Software developers' information needs: towards the development of intelligent recommender systems
Software development is a process which is significantly reliable on information and in the context of the Internet on Information Retrieval (IR) tools. Approximately 20%-30% of work time of software developers is spent on information retrieval and this proportion would be significantly higher if it were not for time constraints and pressure to deliver code. Even though a number of IR solutions exist, 86% of work-related search sessions start with a general purpose search engine. Therefore there exists a significant potential for research and development of ubiquitous, domain specific tools to support the IR process. This paper discusses how the knowledge of work tasks and information needs of software developers can be used to deliver ubiquitous, highly contextsensitive search and intelligent recommendation tools. We present a detailed review of software developers' work related tasks and habits. We also discuss factors that can be used as implicit feedback indicators for further collaborative filtering.
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Software developers' information needs: towards the development of intelligent recommender systems
Semantic Scholar · Computer Science · 2011
Abstract
Software development is a process which is significantly reliable on information and in the context of the Internet on Information Retrieval (IR) tools. Approximately 20%-30% of work time of software developers is spent on information retrieval and this proportion would be significantly higher if it were not for time constraints and pressure to deliver code. Even though a number of IR solutions exist, 86% of work-related search sessions start with a general purpose search engine. Therefore there exists a significant potential for research and development of ubiquitous, domain specific tools to support the IR process. This paper discusses how the knowledge of work tasks and information needs of software developers can be used to deliver ubiquitous, highly contextsensitive search and intelligent recommendation tools. We present a detailed review of software developers' work related tasks and habits. We also discuss factors that can be used as implicit feedback indicators for further collaborative filtering.