Automatically inferring concern code from program investigation activities

When performing a program evolution task, developers typically spend a significant amount of effort investigating and re-investigating source code. To reduce this effort, we propose a technique to automatically infer the essence of program investigation activities as a set of concern descriptions. T...

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Published in18th IEEE International Conference on Automated Software Engineering, 2003. Proceedings pp. 225 - 234
Main Authors Robillard, Martin P., Murphy, Gail C.
Format Conference Proceeding
LanguageEnglish
Published Piscataway, NJ, USA IEEE Press 06.10.2003
IEEE
SeriesACM Conferences
Subjects
Online AccessGet full text
ISBN0769520359
9780769520353
ISSN1938-4300
DOI10.1109/ASE.2003.1240310

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Abstract When performing a program evolution task, developers typically spend a significant amount of effort investigating and re-investigating source code. To reduce this effort, we propose a technique to automatically infer the essence of program investigation activities as a set of concern descriptions. The concern descriptions produced by our technique list methods and fields of importance in the context of the investigation of an object-oriented system. A developer can rely on this information to perform the change task at hand, or at a later stage for a change that involves the same concerns. The technique involves applying an algorithm to a transcript of a program investigation session. The transcript lists which pieces of source code were accessed by a developer when investigating a program and how the different pieces of code were accessed. We applied the technique to data obtained from program investigation activities for five subjects involved in two different program evolution tasks. The results show that relevant concerns can be identified with a manageable level of noise.
AbstractList When performing a program evolution task, developers typically spend a significant amount of effort investigating and re-investigating source code. To reduce this effort, we propose a technique to automatically infer the essence of program investigation activities as a set of concern descriptions. The concern descriptions produced by our technique list methods and fields of importance in the context of the investigation of an object-oriented system. A developer can rely on this information to perform the change task at hand, or at a later stage for a change that involves the same concerns. The technique involves applying an algorithm to a transcript of a program investigation session. The transcript lists which pieces of source code were accessed by a developer when investigating a program and how the different pieces of code were accessed. We applied the technique to data obtained from program investigation activities for five subjects involved in two different program evolution tasks. The results show that relevant concerns can be identified with a manageable level of noise.
When performing a program evolution task, developers typically spend a significant amount of effort investigating and reinvestigating source code. To reduce this effort, we propose a technique to automatically infer the essence of program investigation activities as a set of concern descriptions. The concern descriptions produced by our technique list methods and fields of importance in the context of the investigation of an object-oriented system. A developer can rely on this information to perform the change task at hand, or at a later stage for a change that involves the same concerns. The technique involves applying an algorithm to a transcript of a program investigation session. The transcript lists which pieces of source code were accessed by a developer when investigating a program and how the different pieces of code were accessed. We applied the technique to data obtained from program investigation activities for five subjects involved in two different program evolution tasks. The results show that relevant concerns can be identified with a manageable level of noise.
Author Murphy, Gail C.
Robillard, Martin P.
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SubjectTerms Access protocols
Clustering algorithms
Computer science
Costs
Database systems
Documentation
Graphical user interfaces
Inference algorithms
Noise level
Scattering
Title Automatically inferring concern code from program investigation activities
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