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2012 Third International Workshop on Recommendation Systems for Software Engineering (RSSE)最新文献

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Recommending relevant code artifacts for change requests using multiple predictors 使用多个预测器为变更请求推荐相关的代码工件
2012 Third International Workshop on Recommendation Systems for Software Engineering (RSSE) Pub Date : 2012-06-04 DOI: 10.1109/RSSE.2012.6233416
Oliver Denninger
{"title":"Recommending relevant code artifacts for change requests using multiple predictors","authors":"Oliver Denninger","doi":"10.1109/RSSE.2012.6233416","DOIUrl":"https://doi.org/10.1109/RSSE.2012.6233416","url":null,"abstract":"Finding code artifacts affected by a given change request is a time-consuming process in large software systems. Various approaches have been proposed to automate this activity, e.g., based on information retrieval. The performance of a particular prediction approach often highly depends on attributes like coding style or writing style of change request. Thus, we propose to use multiple prediction approaches in combination with machine learning. First experiments show that machine learning is well suitable to weight different prediction approaches for individual software projects and hence improve prediction performance.","PeriodicalId":193223,"journal":{"name":"2012 Third International Workshop on Recommendation Systems for Software Engineering (RSSE)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129886019","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}
引用次数: 6
Harnessing Stack Overflow for the IDE 利用IDE的堆栈溢出
2012 Third International Workshop on Recommendation Systems for Software Engineering (RSSE) Pub Date : 2012-06-04 DOI: 10.1109/RSSE.2012.6233404
Alberto Bacchelli, Luca Ponzanelli, Michele Lanza
{"title":"Harnessing Stack Overflow for the IDE","authors":"Alberto Bacchelli, Luca Ponzanelli, Michele Lanza","doi":"10.1109/RSSE.2012.6233404","DOIUrl":"https://doi.org/10.1109/RSSE.2012.6233404","url":null,"abstract":"Developers often consult online tutorials and message boards to find solutions to their programming issues. Among the many online resources, Question & Answer websites are gaining popularity. This is no wonder if we consider a case like Stack Overflow, where more than 92% questions on expert topics are answered in a median time of 11 minutes. This new resource has scarcely been acknowledged by any Integrated Development Environment (IDE): Even though developers spend a large part of their working time in IDEs, and the usage of Q&A services has dramatically increased, developers can only use such resources using external applications. We introduce Seahawk, an Eclipse plugin to integrate Stack Overflow crowd knowledge in the IDE. It allows developers to seamlessly access Stack Overflow data, thus obtaining answers without switching the context. We present our preliminary work on Seahawk: It allows users to (1) retrieve Q&A from Stack Overflow, (2) link relevant discussions to any source code in Eclipse, and (3) attach explanative comments to the links.","PeriodicalId":193223,"journal":{"name":"2012 Third International Workshop on Recommendation Systems for Software Engineering (RSSE)","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130899019","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}
引用次数: 95
Group recommendation algorithms for requirements prioritization 需求优先级的分组推荐算法
2012 Third International Workshop on Recommendation Systems for Software Engineering (RSSE) Pub Date : 2012-06-04 DOI: 10.5555/2666719.2666733
A. Felfernig, G. Ninaus
{"title":"Group recommendation algorithms for requirements prioritization","authors":"A. Felfernig, G. Ninaus","doi":"10.5555/2666719.2666733","DOIUrl":"https://doi.org/10.5555/2666719.2666733","url":null,"abstract":"Group recommendation is successfully applied in different domains such as Interactive Television, Ambient Intelligence, and e-Tourism. The focus of this paper is to analyze the applicability of group recommendation to requirements prioritization. We provide an overview of relevant group recommendation heuristics and report the results of an empirical study which focused on the analysis of the prediction quality of these heuristics.","PeriodicalId":193223,"journal":{"name":"2012 Third International Workshop on Recommendation Systems for Software Engineering (RSSE)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114242531","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}
引用次数: 19
Interaction histories mining for software change guide 为软件变更指南挖掘交互历史
2012 Third International Workshop on Recommendation Systems for Software Engineering (RSSE) Pub Date : 2012-06-04 DOI: 10.1109/RSSE.2012.6233415
Takashi Kobayashi, Nozomu Kato, K. Agusa
