{"title":"低代码开发生产率","authors":"João Varajão, António Trigo, Miguel Almeida","doi":"10.1145/3631183","DOIUrl":null,"url":null,"abstract":"This article aims to provide new insights on the subject by presenting the results of laboratory experiments carried out with code-based, low-code, and extreme low-code technologies to study differences in productivity. Low-code technologies have clearly shown higher levels of productivity, providing strong arguments for low-code to dominate the software development mainstream in the short/medium term. The article reports the procedure and protocols, results, limitations, and opportunities for future research.","PeriodicalId":39042,"journal":{"name":"Queue","volume":"168 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Low-code Development Productivity\",\"authors\":\"João Varajão, António Trigo, Miguel Almeida\",\"doi\":\"10.1145/3631183\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article aims to provide new insights on the subject by presenting the results of laboratory experiments carried out with code-based, low-code, and extreme low-code technologies to study differences in productivity. Low-code technologies have clearly shown higher levels of productivity, providing strong arguments for low-code to dominate the software development mainstream in the short/medium term. The article reports the procedure and protocols, results, limitations, and opportunities for future research.\",\"PeriodicalId\":39042,\"journal\":{\"name\":\"Queue\",\"volume\":\"168 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-10-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Queue\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3631183\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Computer Science\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Queue","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3631183","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Computer Science","Score":null,"Total":0}
This article aims to provide new insights on the subject by presenting the results of laboratory experiments carried out with code-based, low-code, and extreme low-code technologies to study differences in productivity. Low-code technologies have clearly shown higher levels of productivity, providing strong arguments for low-code to dominate the software development mainstream in the short/medium term. The article reports the procedure and protocols, results, limitations, and opportunities for future research.