More Web Proxy on the site http://driver.im/

Article

Challenges of using LSI for concept location

Authors:

Shaochun XuAuthors Info & Claims

ACMSE '07: Proceedings of the 45th annual ACM Southeast Conference

Pages 449 - 454

https://doi.org/10.1145/1233341.1233422

Published: 23 March 2007 Publication History

Abstract

Encouraged by the successful application of Latent Semantic Indexing (LSI) in natural language analysis and web search engines, researchers recently adopted the LSI technique to locate the source code where a specific feature was implemented, which is called concept location. However, such applications are still at an early stage and need more validation. This paper tries to discuss in depth some challenges of using LSI technique in concept location, both theoretically and practically, with a hope that this work could lead a good research direction to tackle those challenges so that the LSI can be effectively used in concept location.

References

[1]

Apache Tomcat, http://tomcat.apache.org/

[2]

The Java Platform, http://java.sun.com/javase/

[3]

Chen, K. and Rajlich, V., Case Study of Feature Location Using Dependence Graph, In Proceedings of 8th IEEE International Workshop on Program Comprehension (IWPC'00), pp. 241--249, Limerick, Ireland, 2000.

Digital Library

[4]

Deerwester, Scott C. (Chicago, I., Dumais; Susan T. (Berkeley Heights, NJ), Furnas; George W. (Madison, NJ), Harshman; Richard A. (London, CA), Landauer, Thomas K. (Summit, NJ), Lochbaum; Karen E. (Chatham, NJ), Streeter, Lynn A. (Summit, NJ) "Computer information retrieval using latent semantic structure," U. S. Patent, Ed. USA: Bell Communications Research, Inc. (Livingston, NJ), 1989.

[5]

Deissenboeck, F. and Pizka, M., Concise and Consistent Naming, In Proceedings of 13th International Workshop on Program Comprehension (IWPC'05), pp. 97--106, St. Louis, Missouri, USA, 2005.

Digital Library

[6]

Google, http://www.google.com/

[7]

Google Desktop, http://desktop.google.com/

[8]

Maletic, J. I. and Marcus, A., Supporting Program Comprehension Using Semantic and Structural Information, In Proceedings of 23rd International Conference on Software Engineering (ICSE'01), pp. 103--112, Toronto, Ontario, Canada, 2001.

Digital Library

[9]

Marcus, A., Rajlich, V., Buchta, J., Petrenko, M., and Sergeyev, A., Static Techniques for Concept Location in Object-Oriented Code, In Proceedings of 13th IEEE International Workshop on Program Comprehension (IWPC'05), pp. 33--42, St. Louis, Missouri, USA, 2005.

Digital Library

[10]

Marcus, A., Sergeyev, A., Rajlich, V., and Maletic, J., An Information Retrieval Approach to Concept Location in Source Code, In Proceedings of 11th IEEE Working Conference on Reverse Engineering (WCRE2004), pp. 214--223, Delft, The Netherlands, 2004.

Digital Library

[11]

Poshyvanyk, D., Gueheneuc, Y.-G., Marcus, A., Antoniol, G., and Rajlich, V., Combining Probabilistic Ranking and Latent Semantic Indexing for Feature Identification, In Proceedings of 14th IEEE International Conference on Program Comprehension, pp. 137--148, Athens, Greece, 2006.

Digital Library

[12]

Poshyvanyk, D., Petrenko, M., Marcus, A., Xie, X., and Liu, D., Google Eclipse Search, In Proceedings of IEEE International Conference on Software Maintenance, Philadelphia, Pennsylvania, USA, 2006.

[13]

Rajlich, V. and Wilde, N., The Role of Concepts in Program Comprehension, In Proceedings of IEEE International Workshop on Program Comprehension (IWPC'02), pp. 271--278, Paris, France, 2002.

Digital Library

[14]

Salton, G. and McGill, M., Introduction to Modern Information Retrieval: McGraw-Hill, 1983.

Digital Library

[15]

Wilde, N. and Scully, M., "Software Reconnaissance: Mapping Program Features to Code," Software Maintenance: Research and Practice, vol. 7, pp. 49--62, 1995.

Digital Library

[16]

Wong, E., Gokhale, W., S., S., and Horgan, J. R., "Quantifying the closeness between program components and features," Journal of Systems and Software, vol. 54, pp. 87--98, 2000.

