Skip to main content

Using Semantic Networks and Context in Search for Relevant Software Engineering Artifacts

  • Chapter
Journal on Data Semantics XIV

Abstract

The discovery of relevant software artifacts can increase software reuse and reduce the cost of software development and maintenance. Furthermore, change requests, which are a leading cause of project failures, can be better classified and handled when all relevant artifacts are available to the decision makers. However, traditional full-text and similarity search techniques often fail to provide the full set of relevant documents because they do not take into consideration existing relationships between software artifacts. We propose a metadata approach with semantic networks which convey such relationships. Our approach reveals additional relevant artifacts that the user might have not been aware of. We also apply contextual information to filter out results unrelated to the user contexts, thus, improving the precision of the search results. Experimental results show that the combination of semantic networks and context significantly improve the precision and recall of the search results.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Aamodt, A., Plaza, E.: Case-based reasoning: Foundational Issues, Methodological Variations, and System Approaches. Artificial Intelligence Communications 7(1), 39–59 (1994)

    Google Scholar 

  2. Agrawal, R., Rantzau, R., Terzi, E.: Context-sensitive ranking. In: ACM SIGMOD International Conference on Management of data, Chicago, IL, USA, pp. 383–394 (2006)

    Google Scholar 

  3. Aleman-Meza, B., Halaschek-Wiener, C., Arpinar, I.B., Ramakrishnan, C., Sheth, A.P.: Ranking Complex Relationships on the Semantic Web. IEEE Internet Computing, 37–44 (2005)

    Google Scholar 

  4. Antoniou, G., Hermelen, F.v.: A Semantic Web Primer, p. 238. The MIT Press, Cambridge (2004)

    Google Scholar 

  5. Anvik, J., Hiew, L., Murphy, G.C.: Who should fix this bug? In: International Conference on Software Engineering (2006)

    Google Scholar 

  6. Baeza-Yates, R.A., Ribeiro-Neto, B.A.: Modern Information Retrieval. ACM Press / Addison-Wesley (1999)

    Google Scholar 

  7. Basili, V.R., Rombach, H.D.: Support for Comprehensive Reuse. IEEE Software Engineering Journal 6(5), 303–316 (1991)

    Google Scholar 

  8. Bazire, M., Brezillon, P.: Understanding Context Before Using It. In: Dey, A.K., Kokinov, B., Leake, D.B., Turner, R. (eds.) CONTEXT 2005. LNCS (LNAI), vol. 3554, pp. 29–40. Springer, Heidelberg (2005)

    Google Scholar 

  9. Bergmann, R., Göker, M.: Developing Industrial Case-Based Reasoning Applications Using the INRECA Methodology. In: Workshop at the International Joint Conference on Artificial Intelligence, IJCAI - Automating the Construction of Case Based Reasoners, Stockholm (1999)

    Google Scholar 

  10. Berners-Lee, T., Hendler, J., Lassila, O.: The Semantic Web. Scientific American 284(5), 34–43 (2001)

    Article  Google Scholar 

  11. Bohner, S.A., Arnold, R.S.: Software Change Impact Analysis. IEEE Computer Society Press, Los Alamitos (1996)

    Google Scholar 

  12. Bouquet, P., Giunchiglia, F., van Harmelen, F., Serafini, L., Stuckenschmidt, H.: C-OWL: Contextualizing ontologies. In: Fensel, D., Sycara, K., Mylopoulos, J. (eds.) ISWC 2003. LNCS, vol. 2870, pp. 164–179. Springer, Heidelberg (2003)

    Google Scholar 

  13. Brezillon, P.: Context in Human Machine Problem Solving: A Survey. LAFORIA (1996)

    Google Scholar 

  14. Canfora, G., Cerulo, L.: Impact analysis by mining software and change request repositories. In: International Software Metrics Symposium, METRICS 2005 (2005)

    Google Scholar 

  15. Canfora, G., Cerulo, L., Penta, M.D.: Relating software interventions through IR techniques. In: International Conference on Software Management (2006)

    Google Scholar 

  16. Chen, Z., Gangopadhyay, A., Holden, S., Karabatis, G., McGuire, M.: Semantic Integration of Government Data for Water Quality Management. Journal of Government Information Quarterly – Special Issue on Information Integration 24(4), 716–735 (2007)

    Google Scholar 

  17. Chen, Z., Gangopadhyay, A., Karabatis, G., McGuire, M., Welty, C.: Semantic Integration and Knowledge Discovery for Environmental Research. Journal of Database Management 18(1), 43–67 (2007)

