Page 284 - 《软件学报》2021年第7期
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2202                                     Journal of Software  软件学报 Vol.32, No.7,  July 2021

                 [4]    Ruiz-Rube I, Person  T,  Dodero JM, Mota J, Mota  JM, Sánchez-Jara JM.  Applying static  code  analysis for domain-specific
                     languages. Software & Systems Modeling, 2020,19(1):95–11. [doi: 10.1007/s10270-019-00729-w]
                 [5]    Pagano D, Brügge B. User involvement in software evolution practice: A case study. In: Proc. of the 2013 Int’l Conf. on Software
                     Engineering. San Francisco: IEEE Press, 2013. 953–962.
                 [6]    Xu HY, Jiang Y.  Code quality recognition  and  analysis based on user’s  comments.  Computer Science, 2020,47(6):44–50 (in
                     Chinese with English abstract).
                 [7]    Li AP, Qiu  P, Duan LG.  Document  sentiment  orientation analysis  based  on sentence weighted algorithm.  Journal  of Chinese
                     Computer Systems, 2015,36(10):2252–2256 (in Chinese with English abstract).
                 [8]    Hu TY, Jiang Y. Mining of user’s comments reflecting usage feedback for APP software. Ruan Jian Xue Bao/Journal of Software,
                     2019,30(10):3168–3185  (in Chinese with English abstract).  http://www.jos.org.cn/1000-9825/5794.htm [doi:  10.13328/j.cnki.jos.
                     005794]
                 [9]    Duan WJ, Jiang Y. Defect recognition of APP software based on user feedback. Computer Science, 2020,47(6):44–50 (in Chinese
                     with English abstract).
                [10]    Wang DX,  Wang  Q.  Trustworthiness evidence supporting evaluation  of software  process  trustworthiness. Ruan  Jian Xue Bao/
                     Journal of Software, 2018,29(11):3412–3434 (in Chinese with English abstract). http://www.jos.org.cn/1000-9825/5291.htm [doi:
                     10.13328/j.cnki.jos.005291]
                [11]    Venkatasubramanyamrd RD, Sowmya GR. Why is dynamic analysis not used as extensively as static analysis: An industrial study?
                     In: Proc. of the 1st Int’l Workshop on Software Engineering Research and Industrial Practices—SER&IPs 2014. 2014. 24–33.
                [12]    Liu ZG, Chen XR. A entity-action relationship model for text clustering. Journal of Chinese Information Processing, 2018,32(5):
                     22–30 (in Chinese with English abstract).
                [13]    Liu ZG, Chen XR. Research on argument relationship model based in syntactic analyses. Journal of Nanjing University (Natural
                     Science), 2019,55(6):1010–1019 (in Chinese with English abstract).
                [14]    Mao TT, Lv XQ, Zhou Q, Liu Y. Manual annotation approach to Chinese complex sentences by using bottom-up and top-down.
                     Journal of Chinese Computer Systems, 2016,37(4):716–721 (in Chinese with English abstract).
                [15]    Ye ZL,  Jia Z, Yin  HF,  et al.  Research on  multi-domain natural language question understanding. Computer  Science, 2017(6):
                     216–221 (in Chinese with English abstract).
                [16]    Swain D, Tambe M, Ballal P, Dolase V, Agrawal K, Rajmane Y. Lexical text simplification using WordNet. Communications in
                     Computer and Information Science, 2019,1046:114–122. [doi: 10.1007/978-981-13-9942-8_11]
                [17]    Siddharthan A. Syntactic simplification and text cohesion. Research on Language & Computation, 2006,4(1):77–109. [doi: 10.1007/
                     s11168-006-9011-1]
                [18]    Andreasen E, Gong L, Møller A, Pradel M, Selakovic M, Sen K, Staicu C. A survey of dynamic analysis and test generation for
                     JavaScript. ACM Computing Surveys, 2017,50(5):66:1–36. [doi: 10.1145/3106739]
                [19]    Selakovic M, Pradel M, Karim R, Tip F. Test generation for higher-order functions in dynamic languages. Proc. of the ACM on
                     Programming Languages, 2018,2:27:1–27. [doi: 10.1145/3276531]
                [20]    Huang PJ, Yang MQ. Research and application of static metrics for code quality. Computer Engineering and Applications, 2011,
                     47(23):61–63 (in Chinese with English abstract).
                [21]    Zheng RJ. Computer Software Testing Technology. Beijing: Tsinghua University Press, 1992. 31–35 (in Chinese).
                [22]    Yu Y, Chen L, Jiang JD, Zhao NX. Research on the selection of Chinese patent candidate term based on dependency syntax parsing.
                     Library and Information Service, 2019,63(18):109–118 (in Chinese with English abstract).
                [23]    Agarwal B, Poria S, Mittal N, Gelbukh A, Hussain A. Concept-level sentiment analysis with dependency-based semantic parsing: A
                     novel approach. Cognitive Computation, 2015,7(4):487–499. [doi: 10.1007/s12559-014-9316-6]
                [24]    Feng C, Liao C, Liu ZR, Huang HY. Sentiment key sentence identification based on lexical semantics and syntactic dependency.
                     Acta Electronica Sinica, 2016,44(10):2471–2476 (in Chinese with English abstract).
                [25]    Gan LX, Wan CX, Liu DX, Zhong Q, Jiang TJ. Chinese named entity relation extraction based on syntactic and semantic features.
                     Journal of Computer Research and Development, 2016,53(2):284–302 (in Chinese with English abstract).
                [26]    Wan CX, Gan LX, Jiang TJ, Liu DX, Liu XP, Liu Y. Chinese named entity implicit relation extraction based on company verbs.
                     Chinese Journal of Computers, 2019,42(12):2795–2820 (in Chinese with English abstract).
                [27]    Tian  CY,  Chen DH, Wang  M,  Le JJ. Structured processing  for pathological  reports based on dependency  parsing. Journal of
                     Computer Research and Development, 2016,52(12):2669–2680 (in Chinese with English abstract).
                [28]    Luo SL, Han  L, Pan LM,  Wei  C.  Construction  method of  Chinese sentential semantic structure. Journal of  Beijing Institute of
                     Technology, 2015(1):110–117.
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