Detection of inaccurate replays in software documentation

Publication type Article
Status Published
Affiliation: St. Petersburg State University
Address: Russian Federation
Affiliation: St. Petersburg State University
Address: Russian Federation
Affiliation: St. Petersburg State University
Address: Russian Federation
Affiliation: St. Petersburg State University
Address: Russian Federation
Affiliation: St. Petersburg State University
Address: Russian Federation
Affiliation: St. Petersburg State University
Address: Russian Federation
Journal nameProgrammirovanie
EditionIssue 5


AcknowledgmentThis work was partially supported by the Russian Foundation for Basic Research, Grant No. 16-01-00304.
Publication date28.10.2018
Number of characters1037
Cite   Download pdf To download PDF you should sign in
Размещенный ниже текст является ознакомительной версией и может не соответствовать печатной

views: 710

Readers community rating: votes 0

1. Parnas, D.L. Precise documentation: The key to better software, The Future of Software Engineering, Berlin, Heidelberg: Springer-Verlag, 2011, pp. 125Ts148.

2. Juergens, E., Deissenboeck, F., Feilkas, M., Hummel, B., Schaetz, B., Wagner, S., Domann, C., and Streit, J. Can clone detection support quality assessments of requirements specifications? Proceedings of the 32 ACM/IEEE International Conference on Software Engineering (ICSET10), New York, NY, USA: ACM, 2010, vol. 2, pp. 79Ts88.

3. NosalT, M. Preliminary report on empirical study of repeated fragments in internal documentation, Proceedings of Federated Conference on Computer Science and Information Systems, 2016, pp. 1573Ts1576.

4.  oznov ƒ.¬., –omanovskij  .yo. DocLine: metod razrabotki dokumentatsii semejstva programmnykh produktov // ѕrogrammirovanie. 2008. “. 34. є 4. —. 1Ts13.

5. Romanovsky, K., Koznov, D., and Minchin, L. Refactoring the documentation of software product lines, Lecture Notes in Compute Science, Berlin, Heidelberg: Springer-Verlag, 2011, vol. 4980 of CEE-SET 2008, pp. 158Ts170.

6. Wingkvist, A., Lowe, W., Ericsson, M., and Lincke, R. Analysis and visualization of information quality of technical documentation, Proceedings of the 4th European Conference on Information Management and Evaluation, 2010, pp. 388Ts396.

7. Koznov, D., Luciv, D., Basit, H.A., Lieh, O.E., and Smirnov, M. Clone detection in reuse of software technical documentation, International Andrei Ershov Memorial Conference on Perspectives of System Informatics, 2015, Springer Nature, 2016, vol. 9609 of Lecture Notes in Computer Science, pp. 170Ts185.

8. Ћutsiv ƒ.¬. «adacha poiska nechЄtkikh povtorov pri organizatsii povtornogo ispol'zovani¤ dokumentatsii / ƒ.¬. Ћutsiv, ƒ.¬.  oznov, ’.ј. Ѕasit, ј.Ќ. “erekhov // ѕrogrammirovanie. 2016. “. 42. є 4. —. 39Ts49.

9. Basit, H.A. Efficient Token Based Clone Detection with Flexible Tokenization / H.A. Basit, S.J. Puglisi, W.F. Smyth et al, Proceedings of the 6th Joint Meeting on European Software Engineering Conference and the ACM SIGSOFT Symposium on the Foundations of Software Engineering: Companion Papers. New York, NY, USA: ACM, 2007, pp. 513Ts516.

10. Bassett, P.G. Framing software reuse: Lessons from the real World, Upper Saddle River, NJ, USA: Prentice-Hall, 1997.

11. Documentation Refactoring Toolkit. http://www. /index_en. html.

12. Torvalds, L. Linux Kernel Documentation, Dec 2013 snapshot. /tree/ master/Documentation/DocBook/. 13. Horie, M. and Chiba, S. Tool support for

13. crosscutting concerns of API documentation, Proceedings of the 9th International Conference on Aspect-Oriented Software Development, New York, NY, USA: ACM, 2010, pp. 97Ts108.

14. Nos?alT, M. Reusable software documentation with phrase annotations, Central Europ. J. Comput. Sci., 2014, vol. 4, no. 4, pp. 242Ts258.

15. Oumaziz, M.A., Charpentier, A., Falleri, J.-R., and Blanc, X. Documentation reuse: Hot or not? An empirical study, Mastering Scale and Complexity in Software Reuse: 16th International Conference on Software Reuse, ICSR 2017, Salvador, Brazil, 2017, Proceedings, Botterweck, G. and Werner, C., Eds., Cham: Springer-Verlag, 2017, pp. 12Ts27.

16. Rago, A., Marcos, C., and Diaz-Pace, J.A. Identifying duplicate functionality in textual use cases by aligning semantic actions, Software Syst. Model., 2016, vol. 15, no. 2, pp. 579Ts603.

17. Huang, T.-K., Rahman, Md.S., Madhyastha, H.V., Faloutsos, M., and Ribeiro, B. An analysis of socware cascades in online social networks, Proceedings of the 22Nd International Conference on World Wide Web, New York, NY, USA: ACM, 2013, pp. 619Ts630.

