addition, we present valuable ways in which this data has been and can be used.
{"title":"Detecting Patch Submission and Acceptance in OSS Projects","authors":"C. Bird, A. Gourley, Premkumar T. Devanbu","doi":"10.1109/MSR.2007.6","DOIUrl":"https://doi.org/10.1109/MSR.2007.6","url":null,"abstract":"The success of open source software (OSS) is completely dependent on the work of volunteers who contribute their time and talents. The submission of patches is the major way that participants outside of the core group of developers make contributions. We argue that the process of patch submission and acceptance into the codebase is an important piece of the open source puzzle and that the use of patch-related data can be helpful in understanding how OSS projects work. We present our methods in identifying the submission and acceptance of patches and give results and evaluation in applying these methods to the Apache webserver, Python interpreter, Postgres SQL database, and (with limitations) MySQL database projects. In addition, we present valuable ways in which this data has been and can be used.","PeriodicalId":201749,"journal":{"name":"Fourth International Workshop on Mining Software Repositories (MSR'07:ICSE Workshops 2007)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114865536","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Many software projects fail to deliver their needed results on-time and on-budget. There are a variety of reasons why this may occur. For some of these reasons (notably deterioration of the codebase), corrective action is often difficult to cost-justify or to implement efficiently in practice. To address this, an approach of lightweight risk mitigation is proposed: mine risk data from configuration management and defect tracking systems, integrate this data with project-cost data in a flexible dashboard, and facilitate strategic refactoring with semi-custom transforms where necessary. This prescriptive information would simultaneously help the project manager to cost-justify repair efforts and lowers the cost of finding and fixing hot spots.
{"title":"Lightweight Risk Mitigation for Software Development Projects Using Repository Mining","authors":"S. P. Masticola","doi":"10.1109/MSR.2007.16","DOIUrl":"https://doi.org/10.1109/MSR.2007.16","url":null,"abstract":"Many software projects fail to deliver their needed results on-time and on-budget. There are a variety of reasons why this may occur. For some of these reasons (notably deterioration of the codebase), corrective action is often difficult to cost-justify or to implement efficiently in practice. To address this, an approach of lightweight risk mitigation is proposed: mine risk data from configuration management and defect tracking systems, integrate this data with project-cost data in a flexible dashboard, and facilitate strategic refactoring with semi-custom transforms where necessary. This prescriptive information would simultaneously help the project manager to cost-justify repair efforts and lowers the cost of finding and fixing hot spots.","PeriodicalId":201749,"journal":{"name":"Fourth International Workshop on Mining Software Repositories (MSR'07:ICSE Workshops 2007)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116546397","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
One of the most important decisions researchers face when analyzing the evolution of software systems is the choice of a proper data analysis/exchange format. Most existing formats have to be processed with special programs written specifically for that purpose and are not easily extendible. Most scientists, therefore, use their own data-base(s) requiring each of them to repeat the work of writing the import/export programs to their format. We present EvoOnt, a software repository data exchange format based on the Web Ontology Language (OWL). EvoOnt includes software, release, and bug-related information. Since OWL describes the semantics of the data, EvoOnt is (1) easily extendible, (2) comes with many existing tools, and (3) allows to derive assertions through its inherent Description Logic reasoning capabilities. The paper also shows iSPARQL -our SPARQL-based Semantic Web query engine containing similarity joins. Together with EvoOnt, iSPARQL can accomplish a sizable number of tasks sought in software repository mining projects, such as an assessment of the amount of change between versions or the detection of bad code smells. To illustrate the usefulness of EvoOnt (and iSPARQL), we perform a series of experiments with a real-world Java project. These show that a number of software analyses can be reduced to simple iSPARQL queries on an EvoOnt dataset.
{"title":"Mining Software Repositories with iSPAROL and a Software Evolution Ontology","authors":"Christoph Kiefer, A. Bernstein, Jonas Tappolet","doi":"10.1109/MSR.2007.21","DOIUrl":"https://doi.org/10.1109/MSR.2007.21","url":null,"abstract":"One of the most important decisions researchers face when analyzing the evolution of software systems is the choice of a proper data analysis/exchange format. Most existing formats have to be processed with special programs written specifically for that purpose and are not easily extendible. Most scientists, therefore, use their own data-base(s) requiring each of them to repeat the work of writing the import/export programs to their format. We present EvoOnt, a software repository data exchange format based on the Web Ontology Language (OWL). EvoOnt includes software, release, and bug-related information. Since OWL describes the semantics of the data, EvoOnt is (1) easily extendible, (2) comes with many existing tools, and (3) allows to derive assertions through its inherent Description Logic reasoning capabilities. The paper also shows iSPARQL -our SPARQL-based Semantic Web query engine containing similarity joins. Together with EvoOnt, iSPARQL can accomplish a sizable number of tasks sought in software repository mining projects, such as an assessment of the amount of change between versions or the detection of bad code smells. To illustrate the usefulness of EvoOnt (and iSPARQL), we perform a series of experiments with a real-world Java project. These show that a number of software analyses can be reduced to simple iSPARQL queries on an EvoOnt dataset.","PeriodicalId":201749,"journal":{"name":"Fourth International Workshop on Mining Software Repositories (MSR'07:ICSE Workshops 2007)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129988969","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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