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Using natural language program analysis to locate and understand action-oriented concerns
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Source Aspect-oriented software development; Vol. 208 archive
Proceedings of the 6th international conference on Aspect-oriented software development table of contents
Vancouver, British Columbia, Canada
SESSION: Aspect mining table of contents
Pages: 212 - 224  
Year of Publication: 2007
ISBN:1-59593-615-7
Authors
David Shepherd  University of Delaware, Newark, Delaware
Zachary P. Fry  University of Delaware, Newark, Delaware
Emily Hill  University of Delaware, Newark, Delaware
Lori Pollock  University of Delaware, Newark, Delaware
K. Vijay-Shanker  University of Delaware, Newark, Delaware
Sponsors
AOSA : Aspect-Oriented Software Association
: Google
IBMR : IBM Research
: Eclipse Foundation
: AOSD-Europe: European Network of Excellence on Aspect-Oriented Software Development
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 10,   Downloads (12 Months): 102,   Citation Count: 15
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ABSTRACT

Most current software systems contain undocumented high-level ideas implemented across multiple files and modules. When developers perform program maintenance tasks, they often waste time and effort locating and understanding these scattered concerns. We have developed a semi-automated concern location and comprehension tool, Find-Concept, designed to reduce the time developers spend on maintenance tasks and to increase their confidence in the results of these tasks. Find-Concept is effective because it searches a unique natural language-based representation of source code, uses novel techniques to expand initial queries into more effective queries, and displays search results in an easy-to-comprehend format. We describe the Find-Concept tool, the underlying program analysis, and an experimental study comparing Find-Concept's search effectiveness with two state-of-the-art lexical and information retrieval-based search tools. Across nine action-oriented concern location tasks derived from open source bug reports, our Eclipse-based tool produced more effective queries more consistently than either competing search tool with similar user effort.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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CITED BY  15

Collaborative Colleagues:
David Shepherd: colleagues
Zachary P. Fry: colleagues
Emily Hill: colleagues
Lori Pollock: colleagues
K. Vijay-Shanker: colleagues