Please use this identifier to cite or link to this item:
https://doi.org/10.1109/ICSM.2011.6080788
DC Field | Value | |
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dc.title | An exploratory study of feature location process: Distinct phases, recurring patterns, and elementary actions | |
dc.contributor.author | Wang, J. | |
dc.contributor.author | Peng, X. | |
dc.contributor.author | Xing, Z. | |
dc.contributor.author | Zhao, W. | |
dc.date.accessioned | 2013-07-04T08:32:21Z | |
dc.date.available | 2013-07-04T08:32:21Z | |
dc.date.issued | 2011 | |
dc.identifier.citation | Wang, J.,Peng, X.,Xing, Z.,Zhao, W. (2011). An exploratory study of feature location process: Distinct phases, recurring patterns, and elementary actions. IEEE International Conference on Software Maintenance, ICSM : 213-222. ScholarBank@NUS Repository. <a href="https://doi.org/10.1109/ICSM.2011.6080788" target="_blank">https://doi.org/10.1109/ICSM.2011.6080788</a> | |
dc.identifier.isbn | 9781457706646 | |
dc.identifier.uri | http://scholarbank.nus.edu.sg/handle/10635/41645 | |
dc.description.abstract | Developers often have to locate the parts of the source code that contribute to a specific feature during software maintenance tasks. This activity, referred to as feature location in software engineering, is a human- and knowledge-intensive process. Researchers have investigated information retrieval, static/dynamic analysis based techniques to assist developers in such feature location activities. However, little work has been done on better understanding how developers perform feature location tasks. In this paper, we report an exploratory study of feature location process, consisting of two experiments in which developers were given unfamiliar systems and asked to complete six feature location tasks in two hours. Our study suggests that feature location process can be understood hierarchically at three levels of granularities: phase, pattern, and action. Furthermore, our study suggests that these feature-location phases, patterns and actions can be effectively imparted to junior developers and consequently improve their performance on feature location tasks. Our results open up new opportunities to feature location research, which could lead to better tool support and more rigorous feature location process. © 2011 IEEE. | |
dc.description.uri | http://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/ICSM.2011.6080788 | |
dc.source | Scopus | |
dc.subject | conceputal framework | |
dc.subject | feature location | |
dc.subject | human study | |
dc.type | Conference Paper | |
dc.contributor.department | COMPUTER SCIENCE | |
dc.description.doi | 10.1109/ICSM.2011.6080788 | |
dc.description.sourcetitle | IEEE International Conference on Software Maintenance, ICSM | |
dc.description.page | 213-222 | |
dc.identifier.isiut | NOT_IN_WOS | |
Appears in Collections: | Staff Publications |
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