loading...
 This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
18th IEEE International Conference on Automated Software Engineering (ASE'03)
Automatically Inferring Concern Code from Program Investigation Activities
Montreal, Quebec, Canada
October 06-October 10
ISBN: 0-7695-2035-9
Martin P. Robillard, University of British Columbia
Gail C. Murphy, University of British Columbia
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.
Citation:
Martin P. Robillard, Gail C. Murphy, "Automatically Inferring Concern Code from Program Investigation Activities," ase, pp.225, 18th IEEE International Conference on Automated Software Engineering (ASE'03), 2003
Usage of this product signifies your acceptance of the Terms of Use.