{"title":"Interaction histories mining for software change guide","authors":"Takashi Kobayashi, Nozomu Kato, K. Agusa","doi":"10.1109/RSSE.2012.6233415","DOIUrl":"https://doi.org/10.1109/RSSE.2012.6233415","url":null,"abstract":"This paper presents a prediction model for change propagation based on the developers 'interaction history. Since artifacts have internal and external dependencies, a change will cause some changes on related artifacts. In order to guide change operations in software development, our proposed method generates a change guide graph by mining developers' interaction histories which consist of write and read accesses to artifacts. Using a change guide graph, we can guide change using the context of previous changes. To evaluate proposed change guide method, we perform a case study with an open-source software. We show that the context information is effective for file level and method level change predictions.","PeriodicalId":193223,"journal":{"name":"2012 Third International Workshop on Recommendation Systems for Software Engineering (RSSE)","volume":"243 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114999825","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}
引用次数: 12
A cost-benefit approach to recommending conflict resolution for parallel software development 为并行软件开发推荐冲突解决方案的成本效益方法
2012 Third International Workshop on Recommendation Systems for Software Engineering (RSSE) Pub Date : 2012-06-04 DOI: 10.1109/RSSE.2012.6233403
Nan Niu, Fangbo Yang, Jing-Ru C. Cheng, S. Reddivari
{"title":"A cost-benefit approach to recommending conflict resolution for parallel software development","authors":"Nan Niu, Fangbo Yang, Jing-Ru C. Cheng, S. Reddivari","doi":"10.1109/RSSE.2012.6233403","DOIUrl":"https://doi.org/10.1109/RSSE.2012.6233403","url":null,"abstract":"Merging parallel versions of source code is a common and essential activity during the lifespan of large-scale software systems. When a non-trivial number of conflicts is detected, there is a need to support the maintainer in investigating and resolving these conflicts. In this paper, we contribute a cost-benefit approach to ranking the conflicting software entities by leveraging both structural and semantic information of the source code. We present a study by applying our approach to a legacy system developed by computational scientists. The study not only demonstrates the feasibility of our approach, but also sheds light on the future development of conflict resolution recommenders.","PeriodicalId":193223,"journal":{"name":"2012 Third International Workshop on Recommendation Systems for Software Engineering (RSSE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127177396","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}
引用次数: 8
Facilitating reuse in model-based development with context-dependent model element recommendations 使用与上下文相关的模型元素建议促进基于模型的开发中的重用
2012 Third International Workshop on Recommendation Systems for Software Engineering (RSSE) Pub Date : 2012-06-04 DOI: 10.1109/RSSE.2012.6233402
L. Heinemann
{"title":"Facilitating reuse in model-based development with context-dependent model element recommendations","authors":"L. Heinemann","doi":"10.1109/RSSE.2012.6233402","DOIUrl":"https://doi.org/10.1109/RSSE.2012.6233402","url":null,"abstract":"Reuse recommendation systems suggest code entities useful for the task at hand within the IDE. Current approaches focus on code-based development. However, model-based development poses similar challenges to developers regarding the identification of useful elements in large and complex reusable modeling libraries. This paper proposes an approach for recommending library elements for domain specific languages. We instantiate the approach for Simulink models and evaluate it by recommending library blocks for a body of 165 Simulink files from a public repository. We compare two alternative variants for computing recommendations: association rules and collaborative filtering. Our results indicate that the collaborative filtering approach performs better and produces recommendations for Simulink models with satisfactory precision and recall.","PeriodicalId":193223,"journal":{"name":"2012 Third International Workshop on Recommendation Systems for Software Engineering (RSSE)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134066705","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}
引用次数: 10
Combining activity metrics and contribution topics for software recommendations 结合活动指标和软件推荐的贡献主题
2012 Third International Workshop on Recommendation Systems for Software Engineering (RSSE) Pub Date : 2012-06-04 DOI: 10.1109/RSSE.2012.6233408
K. Christidis, Fotis Paraskevopoulos, Dimitris Panagiotou, G. Mentzas
{"title":"Combining activity metrics and contribution topics for software recommendations","authors":"K. Christidis, Fotis Paraskevopoulos, Dimitris Panagiotou, G. Mentzas","doi":"10.1109/RSSE.2012.6233408","DOIUrl":"https://doi.org/10.1109/RSSE.2012.6233408","url":null,"abstract":"In this paper we outline work in progress for the development of a recommender system for open source software development communities that takes into account information from multiple sources. Specifically our approach combines latent semantics of contributed information artifacts with quantitative metrics that indicate developer activity.","PeriodicalId":193223,"journal":{"name":"2012 Third International Workshop on Recommendation Systems for Software Engineering (RSSE)","volume":"751 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116108446","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}
