Task-specific information retrieval systems for software engineers
This paper discusses the development of task-specific information retrieval systems for software engineers. We discuss how software engineers interact with information and information retrieval systems and investigate to what extent a domain-specific search and recommendation system can be developed...
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Veröffentlicht in: | Journal of computer and system sciences 2012-07, Vol.78 (4), p.1204-1218 |
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Hauptverfasser: | , |
Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | This paper discusses the development of task-specific information retrieval systems for software engineers. We discuss how software engineers interact with information and information retrieval systems and investigate to what extent a domain-specific search and recommendation system can be developed in order to support their work related activities. We have conducted a user study which is based on the “Cognitive Research Framework” to identify the relation between the information objects used during the code development (code snippets and search queries), the tasks users engage in and the associated use of search interfaces. Based on our user studies, a questionnaire and an automated observation of user interactions with the browser and software development environment, we identify that software engineers engage in a finite number of work related tasks and they also develop a finite number of “work practices”/“archetypes of behaviour”. Secondly we identify a group of domain specific behaviours that can successfully be used as a source of strong implicit relevance feedback. Based on our results, we design a snippet recommendation interface, and a code related recommendation interface which are embedded within the standard search engine.
► We investigate the information behaviour of software developers. ► We examine the potential software related implicit feedback indicators. ► Two user studies reveal the strengths of the investigated indicators of relevance. ► Information is copy and pasted frequently and only when it is relevant. ► Focus changes and build actions following IR are also strongly indicating relevance. |
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ISSN: | 0022-0000 1090-2724 |
DOI: | 10.1016/j.jcss.2011.10.009 |