Page 231 - 《软件学报》2020年第9期
P. 231

2852                                 Journal of Software  软件学报 Vol.31, No.9,  September 2020

         [87]    Rao  S, Medeiros H, Kak AC. Comparing incremental  latent  semantic analysis algorithms  for efficient  retrieval from software
             libraries for bug localization. ACM SIGSOFT Software Engineering Notes, 2015,40(1):1−8. [doi: 10.1145/2693208.2693222]
         [88]    Naish L, Ramamohanarao NK. Multiple bug spectral fault localization using genetic programming. In: Proc. of the Australasian
             Software Engineering Conf. 2015. 11−17. [doi: 10.1109/ASWEC.2015.12]
         [89]    Alduailij M, Al-Duailej M. Performance evaluation of information retrieval models in bug localization on the method level. In:
             Proc. of the Int’l Conf. on Collaboration Technologies and Systems. 2015. 305−313. [doi: 10.1109/CTS.2015.7210439]
         [90]    Kilinç D,  Yücalar  F, Borandag E, Aslan E. Multi-Level  reranking approach  for  bug  localization. Expert  Systems,  2016,33(3):
             286−294. [doi: 10.1111/exsy.12150]
         [91]    Shi ZD, Keung JW, Bennin KE, Limsettho N, Song QB. A strategy to determine when to stop using automatic bug localization. In:
             Proc. of the Int’l Computer Software and Applications Conf. 2016. 185−190. [doi: 10.1109/COMPSAC.2016.39]
         [92]    Rahman S, Rahman MM, Sakib K. An improved method level bug localization approach using minimized code space. In: Proc. of
             the Int’l Conf. on Evaluation of Novel Approaches to Software Engineering. 2016. 179−200. [doi: 10.1007/978- 3-319-56390-9_9]
         [93]    Gore A, Choubey SD, Gangrade K. Improved bug localization technique using hybrid information retrieval model. In: Proc. of the
             Int’l Conf. on Distributed Computing and Internet Technology. 2016. 127−131. [doi: 10.1007/978-3-319-28034-9_16]
         [94]    Shi  ZD,  Keung J,  Bennin  KE,  Zhang ZJ.  Comparing learning to rank techniques in hybrid bug localization. Applied Soft
             Computing, 2019,62:636−648. [doi: 10.1016/j.asoc.2017.10.048]
         [95]    Loyola P, Gajananan K, Satoh F. Bug localization by learning to rank and represent bug inducing changes. In: Proc. of the Int’l
             Conf. on Information and Knowledge Management. 2018. 657−665. [doi: 10.1145/3269206.3271811]
         [96]    Xiao Y, Keung J, Mi Q, Bennin KE. Bug localization with semantic and structural features using convolutional neural network and
             cascade forest. In: Proc. of the Int’l Conf. on Evaluation and Assessment in Software Engineering. 2018. 101−111. [doi: 10.1145/
             3210459.3210469]
         [97]    Rath  M,  Mäder P. Influence of  structured information  in bug report descriptions on IR-Based bug localization. In: Proc. of  the
             Euromicro Conf. on Software Engineering and Advanced Applications. 2018. 26−32. [doi: 10.1109/SEAA.2018.00014]
         [98]     Wang YJ, Yuan Y, Tong HH, Huo X, Li M, Xu F, Lu J. Bug localization via supervised topic modeling. In: Proc. of the Int’l Conf.
             on Data Mining. 2018. 607−616. [doi: 10.1109/ICDM.2018.00076]
         [99]    Swe KEE, Oo HM. Bug localization approach using source code structure with different structure fields. In: Proc. of the Int’l Conf.
             on Software Engineering Research, Management and Applications. 2018. 159−164. [doi: 10.1109/SERA.2018.8477206]
        [100]    Zhang T, Hu WJ, Luo XP, Ma XB. A commit messages-based bug localization for android applications. Int’l Journal of Software
             Engineering and Knowledge Engineering, 2019,29(4):457−487. [doi: 10.1142/S0218194019500207]
        [101]    Polisetty S, Miranskyy AV, Basar A. On usefulness of the deep-learning-based bug localization models to practitioners. In: Proc. of
             the Int’l Workshop on Predictor Models in Software Engineering. 2019. 16−25. [doi: 10.1145/3345629.3345632]
        [102]    Kim M, Lee E. A novel approach to automatic query reformulation for IR-based bug localization. In: Proc. of the Symp. on Applied
             Computing. 2019. 1752−1759. [doi: 10.1145/3297280.3297451]
        [103]    Ranman S, Ganguly KK, Sakib K. An improved bug localization using structured information retrieval and version history. In: Proc.
             of the Int’l Conf. on Computer and Information Technology. 2015. 190−195. [doi: 10.1109/ICCITechn.2015.7488066]
        [104]    Shao P, Atkison T, Kraft NA, Smith RK. Combining lexical and structural information for static bug localisation. Int’l Journal of
             Computer Applications in Technology, 2012, 44(1),61−71. [doi: 10.1504/IJCAT.2012.048208]
        [105]    Davies S, Roper M. Bug localisation through diverse sources of information. In: Proc. of the Int’l Symp. on Software Reliability
             Engineering. 2013. 126−131. [doi: 10.1109/ISSREW.2013.6688891]
        [106]    Salton G, McGill M. Introduction to Modern Information Retrieval. New York: McGraw-Hill, 1983. [doi: 10.1080/00048623.2010.
             10721488]
        [107]    Deerwester S, Dumais ST, Furnas GW, Landauer TK, Harshman R. Indexing by latent semantic analysis. Journal of The American
             Society for Information Science, 1990,41(6):391−407.
        [108]    Blei D, Ng AY, Jordan M. Latent dirichlet allocation. Journal of Machine Learning Research, 2003,3(4/5):993−1022. [doi: 10.1162/
             jmlr.2003.3.4-5.993]
   226   227   228   229   230   231   232   233   234   235   236