Raheleh Rahmati, A. Rasoolzadegan, Diyana Tehrany Dehkordy
{"title":"GoF设计模式的自动选择方法","authors":"Raheleh Rahmati, A. Rasoolzadegan, Diyana Tehrany Dehkordy","doi":"10.1109/ICCKE48569.2019.8965221","DOIUrl":null,"url":null,"abstract":"Nowadays, an increase in the growth of software systems has risen the importance of the design phase. So far, developers have introduced numerous software design patterns. This study presents a new method to select the Gang of Four (GoF) design patterns. The proposed method is implemented based on the vector space model (VSM). In this method, the Term Frequency-Inverse Document Frequency (TF-IDF) weighting algorithm has been improved to determine the similarity between two texts, more accurately. Also, we used a set of hyponyms and synonyms of the words in weighting. We evaluated the proposed method with 23 design patterns, 29 object-oriented related design problems, and nine real-world problems. Finally, we observed promising results compared to other methods. We found 8.5%, 1.2%, and 5.2% improvement in terms of precision, recall, and accuracy of the proposed method as compared to other methods.","PeriodicalId":6685,"journal":{"name":"2019 9th International Conference on Computer and Knowledge Engineering (ICCKE)","volume":"44 1","pages":"345-350"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"An Automated Method for Selecting GoF Design Patterns\",\"authors\":\"Raheleh Rahmati, A. Rasoolzadegan, Diyana Tehrany Dehkordy\",\"doi\":\"10.1109/ICCKE48569.2019.8965221\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Nowadays, an increase in the growth of software systems has risen the importance of the design phase. So far, developers have introduced numerous software design patterns. This study presents a new method to select the Gang of Four (GoF) design patterns. The proposed method is implemented based on the vector space model (VSM). In this method, the Term Frequency-Inverse Document Frequency (TF-IDF) weighting algorithm has been improved to determine the similarity between two texts, more accurately. Also, we used a set of hyponyms and synonyms of the words in weighting. We evaluated the proposed method with 23 design patterns, 29 object-oriented related design problems, and nine real-world problems. Finally, we observed promising results compared to other methods. We found 8.5%, 1.2%, and 5.2% improvement in terms of precision, recall, and accuracy of the proposed method as compared to other methods.\",\"PeriodicalId\":6685,\"journal\":{\"name\":\"2019 9th International Conference on Computer and Knowledge Engineering (ICCKE)\",\"volume\":\"44 1\",\"pages\":\"345-350\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 9th International Conference on Computer and Knowledge Engineering (ICCKE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCKE48569.2019.8965221\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 9th International Conference on Computer and Knowledge Engineering (ICCKE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCKE48569.2019.8965221","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Automated Method for Selecting GoF Design Patterns
Nowadays, an increase in the growth of software systems has risen the importance of the design phase. So far, developers have introduced numerous software design patterns. This study presents a new method to select the Gang of Four (GoF) design patterns. The proposed method is implemented based on the vector space model (VSM). In this method, the Term Frequency-Inverse Document Frequency (TF-IDF) weighting algorithm has been improved to determine the similarity between two texts, more accurately. Also, we used a set of hyponyms and synonyms of the words in weighting. We evaluated the proposed method with 23 design patterns, 29 object-oriented related design problems, and nine real-world problems. Finally, we observed promising results compared to other methods. We found 8.5%, 1.2%, and 5.2% improvement in terms of precision, recall, and accuracy of the proposed method as compared to other methods.