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  1. Proceedings of the 3rd International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering (RAISE 2014)
  2. Supporting comprehension of unfamiliar programs by modeling an expert's perception
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Towards more intelligent trace retrieval algorithms
A mapping study on bayesian networks for software quality prediction
SANAYOJAN: a framework for traceability link recovery between use-cases in software requirement specification and regulatory documents
Supporting comprehension of unfamiliar programs by modeling an expert's perception
Machine learning for constituency test of coordinating conjunctions in requirements specifications
OCL usability: a major challenge in adopting UML
A self-learning approach for validation of communication in embedded systems
Deriving time lines from texts
Mining issue tracking systems using topic models for trend analysis, corpus exploration, and understanding evolution

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Supporting comprehension of unfamiliar programs by modeling an expert's perception

Content Provider ACM Digital Library
Author Kulkarni, Naveen Varma, Vasudeva
Abstract Developers need to understand many Software Engineering (SE) artifacts while making changes to the code. In such cases, developers use cues extensively to establish relevance of an information with the task. Their familiarity with different kind of cues will help them in comprehending a program. But, developers face information overload because (a) there are many cues and (b) they might be unfamiliar with artifacts. So, we propose a novel approach to overcome information overload problem by modeling developer's perceived value of information based on cues. In this preliminary study, we validate one such model for common comprehension tasks. We also apply this model to summarize source code. An evaluation of the generated summaries resulted in 83% similarity with summaries recorded by developers. The promising results encourages us to create a repository of perception models that can later aid complex SE tasks. .
Starting Page 19
Ending Page 24
Page Count 6
File Format PDF
ISBN 9781450328463
DOI 10.1145/2593801.2593805
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2014-06-03
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Program comprehension Information scent Summarization
Content Type Text
Resource Type Article
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