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                 [51]  Yang  G,  Lee  B.  Utilizing  topic-based  similar  commit  information  and  CNN-LSTM  algorithm  for  bug  localization.  Symmetry,  2021,
                     13(3): 406. [doi: 10.3390/sym13030406]
                 [52]  Ciborowska A, Damevski K. Fast changeset-based bug localization with BERT. In: Proc. of the 44th Int’l Conf. on Software Engineering.
                     Pittsburgh: ACM, 2022. 946–957. [doi: 10.1145/3510003.3510042]
                 [53]  Zhu  ZY,  Tong  HH,  Wang  Y,  Li  Y.  BL-GAN:  Semi-supervised  bug  localization  via  generative  adversarial  network.  IEEE  Trans.  on
                     Knowledge and Data Engineering, 2023, 35(11): 11112–11125. [doi: 10.1109/tkde.2022.3225329]
                 [54]  Liang HL, Hang DJ, Li XY. Modeling function-level interactions for file-level bug localization. Empirical Software Engineering, 2022,
                     27(7): 186. [doi: 10.1007/s10664-022-10237-z]
                 [55]  Luo ZM, Wang WY, Cen CC. Improving bug localization with effective contrastive learning representation. IEEE Access, 2023, 11:
                     32523–32533. [doi: 10.1109/access.2022.3228802]
                 [56]  Ma YF, Li M. Learning from the multi-level abstraction of the control flow graph via alternating propagation for bug localization. In:
                     Proc. of the 2022 IEEE Int’l Conf. on Data Mining. Orlando: IEEE, 2022. 299–308. [doi: 10.1109/icdm54844.2022.00040]
                 [57]  Ma YF, Li M. The flowing nature matters: Feature learning from the control flow graph of source code for bug localization. Machine
                     Learning, 2022, 111(3): 853–870. [doi: 10.1007/s10994-021-06078-4]
                 [58]  Chen H, Yang HY, Yan ZL, Kuang L, Zhang LY. CGMBL: Combining GAN and method name for bug localization. In: Proc. of the
                     2023, 11: 35901–35913. [doi: 10.1109/access.2023.3265731]
                     22nd IEEE Int’l Conf. on Software Quality, Reliability and Security. Guangzhou: IEEE, 2022. 231–241. [doi: 10.1109/qrs57517.2022.
                     00033]
                 [59]  Zhu ZY, Tong HH, Wang Y, Li Y. Enhancing bug localization with bug report decomposition and code hierarchical network. Knowledge-
                     based Systems, 2022, 248: 108741. [doi: 10.1016/j.knosys.2022.108741]
                 [60]  Shi XY, Ju XL, Chen X, Lu GL, Xu MQ. SemirFL: Boosting fault localization via combining semantic information and information
                     retrieval. In: Proc. of the 22nd IEEE Int’l Conf. on Software Quality, Reliability, and Security Companion. Guangzhou: IEEE, 2022.
                     324–332. [doi: 10.1109/qrs-c57518.2022.00055]
                 [61]  Kim M, Kim Y, Lee E. An empirical study of IR-based bug localization for deep learning-based software. In: Proc. of the 2022 IEEE
                     Conf. on Software Testing, Verification and Validation. Valencia: IEEE, 2022. 128–139. [doi: 10.1109/icst53961.2022.00024]
                 [62]  Huang  XX,  Xiang  C,  Li  H,  He  P.  SBuglocater:  Bug  localization  based  on  deep  matching  and  information  retrieval.  Mathematical
                     Problems in Engineering, 2022, 2022: 3987981. [doi: 10.1155/2022/3987981]
                 [63]  Chakraborty P, Alfadel M, Nagappan M. RLocator: Reinforcement learning for bug localization. IEEE Trans. on Software Engineering,
                     2024, 50(10): 2695–2708. [doi: 10.1109/tse.2024.3452595]
                 [64]  Al-Aidaroos  AS,  Bamzahem  SM.  The  impact  of  GloVe  and  Word2Vec  word-embedding  technologies  on  bug  localization  with
                     convolutional  neural  network.  Int’l  Journal  of  Science  and  Engineering  Applications,  2023,  12(1):  108–111.  [doi:  10.7753/ijsea1201.
                     1035]
                 [65]  Ciborowska A, Damevski K. Too few bug reports? Exploring data augmentation for improved changeset-based bug localization. arXiv:
                     2305.16430, 2023.
                 [66]  Ahmad AA, Yu LS, Kholief M, Garba A. AttentiveBugLocator: A bug localization model using attention-based semanticfeatures and
                     information retrieval. 2023. [doi: 10.21203/rs.3.rs-3348519/v1]
                 [67]  Xiao  X,  Xiao  RJ,  Li  Q,  Lv  JH,  Cui  SY,  Liu  QX.  BugRadar:  Bug  localization  by  knowledge  graph  link  prediction.  Information  and
                     Software Technology, 2023, 162: 107274. [doi: 10.1016/j.infsof.2023.107274]
                 [68]  Ma  YF,  Du  YL,  Li  M.  Capturing  the  long-distance  dependency  in  the  control  flow  graph  via  structural-guided  attention  for  bug
                     localization. In: Proc. of the 32nd Int’l Joint Conf. on Artificial Intelligence. 2023. 2242–2250. [doi: 10.24963/ijcai.2023/249]
                 [69]  Mohsen AM, Hassan HA, Wassif KT, Moawad R, Makady SH. Enhancing bug localization using phase-based approach. IEEE Access,

                 [70]  Du YL, Yu ZX. Pre-training code representation with semantic flow graph for effective bug localization. In: Proc. of the 31st ACM Joint
                     European Software Engineering Conf. and Symp. on the Foundations of Software Engineering. New York: ACM, 2023. 579–591. [doi:
                     10.1145/3611643.3616338]
                 [71]  Ali W, Bo LL, Sun XB, Wu XX, Memon S, Siraj S, Suwaree Ashton A. Automated software bug localization enabled by meta-heuristic-
                     based convolutional neural network and improved deep neural network. Expert Systems with Applications, 2023, 232: 120562. [doi: 10.
                     1016/j.eswa.2023.120562]
                 [72]  Xu GQ, Wang XQ, Wei D, Shao YL, Chen B. Bug localization with features crossing and structured semantic information matching. Int’l
                     Journal of Software Engineering and Knowledge Engineering, 2023, 33(8): 1261–1291. [doi: 10.1142/s0218194023500316]
                 [73]  Rahman F, Posnett D, Hindle A, Barr E, Devanbu P. BugCache for inspections: Hit or miss? In: Proc. of the 19th ACM SIGSOFT Symp.
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