18. Williams, K. and Giles, C.L. Near duplicate detection in an Academic Digital Library, Proceedings of the ACM Symposium on Document Engineering, New York, NY, USA: ACM, 2013, pp. 91Ts94.

19. Zhang, Q., Zhang Yu., Yu, H., and Huang, X. Efficient partial-duplicate detection based on sequence matching, Proceedings of the 33rd International ACM SIGIR Conference on Research and Development in Information Retrieval, New York, NY, USA: ACM, 2010, pp. 675Ts682.

20. Abdel Hamid, O., Behzadi, B., Christoph, S., and Henzinger, M. Detecting the origin of text segments efficiently, Proceedings of the 18th International Conference on World Wide Web, New York, NY, USA: ACM, 2009, pp. 61Ts70.

21. Ramaswamy, L., Iyengar, A., Liu, L., and Douglis, F. Automatic detection of fragments in dynamically generated web pages, Proceedings of the 13th International Conference on World Wide Web, New York, NY, USA: ACM, 2004, pp. 443Ts454.

22. Gibson, D., Punera, K., and Tomkins, A. The volume and evolution of web page templates, Special Interest Tracks and Posters of the 14th International Conference on World Wide Web, New York, NY, USA: ACM, 2005, pp. 830Ts839.

23. Valles, E. and Rosso, P. Detection of nearduplicate user generated contents: The SMS spam collection, Proceedings of the 3rd International Workshop on Search and Mining User-generated Contents, New York, NY, USA: ACM, 2011, pp. 27Ts34.

24. Barron-Cede?no, A., Vila, M., Marti, M., and Rosso, P. Plagiarism meets paraphrasing: Insights for the next generation in automatic plagiarism detection, Comput. Linguist., 2013, vol. 39, no. 4, pp. 917Ts947.

25. Antiplagiarism (in Russian). Accessed January 16, 2018.

26. Sajnani, H., Saini, V., Svajlenko, J., Roy, C.K., and Lopes, C.V. SourcererCC: Scaling code clone detection to big-code, Proceedings of the 38th International Conference on Software Engineering, New York, NY, USA: ACM, 2016, pp. 1157Ts1168.

27. Jiang, L., Misherghi, G., Su, Z., and Glondu, S. DECKARD: Scalable and accurate tree-based detection of code clones, Proceedings of the 29th International Conference on Software Engineering, Washington, DC, USA: IEEE Computer Soc., 2007, pp. 96Ts105.

28. Cordy, J.R. and Roy, C.K. The NiCad clone detector, in Proceedings of IEEE 19th International Conference on Program Comprehension, 2011, pp. 219Ts220.

29. Akhin, M. and Itsykson, V. Tree slicing in clone detection: Syntactic analysis made (semi)-semantic (in Russian), Model. Anal. Inform. Syst., 2012, vol. 19, no. 6, pp. 69Ts78.

30. Zeltser, N.G. Automatic clone detection for refactoring, Proc. Inst. Syst. Program., 2013, vol. 25, pp. 39Ts50.

31. Wagner, S. and Fern???ndez, D.M. Analyzing text in software projects, The Art and Science of Analyzing Software Data, Elsevier, 2015, pp. 39Ts72.

32. Korshunov, A. and Gomzin, A. Topic modeling in natural language texts (in Russian), Proc. Inst. Syst. Program., 2012, vol. 23, pp. 21Ts242.

33. Tomita-parser Ch Yandex Technologies (in Russian). Accessed January 16, 2018.

34. Rattan, D., Bhatia, R., and Singh, M. Software clone detection: A systematic review, Inform. Software Technol., 2013, vol. 55, no. 7, pp. 1165Ts1199.

35. Abouelhoda, M.I., Kurtz, S., and Ohlebusch, E. Replacing suffix trees with enhanced suffix arrays, J. Discrete Algorithms, 2004, vol. 2, no. 1, pp. 53Ts86.

36. Bassett, P.G. The theory and practice of adaptive reuse, SIGSOFT Software Eng. Notes, 1997, vol. 22, no. 3, pp. 2Ts9.

37. De Berg, M., Cheong, O., van Kreveld, M., and Overmars, M. Computational Geometry, Berlin Heidelberg: Springer-Verlag, 2008, pp. 220Ts226.

38. Preparata, F.P. and Shamos, M.I. Computational Geometry: An Introduction, Berlin: Springer- Verlag, 1985, pp. 359Ts363.

39. PyIntervalTree. /intervaltree.

40. Kolchin, A.V., Kotljarov, V.P., and Drobincev, P.D. The method of test scenariogeneration in the environment of the insertion modeling, Control Syst. Mach., 2012, no. 6, pp. 43Ts48. 41. Pakulin, N.V. and Tugaenko, A.N. Model-based testing of Internet Mail Protocols, Proc. Inst. Syst. Program., 2011, vol. 20, pp. 125Ts141.

41. Kudryavtsev, D. and Gavrilova T. Diagrammatic knowledge modeling for managers: Ontologybased approach, Proceedings of the International Conference on Knowledge Engineering and Ontology Development, 2011, pp. 386Ts389.

Система Orphus