通信学报2023，Vol.44Issue(11)：249-259,11.DOI:10.11959/j.issn.1000-436x.2023203
PSR-SQUARES:基于程序空间约简器的SQL逆向合成系统
PSR-SQUARES:SQL reverse synthesis system based on program space reducer
摘要
Abstract
In order to address the issue of rapid growth of program space in SQUARES,which led to low efficiency in program synthesis,a program space reducer based on deep neural network(DNN)was introduced into the SQUARES framework.A given<Queried tables,Query result>pair was represented as a 2D tensor which was used as input for a DNN.And the output of the DNN was the relevance vector of the target SQL statement synthesis rules.Based on the output of the DNN,the last N rules with weak correlation to the target SQL statement were eliminated,thereby shrinking the program search space and improving the system synthesis efficiency.The architecture of DNN,the method of gener-ating training datasets,and the training process of DNN were described in detail.Furthermore,experimental comparisons between PSR-SQUARES and other representative SQL reverse synthesis systems were conducted.The results show that the overall performance of PSR-SQUARES is superior to other synthesis systems to varying degrees,with the average synthesis time reduced from 251 s in SQUARES to 130 s and the target program synthesis success rate increased from 80%to 89%.关键词
程序合成/SQL逆向合成/SQUARES/程序空间约简器/领域特定语言Key words
program synthesis/SQL reverse synthesis/SQUARES/program space reducer/domain-specific language分类
信息技术与安全科学引用本文复制引用
窦全胜,张顺,潘浩,王荟贤,唐焕玲..PSR-SQUARES:基于程序空间约简器的SQL逆向合成系统[J].通信学报,2023,44(11):249-259,11.基金项目
国家自然科学基金资助项目(No.61976124,No.61976125) （No.61976124,No.61976125）
新疆维吾尔自治区自然科学基金面上项目(No.2022D01A237,No.2022D01A238) The National Natural Science Foundation of China(No.61976124,No.61976125),The Natural Science Founda-tion of Xinjiang Uygur Autonomous Region(No.2022D01A237,No.2022D01A238) （No.2022D01A237,No.2022D01A238）