Digital Library

Cited By

CAI ZYANG XWANG XKAVS A(2012)Feature Location in Source Code by Trace-Based Impact Analysis and Information RetrievalIEICE Transactions on Information and Systems10.1587/transinf.E95.D.205E95-D:1(205-214)Online publication date: 2012
https://doi.org/10.1587/transinf.E95.D.205
Bernau DMordvinova OKarstens JHickl S(2011)Investigating influence of data storage organization on structured code search performance2011 IEEE 2nd International Conference on Computing, Control and Industrial Engineering10.1109/CCIENG.2011.6008112(247-250)Online publication date: Aug-2011
https://doi.org/10.1109/CCIENG.2011.6008112
Panchenko OPlattner HZeier A(2011)Efficient storage and fast querying of source codeInformation Systems Frontiers10.1007/s10796-010-9285-613:3(349-357)Online publication date: 1-Jul-2011
https://dl.acm.org/doi/10.1007/s10796-010-9285-6
Show More Cited By

Index Terms

Challenges of using LSI for concept location
1. Software and its engineering
  1. Software creation and management
    1. Software post-development issues
      1. Software reverse engineering

Recommendations

Concept location using formal concept analysis and information retrieval

The article addresses the problem of concept location in source code by proposing an approach that combines Formal Concept Analysis and Information Retrieval. In the proposed approach, Latent Semantic Indexing, an advanced Information Retrieval approach,...
Concept location using program dependencies and information retrieval (DepIR)

ContextThe functionality of a software system is most often expressed in terms of concepts from its problem or solution domains. The process of finding where these concepts are implemented in the source code is known as concept location and it is a ...
On the Effect of the Query in IR-based Concept Location
ICPC '11: Proceedings of the 2011 IEEE 19th International Conference on Program Comprehension

Concept location is an essential task during software maintenance and in particular program comprehension activities. One of the approaches to this task is the based on leveraging the lexical information found in the source code by means of Information ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Conferences

ACMSE '07: Proceedings of the 45th annual ACM Southeast Conference

March 2007

574 pages

ISBN:9781595936295

DOI:10.1145/1233341

Conference Chairs:
David John
Wake Forest University
,
Sandria Kerr
Winston-Salem State University

Copyright © 2007 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

SIGAPP: ACM Special Interest Group on Applied Computing

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 23 March 2007

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Article

Conference

ACM SE07

Sponsor:

SIGAPP

ACM SE07: ACM Southeast Regional Conference

March 23 - 24, 2007

North Carolina, Winston-Salem

Acceptance Rates

ACMSE '07 Paper Acceptance Rate 81 of 137 submissions, 59%;

Overall Acceptance Rate 502 of 1,023 submissions, 49%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

4
Total Citations
View Citations
253
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 11 Dec 2024

Other Metrics

View Author Metrics

Citations

Cited By

CAI ZYANG XWANG XKAVS A(2012)Feature Location in Source Code by Trace-Based Impact Analysis and Information RetrievalIEICE Transactions on Information and Systems10.1587/transinf.E95.D.205E95-D:1(205-214)Online publication date: 2012
https://doi.org/10.1587/transinf.E95.D.205
Bernau DMordvinova OKarstens JHickl S(2011)Investigating influence of data storage organization on structured code search performance2011 IEEE 2nd International Conference on Computing, Control and Industrial Engineering10.1109/CCIENG.2011.6008112(247-250)Online publication date: Aug-2011
https://doi.org/10.1109/CCIENG.2011.6008112
Panchenko OPlattner HZeier A(2011)Efficient storage and fast querying of source codeInformation Systems Frontiers10.1007/s10796-010-9285-613:3(349-357)Online publication date: 1-Jul-2011
https://dl.acm.org/doi/10.1007/s10796-010-9285-6
Panchenko O(2009)Hybrid storage for enabling fully-featured text search and fine-grained structural search over source codeProceedings of the 2009 ICSE Workshop on Search-Driven Development-Users, Infrastructure, Tools and Evaluation10.1109/SUITE.2009.5070019(37-40)Online publication date: 16-May-2009
https://dl.acm.org/doi/10.1109/SUITE.2009.5070019

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Table of Contents