Enhance code search via reformulating queries with evolving contexts

• Carpineto, C., Romano, G.: A survey of automatic query expansion in information retrieval. ACM Comput. Surv. 44(1), 1 (2012)

  Article  Google Scholar 

• Chaparro, O., Florez, J.M., Marcus, A.: Using observed behavior to reformulate queries during text retrieval-based bug localization. In: IEEE International Conference on Software Maintenance and Evolution (ICSME). IEEE (2017)

• Fischer, G., Henninger, S., Redmiles, D.: Cognitive tools for locating and comprehending software objects for reuse. In: Proceedings of the 13th International Conference on Software Engineering, pp. 318–328 (1991)

• Fluri, B., Wursch, M., Pinzger, M., Gall, H.C.: Change distilling—tree differencing for fine-grained source code change extraction. IEEE Trans. Softw. Eng. 33(11), 725–743 (2007)

  Article  Google Scholar 

• Haiduc, S., Bavota, G., Marcus, A., Oliveto, R., De Andrea, L., Menzies, T.: Automatic query reformulations for text retrieval in software engineering. In: Proceedings of the 35th International Conference on Software Engineering (ICSE), pp. 842–851 (2013)

• Howard, M.J., Gupta, S., Pollock, L., Vijay-Shanker, K.: Automatically mining software-based, semantically-similar words from comment code mappings. In: Proceedings of the 10th Working Conference on Mining Software Repositories, pp. 377–386 (2013)

• Keivanloo, I., Rilling, J., Zou, Y.: Spotting working code examples. In: Proceedings of the 36th International Conference on Software Engineering, pp. 664–675 (2014)

• Lemos, O., Bajracharya, S., Ossher, J., Morla, R., Masiero, P., Baldi, P., Lopes, C.: CodeGenie: using test-cases to search and reuse source code. In: Proceedings of the Twenty-Second IEEE/ACM International Conference on Automated Software Engineering, pp. 525–526 (2007)

• Lv, F., Zhang, H., Lou, J.-G., Wang, S., Zhang, D., Zhao, J.: CodeHow: effective code search based on API understanding and extended boolean model (E). In: Proceedings of the 30th IEEE/ACM International Conference on Automated Software Engineering (ASE), pp. 260–270 (2015)

• Manning, C.D., Raghavan, P., Schtze, H.: Introduction to Information Retrieval. Cambridge University Press, Cambridge (2008)

  Book  Google Scholar 

• McMillan, C., Grechanik, M., Poshyvanyk, D., Fu, C., Xie, Q.: Exemplar: a source code search engine for finding highly relevant applications. IEEE Trans. Softw. Eng. 38(5), 1069–1087 (2012)

  Article  Google Scholar 

• Mcmillan, C., Poshyvanyk, D., Grechanik, M., Xie, Q., Fu, C.: Portfolio: searching for relevant functions and their usages in millions of lines of code. ACM Trans. Softw. Eng. Methodol. 22(4), 1–30 (2013)

  Article  Google Scholar 

• Nguyen, A.T., Hilton, M., Codoban, M., Nguyen, H.A., Mast, L., Rademacher, E., Nguyen, T.N., Dig, D.: API code recommendation using statistical learning from fine-grained changes. In: Proceedings of the 24th ACM SIGSOFT International Symposium on Foundations of Software Engineering, pp. 511–522 (2016)

• Nie, L., Jiang, H., Ren, Z., Sun, Z., Li, X.: Query expansion based on crowd knowledge for code search. IEEE Trans. Serv. Comput. 9(5), 771–783 (2016)

  Article  Google Scholar 

• Proksch, S., Amann, S., Nadi, S., Mezini, M.: Evaluating the evaluations of code recommender systems: a reality check. In: Proceedings of the 31st IEEE/ACM International Conference on Automated Software Engineering, Singapore, pp. 111–121 (2016)

• Sadowski, C., Stolee, K.T., Elbaum, S.: How users search for code: a case study. Presented at the Proceedings, 10th Joint Meeting Foundations of Software Engineering (2015)

• Salton, G., Fox, E.A., Wu, H.: Extended boolean information retrieval. Commun. ACM 26, 1022–1036 (1983)

  Article  MathSciNet  Google Scholar 

• Sim, S.E, Clarke, C.L.A., Holt, R.C.: Archetypal source code searches: a survey of software users and maintainers. In: International Workshop on Program Comprehension, Iwpc ’98, Proceedings. IEEE, pp. 180–187 (1998)

• Sridhara, G., Hill, E., Pollock, L.L., Vijay-Shanker, K.: Identifying word relations in software: a comparative study of semantic similarity tools. In: Proceedings 16th IEEE International Conference on Program Comprehension (ICPC 08), pp. 123–132 (2008)

• Stolee, K.T., Elbaum, S., Dobos, D.: Solving the search for source code. ACM Trans. Softw. Eng. Methodol. (TOSEM) 23(3), 26 (2014)

  Article  Google Scholar 

• Sun, X., Liu, X., Hu, J., Zhu, J.: Empirical studies on the NLP techniques for source code data preprocessing. In: Proceedings of the 3rd International Workshop on Evidential Assessment of Software Technologies, pp. 32–39 (2014)

• Tian, Y., Lo, D., Lawall, J.: SEWordSim: software-specific word similarity database. In: Companion Proceedings of the 36th International Conference on Software Engineering. ACM (2014)

• Xu, B., Lin, H., Lin, Y.: Assessment of learning to rank methods for query expansion. J. Assoc. Inf. Sci. Technol. (JASIST) 67(6), 1345–1357 (2016)

  Article  MathSciNet  Google Scholar 

• Ye, X., Shen, H., Ma, X., Bunescu, R.C., Liu, C.: From word embeddings to document similarities for improved information retrieval in software engineering. In: Proceedings of the 38th International Conference on Software Engineering, pp. 404–415 (2016)

• Youm, K.C., Ahn, J., Lee, E.: Improved bug localization based on code change histories and bug reports. Inf. Softw. Technol. 82, 177–192 (2017)

  Article  Google Scholar 

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