    Google Scholar 

  18. Cubranic, D., Murphy, G.C.: Automatic bug triage using text categorization. In: International Conference on Software Engineering & Knowledge Engineering, Banff, Alberta, Canada, pp. 92–97 (2004)

    Google Scholar 

  19. Dennis, G.: TSAFE: Building a Trusted Computing Base for Air Traffic Control Software. MIT, Cambridge (2003)

    Google Scholar 

  20. Diligenti, M., Coetzee, F., Lawrence, S., Giles, C.L., Gori, M.: Focused Crawling Using Context Graphs. In: 26th International Conference on Very Large Data Bases, Cairo, Egypt, pp. 527–534 (2000)

    Google Scholar 

  21. Erzberger, H.: Transforming the NAS: The Next Generation Air Traffic Control System. In: 24th International Congress of the Aeronautical Sciences (2004)

    Google Scholar 

  22. Fankhauser, P., Kracker, M., Neuhold, E.J.: Semantic vs. Structural Resemblance of Classes. SIGMOD Record 20(4), 59–63 (1991)

    Article  Google Scholar 

  23. Farquhar, A., Dappert, A., Fikes, R., Pratt, W.: Integrating Information Sources using Context Logic. In: AAAI Spring Symposium on Information Gathering from Distributed Heterogeneous Environments (1995)

    Google Scholar 

  24. Fayyad, U., Piatetsky-Shapiro, G., Smyth, P.: From Data Mining to Knowledge Discovery: An overview. In: Advances in Knowledge Discovery and Data Mining. AAAI/MIT Press (1996)

    Google Scholar 

  25. Feldmann, R.L., Rech, J., Wenzler, A.J.: Experience Retrieval in LSOs: Do you find what you are looking for? In: 8th International Workshop on Learning Software Organizations (LSO 2006), Rio de Janeiro, Brazil (2006)

    Google Scholar 

  26. Fellbaum, C.: WordNet: An Electronic Lexical Database, p. 423. MIT Press, Cambridge (1998)

    MATH  Google Scholar 

  27. Finkelstein, L., Gabrilovich, E., Matias, Y., Rivlin, E., Solan, Z., Wolfman, G., Ruppin, E.: Placing Search in Context: the Concept Revisited. In: WWW, pp. 406–414 (2001)

    Google Scholar 

  28. Georgakopoulos, D., Karabatis, G., Gantimahapatruni, S.: Specification and Management of Interdependent Data in Operational Systems and Data Warehouses. Distributed and Parallel Databases 5(2), 121–166 (1997)

    Article  Google Scholar 

  29. Glass, R.: Agile Versus Traditional: Make Love, Not War. Cutter IT Journal, 12–18 (2001)

    Google Scholar 

  30. Goh, C.H., Bressan, S., Madnick, S., Siegel, M.: Context Interchange: New Features and Formalisms for the Intelligent Integration of Information. ACM Transactions on Information Systems 17(3), 270–293 (1999)

    Article  Google Scholar 

  31. Gong, L., Riecken, D.: Constraining Model-Based Reasoning Using Contexts. In: IEEE International Conference on Web Intelligence, WI 2003 (2003)

    Google Scholar 

  32. Guha, R., McCool, R., Fikes, R.: Contexts for the Semantic Web. In: McIlraith, S.A., Plexousakis, D., van Harmelen, F. (eds.) ISWC 2004. LNCS, vol. 3298, pp. 32–46. Springer, Heidelberg (2004)

    Google Scholar 

  33. Haney, F.M.: Module Connection Analysis - A Tool for Scheduling Software Debugging Activites. In: AFIPS Joint Computer Conference, pp. 173–179 (1972)

    Google Scholar 

  34. Haranczyk, M., Holliday, J.: Comparison of Similarity Coefficients for Clustering and Compound Selection. Journal of Chemical Information and Modeling 48(3), 498–508 (2008)

    Article  Google Scholar 

  35. Joachims, T.: Optimizing search engines using clickthrough data. In: ACM SIGKDD international conference on Knowledge discovery and data mining, Edmonton, Alberta, Canada, pp. 133–142 (2002)

    Google Scholar 

  36. Johnson, J.H.: Micro Projects Cause Constant Change. In: 2nd International Conference on eXtreme Programming and Flexible Processes in Software Engineering, pp. 132–135 (2001)

    Google Scholar 

  37. Karabatis, G.: Using Context in Semantic Data Integration. Journal of Interoperability in Business Information Systems 1(3), 9–21 (2006)

    Google Scholar 

  38. Karabatis, G., Rusinkiewicz, M., Sheth, A.: Interdependent Database Systems. In: Management of Heterogeneous and Autonomous Database Systems, pp. 217–252. Morgan-Kaufmann, San Francisco (1999)

