Luca Ponzanelli, Simone Scalabrino, G. Bavota, Andrea Mocci, R. Oliveto, M. D. Penta, Michele Lanza
{"title":"Supporting Software Developers with a Holistic Recommender System","authors":"Luca Ponzanelli, Simone Scalabrino, G. Bavota, Andrea Mocci, R. Oliveto, M. D. Penta, Michele Lanza","doi":"10.1109/ICSE.2017.17","DOIUrl":null,"url":null,"abstract":"The promise of recommender systems is to provide intelligent support to developers during their programming tasks. Such support ranges from suggesting program entities to taking into account pertinent Q&A pages. However, current recommender systems limit the context analysis to change history and developers' activities in the IDE, without considering what a developer has already consulted or perused, e.g., by performing searches from the Web browser. Given the faceted nature of many programming tasks, and the incompleteness of the information provided by a single artifact, several heterogeneous resources are required to obtain the broader picture needed by a developer to accomplish a task. We present Libra, a holistic recommender system. It supports the process of searching and navigating the information needed by constructing a holistic meta-information model of the resources perused by a developer, analyzing their semantic relationships, and augmenting the web browser with a dedicated interactive navigation chart. The quantitative and qualitative evaluation of Libra provides evidence that a holistic analysis of a developer's information context can indeed offer comprehensive and contextualized support to information navigation and retrieval during software development.","PeriodicalId":6505,"journal":{"name":"2017 IEEE/ACM 39th International Conference on Software Engineering (ICSE)","volume":"47 1","pages":"94-105"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"41","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE/ACM 39th International Conference on Software Engineering (ICSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSE.2017.17","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 41
Abstract
The promise of recommender systems is to provide intelligent support to developers during their programming tasks. Such support ranges from suggesting program entities to taking into account pertinent Q&A pages. However, current recommender systems limit the context analysis to change history and developers' activities in the IDE, without considering what a developer has already consulted or perused, e.g., by performing searches from the Web browser. Given the faceted nature of many programming tasks, and the incompleteness of the information provided by a single artifact, several heterogeneous resources are required to obtain the broader picture needed by a developer to accomplish a task. We present Libra, a holistic recommender system. It supports the process of searching and navigating the information needed by constructing a holistic meta-information model of the resources perused by a developer, analyzing their semantic relationships, and augmenting the web browser with a dedicated interactive navigation chart. The quantitative and qualitative evaluation of Libra provides evidence that a holistic analysis of a developer's information context can indeed offer comprehensive and contextualized support to information navigation and retrieval during software development.