Skip to main content
Top

2017 | OriginalPaper | Chapter

TEXAS2: A System for Extracting Domain Topic Using Link Analysis and Searching for Relevant Features

Authors : SangWon Hwang, YongSeok Lee, YoungKwang Nam

Published in: Advances in Computer Science and Ubiquitous Computing

Publisher: Springer Singapore

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

It is very important to understand the domain topic of software to maintain and reuse it. However, the continual development and change in its size makes it difficult to understand it. To solve this problem, researches have been recently conducted to extract the domain topic using various information search techniques such as LDA, with the researches on LDA-based techniques being especially active. However, since only unstructured information such as an identifier or note is used in most research, without including structured ones like information calling, problems in which extracted topics are different from the characteristics of the program can occur. In this paper, we propose a method to generate documents and extract topics using both structured and unstructured information. We also generate indexes based on the frequency of the identifier of the source code, and propose a system that extracts an association rule based on the simultaneous generation of the method. We as well establish a system that provides highly reliable search results to user queries by combining domain topics, indexes with scores, and the association rule information. Consequently a TEXAS2 system for this study was established and confirmed a high user satisfaction on search results to the queries in a performance test.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Literature
1.
go back to reference Antoniol, G., Guéhéneuc, Y. G.: Feature identification: an epidemiological metaphor. IEEE Trans. Softw. Eng. 32(9), 627–641. IEEE Press, New York (2006) Antoniol, G., Guéhéneuc, Y. G.: Feature identification: an epidemiological metaphor. IEEE Trans. Softw. Eng. 32(9), 627–641. IEEE Press, New York (2006)
2.
go back to reference Karrer, T., Krämer, J.P., Diel, J., Hartmann, B.: Stacksplorer: call graph navigation helps increasing code maintenance efficiency. In: Proceedings of the 24th Annual ACM Symposium on User Interface Software and Technology, pp. 217–224. ACM, New York (2011) Karrer, T., Krämer, J.P., Diel, J., Hartmann, B.: Stacksplorer: call graph navigation helps increasing code maintenance efficiency. In: Proceedings of the 24th Annual ACM Symposium on User Interface Software and Technology, pp. 217–224. ACM, New York (2011)
3.
go back to reference Maskeri, G., Sarkar, S., Heafield, K.: Mining business topics in source code using Latent Dirichlet Allocation. In: Proceedings of the 1st India Software Engineering Conference, pp. 113–120. ACM, New York (2008) Maskeri, G., Sarkar, S., Heafield, K.: Mining business topics in source code using Latent Dirichlet Allocation. In: Proceedings of the 1st India Software Engineering Conference, pp. 113–120. ACM, New York (2008)
4.
go back to reference Alenezi, M.: Extracting high-level concepts from open-source systems. Intl. J. Softw. Eng. Appl. 9(1), 183–190 (2015). SERSC, Tasmania Alenezi, M.: Extracting high-level concepts from open-source systems. Intl. J. Softw. Eng. Appl. 9(1), 183–190 (2015). SERSC, Tasmania
5.
go back to reference McBurney, P.W., Liu, C., McMillan, C., Weninger, T.: Improving topic model source code summarization. In: Proceedings of the 22nd International Conference on Program Comprehension, pp. 291–294. ACM, New York (2014) McBurney, P.W., Liu, C., McMillan, C., Weninger, T.: Improving topic model source code summarization. In: Proceedings of the 22nd International Conference on Program Comprehension, pp. 291–294. ACM, New York (2014)
6.
go back to reference Savage, T., Dit, B., Gethers, M., Poshyvank, D.: Topic XP: exploring topics in source code using Latent Dirichlet Allocation. In: IEEE International Conference on Software Maintenance, pp. 1–6. IEEE Press, New York (2010) Savage, T., Dit, B., Gethers, M., Poshyvank, D.: Topic XP: exploring topics in source code using Latent Dirichlet Allocation. In: IEEE International Conference on Software Maintenance, pp. 1–6. IEEE Press, New York (2010)
7.
go back to reference Slimani, T., Lazzez, A.: Sequential mining: patterns and algorithms analysis. Intl. J. Comput. Electron. Res. 2, 639–647 (2013) Slimani, T., Lazzez, A.: Sequential mining: patterns and algorithms analysis. Intl. J. Comput. Electron. Res. 2, 639–647 (2013)
10.
go back to reference Blei, D., Ng, A., Jordan, M.: Latent Dirichlet Allocation. J. Mach. Learn. Res. 3, 993–1022 (2003). MIT Press, Cambridge Blei, D., Ng, A., Jordan, M.: Latent Dirichlet Allocation. J. Mach. Learn. Res. 3, 993–1022 (2003). MIT Press, Cambridge
11.
go back to reference Blei, D.: Probabilistic topic models. Commun. ACM 55(4), 77–84 (2012). ACM, New York Blei, D.: Probabilistic topic models. Commun. ACM 55(4), 77–84 (2012). ACM, New York
12.
go back to reference Brin, S., Page, L.: The anatomy of a large-scale hypertextual web search engine. J. Comput. Netw. ISDN Syst. 30, 107–117 (1998). Amsterdam Brin, S., Page, L.: The anatomy of a large-scale hypertextual web search engine. J. Comput. Netw. ISDN Syst. 30, 107–117 (1998). Amsterdam
13.
go back to reference Agrawal, R., Srikant, R.: Fast algorithms for mining association rules. In: Proceedings of the 20th VLDB Conference Agrawal, R., Srikant, R.: Fast algorithms for mining association rules. In: Proceedings of the 20th VLDB Conference
Metadata
Title
TEXAS2: A System for Extracting Domain Topic Using Link Analysis and Searching for Relevant Features
Authors
SangWon Hwang
YongSeok Lee
YoungKwang Nam
Copyright Year
2017
Publisher
Springer Singapore
DOI
https://doi.org/10.1007/978-981-10-3023-9_113