    Google Scholar 

  39. Kashyap, V., Sheth, A.: Semantic and schematic similarities between database objects: a context-based approach. The VLDB Journal 5(4), 276–304 (1996)

    Article  Google Scholar 

  40. Kaufman, L., Rousseeuw, P.J.: Finding Groups In Data: An Introduction To Cluster Analysis. Wiley-Interscience, Hoboken (2005)

    Google Scholar 

  41. Kraft, R., Maghoul, F., Chang, C.C.: Y!Q: Contextual Search at the Point of Inspiration. In: ACM International Conference on Information and Knowledge Management, Bremen, Germany, pp. 816–823 (2005)

    Google Scholar 

  42. Lieberman, H., Selker, T.: Out of context: Computer Systems that adapt to, and learn from, context. IBM Systems Journal 39(3&4), 617–632 (2000)

    Article  Google Scholar 

  43. Lindvall, M., Feldmann, R.L., Karabatis, G., Chen, Z., Janeja, V.P.: Searching for Relevant Software Change Artifacts using Semantic Networks. In: 24th Annual ACM Symposium on Applied Computing SAC 2009, Honolulu, Hawaii, U.S.A., pp. 496–500 (2009)

    Google Scholar 

  44. Lindvall, M., Rus, I., Shull, F., Zelkowitz, M.V., Donzelli, P., Memon, A., Basili, V.R., Costa, P., Tvedt, R.T., Hochstein, L., Asgari, S., Ackermann, C., Pech, D.: An Evolutionary Testbed for Software Technology Evaluation. Innovations in Systems and Software Engineering - a NASA Journal 1(1), 3–11 (2005)

    Article  Google Scholar 

  45. Lindvall, M., Sandahl, K.: How Well do Experienced Software Developers Predict Software Change? Journal of Systems and Software 43(1), 19–27 (1998)

    Article  Google Scholar 

  46. Liu, H., Singh, P.: ConceptNet: A Practical Commonsense Reasoning Toolkit. BT Technology Journal 22(4), 211–226 (2004)

    Article  Google Scholar 

  47. Lormans, M., Deursen, A.v.: Can LSI help Reconstructing Requirements Traceability in Design and Test? In: Conference on Software Maintenance and Reengineering, CSMR 2006 (2006)

    Google Scholar 

  48. Lucca, G.D., Penta, M.D., Gradara, S.: An approach to classify software maintenance requests. In: International Conference on Software Maintenance, Los Alamitos, CA (2002)

    Google Scholar 

  49. Lydie, Y.T.M.: Context-Based Information Retrieval -User Problems and Benefits of Potential Solutions, Technical Report. FC-MD (2006)

    Google Scholar 

  50. Marcus, A., Maletic, J.I.: Recovering Documentation-to-Source-Code Traceability Links using Latent Semantic Indexing. In: 25th International Conference on Software Engineering, ICSE 2003 (2003)

    Google Scholar 

  51. Masterman, M.: Semantic message detection for machine translation, using an interlingua. NPL, 438–475 (1961)

    Google Scholar 

  52. McCarthy, J.: Notes on formalizing context. In: International Joint Conference on Artificial Intelligence (IJCAI), Chambéry, France, pp. 555–560 (1993)

    Google Scholar 

  53. McGuinness, D.L., Harmelen, F.v.: OWL Web Ontology Language Overview W3C (2004), http://www.w3.org/TR/owl-features/

  54. Mockus, A., Herbsleb, J.D.: Expertise browser: a quantitative approach to identifying expertise. In: International Conference on Software Engineering, New York, NY, pp. 503–512 (2002)

    Google Scholar 

  55. Mylopoulos, J., Cohen, P., Borgida, A., Sugar, L.: Semantic Networks and the Generation of Context. In: International Joint Conference on Artificial Intelligence, Tiblisi, Georgia, pp. 134–142 (1975)

    Google Scholar 

  56. Ostertag, E., Hendler, J., Prieto-Diaz, R., Braun, C.: Computing similarity in a reuse library system: An AI-based approach. ACM Transactions on Software Engineering and Methodology 1(3), 205–228 (1992)