引用次数: 8
Optimizing a search-based code recommendation system 优化基于搜索的代码推荐系统
2012 Third International Workshop on Recommendation Systems for Software Engineering (RSSE) Pub Date : 2012-06-04 DOI: 10.1109/RSSE.2012.6233414
N. Murakami, H. Masuhara
{"title":"Optimizing a search-based code recommendation system","authors":"N. Murakami, H. Masuhara","doi":"10.1109/RSSE.2012.6233414","DOIUrl":"https://doi.org/10.1109/RSSE.2012.6233414","url":null,"abstract":"Search-based code recommendation systems with a large-scale code repository can provide the programmers example code snippets that teach them not only names in application programming interface of libraries and frameworks, but also practical usages consisting of multiple steps. However, it is not easy to optimize such systems because usefulness of recommended code is indirect and hard to be measured. We propose a method that mechanically evaluates usefulness for our recommendation system called Selene. By using the proposed method, we adjusted several search and user-interface parameters in Selene for better recall factor, and also learned characteristics of those parameters.","PeriodicalId":193223,"journal":{"name":"2012 Third International Workshop on Recommendation Systems for Software Engineering (RSSE)","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115365578","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}
引用次数: 11
Context-aware recommender systems for non-functional requirements 针对非功能性需求的上下文感知推荐系统
2012 Third International Workshop on Recommendation Systems for Software Engineering (RSSE) Pub Date : 2012-06-04 DOI: 10.1109/RSSE.2012.6233417
A. Danylenko, Welf Löwe
{"title":"Context-aware recommender systems for non-functional requirements","authors":"A. Danylenko, Welf Löwe","doi":"10.1109/RSSE.2012.6233417","DOIUrl":"https://doi.org/10.1109/RSSE.2012.6233417","url":null,"abstract":"For large software projects, system designers have to adhere to a significant number of functional and non-functional requirements, which makes software development a complex engineering task. If these requirements change during the development process, complexity even increases. In this paper, we suggest recommendation systems based on context-aware composition to enable a system designer to postpone and automate decisions regarding efficiency non-functional requirements, such as performance, and focus on the design of the core functionality of the system instead. Context-aware composition suggests the optimal component variants of a system for different static contexts (e.g., software and hardware environment) or even different dynamic contexts (e.g., actual parameters and resource utilization). Thus, an efficiency non-functional requirement can be automatically optimized statically or dynamically by providing possible component variants. Such a recommender system reduces time and effort spent on manually developing optimal applications that adapts to different (static or dynamic) contexts and even changes thereof.","PeriodicalId":193223,"journal":{"name":"2012 Third International Workshop on Recommendation Systems for Software Engineering (RSSE)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134498932","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}
引用次数: 20
Recommendations as learning: From discrepancies to software improvement 作为学习的建议:从差异到软件改进
2012 Third International Workshop on Recommendation Systems for Software Engineering (RSSE) Pub Date : 2012-06-04 DOI: 10.1109/RSSE.2012.6233405
K. Schneider, Stefan Gärtner, Tristan Wehrmaker, B. Brügge
{"title":"Recommendations as learning: From discrepancies to software improvement","authors":"K. Schneider, Stefan Gärtner, Tristan Wehrmaker, B. Brügge","doi":"10.1109/RSSE.2012.6233405","DOIUrl":"https://doi.org/10.1109/RSSE.2012.6233405","url":null,"abstract":"Successful software development requires software engineering skills as well as domain and user knowledge. This knowledge is difficult to master. Increasing complexity and fast evolving technologies cause deficits in development and system behavior. They cause discrepancies between expectations and observations. We propose using discrepancies as a trigger for recommendations to developers. Discrepancies in using a software application are combined with discrepancies between development artifacts. To efficiently support software engineers, recommendations must consider knowledge bases of discrepancies and resolution options. They evolve over time along with evolving experience. Hence, recommendations and organizational learning are intertwined.","PeriodicalId":193223,"journal":{"name":"2012 Third International Workshop on Recommendation Systems for Software Engineering (RSSE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130849588","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}
引用次数: 4
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