    Article  Google Scholar 

  57. Ostertag, E.J.: A Classification System for Software Reuse, Ph.D. Dissertation. University of Maryland (1992)

    Google Scholar 

  58. Pearl, J.: Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Morgan Kaufmann, San Francisco (1988)

    Google Scholar 

  59. Pearl, J.: Causality: Models, Reasoning, and Inference. Cambridge University Press, Cambridge (2000)

    MATH  Google Scholar 

  60. Pomerol, J.-C., Brezillon, P.: Dynamics between Contextual Knowledge and Proceduralized Context. In: Bouquet, P., Serafini, L., Brézillon, P., Benercetti, M., Castellani, F. (eds.) CONTEXT 1999. LNCS (LNAI), vol. 1688, pp. 284–295. Springer, Heidelberg (1999)

    Chapter  Google Scholar 

  61. Prieto-Diaz, R.: Implementing faceted classification for software reuse. Communications of the ACM 34(5), 89–97 (1991)

    Article  Google Scholar 

  62. Prieto-Diaz, R.: Status report: Software reusability. IEEE Software 10(3), 61–66 (1993)

    Article  Google Scholar 

  63. Prieto-Diaz, R., Freeman, P.: Classifying software for reusability. IEEE Software 4(1), 6–16 (1987)

    Article  Google Scholar 

  64. Rice, J.A.: Mathematical Statistics and Data Analysis. Duxbury Press (1994)

    Google Scholar 

  65. Rusinkiewicz, M., Sheth, A., Karabatis, G.: Specifying Interdatabase Dependencies in a Multidatabase Environment. IEEE Computer 24(12), 46–53 (1991)

    Google Scholar 

  66. Shen, X., Tan, B., Zhai, C.: Context-Sensitive Information Retrieval using Implicit Feedback. In: 28th international ACM SIGIR conference on Research and development in information retrieval, Salvador, Brazil, pp. 43–50 (2005)

    Google Scholar 

  67. Sheth, A., Aleman-Meza, B., Arpinar, I.B., Bertram, C., Warke, Y., Ramakrishanan, C., Halaschek, C., Anyanwu, K., Avant, D., Arpinar, F.S., Kochut, K.: Semantic Association Identification and Knowledge Discovery for National Security Applications. Journal of Database Management 16(1) (2004)

    Google Scholar 

  68. Sheth, A., Karabatis, G.: Multidatabase Interdependencies in Industry. In: ACM SIGMOD International Conference on Management of Data, Washington, DC (1993)

    Google Scholar 

  69. Sowa, J.F.: Semantic Networks, http://www.jfsowa.com/pubs/semnet.htm

  70. Sowa, J.F.: Semantic Networks. In: Shapiro, S.C. (ed.) Encyclopedia of Artificial Intelligence, pp. 1493–1511. Wiley, New York (1992)

    Google Scholar 

  71. Sowa, J.F.: Laws, Facts, and Contexts: Foundations for Multimodal Reasoning. In: Hendricks, V.F., Jorgensen, K.F., Pedersen, S.A. (eds.) Knowledge Contributors, pp. 145–184. Kluwer Academic Publishers, Dordrecht (2003)

    Google Scholar 

  72. Sugiyama, K., Hatano, K., Yoshikawa, M.: Adaptive web search based on user profile constructed without any effort from users. In: WWW (2004)

    Google Scholar 

  73. Tan, P.-N., Steinbach, M., Kumar, V.: Introduction to Data Mining. Addison-Wesley, Reading (2006)

    Google Scholar 

  74. TopicMap: XML Topic Maps (XTM) 1.0, http://www.topicmaps.org/xtm/

  75. W3C: Semantic Web (2001), http://www.w3.org/2001/sw/

  76. Wache, H., Stuckenschmidt, H.: Practical Context Transformation for Information System Interoperability. In: Akman, V., Bouquet, P., Thomason, R.H., Young, R.A. (eds.) CONTEXT 2001. LNCS (LNAI), vol. 2116, pp. 367–380. Springer, Heidelberg (2001)

    Chapter  Google Scholar 

  77. Wu, H., Siegel, M., Ablay, S.: Sensor Fusion for Context Understanding. In: 19th IEEE Instrument and Measurement Technology Conference, Anchorage, AK, USA (2002)

    Google Scholar 

  78. Zimmermann, A., Lorenz, A., Oppermann, R.: An operational definition of context. In: Kokinov, B., Richardson, D.C., Roth-Berghofer, T.R., Vieu, L. (eds.) CONTEXT 2007. LNCS (LNAI), vol. 4635, pp. 558–571. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Karabatis, G. et al. (2009). Using Semantic Networks and Context in Search for Relevant Software Engineering Artifacts. In: Spaccapietra, S., Delcambre, L. (eds) Journal on Data Semantics XIV. Lecture Notes in Computer Science, vol 5880. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10562-3_3

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-10562-3_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-10561-6

  • Online ISBN: 978-3-642-10562-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics