{"title":"比较使用基于敏捷模型的软件工程方法与仅使用Scrum的度量敏捷软件开发指标","authors":"Moe Huss, Daniel R. Herber, J. Borky","doi":"10.3390/software2030015","DOIUrl":null,"url":null,"abstract":"This study compares the reliability of estimation, productivity, and defect rate metrics for sprints driven by a specific instance of the agile approach (i.e., scrum) and an agile model-Bbased software engineering (MBSE) approach called the integrated Scrum Model-Based System Architecture Process (sMBSAP) when developing a software system. The quasi-experimental study conducted ten sprints using each approach. The approaches were then evaluated based on their effectiveness in helping the product development team estimate the backlog items that they could build during a time-boxed sprint and deliver more product backlog items (PBI) with fewer defects. The commitment reliability (CR) was calculated to compare the reliability of estimation with a measured average scrum-driven value of 0.81 versus a statistically different average sMBSAP-driven value of 0.94. Similarly, the average sprint velocity (SV) for the scrum-driven sprints was 26.8 versus 31.8 for the MBSAP-driven sprints. The average defect density (DD) for the scrum-driven sprints was 0.91, while that of the sMBSAP-driven sprints was 0.63. The average defect leakage (DL) for the scrum-driven sprints was 0.20, while that of the sMBSAP-driven sprints was 0.15. The t-test analysis concluded that the sMBSAP-driven sprints were associated with a statistically significant larger mean CR, SV, DD, and DL than that of the scrum-driven sprints. The overall results demonstrate formal quantitative benefits of an agile MBSE approach compared to an agile alone, thereby strengthening the case for considering agile MBSE methods within the software development community. Future work might include comparing agile and agile MBSE methods using alternative research designs and further software development objectives, techniques, and metrics.","PeriodicalId":50378,"journal":{"name":"IET Software","volume":"43 1","pages":""},"PeriodicalIF":1.5000,"publicationDate":"2023-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Comparing Measured Agile Software Development Metrics Using an Agile Model-Based Software Engineering Approach versus Scrum Only\",\"authors\":\"Moe Huss, Daniel R. Herber, J. Borky\",\"doi\":\"10.3390/software2030015\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study compares the reliability of estimation, productivity, and defect rate metrics for sprints driven by a specific instance of the agile approach (i.e., scrum) and an agile model-Bbased software engineering (MBSE) approach called the integrated Scrum Model-Based System Architecture Process (sMBSAP) when developing a software system. The quasi-experimental study conducted ten sprints using each approach. The approaches were then evaluated based on their effectiveness in helping the product development team estimate the backlog items that they could build during a time-boxed sprint and deliver more product backlog items (PBI) with fewer defects. The commitment reliability (CR) was calculated to compare the reliability of estimation with a measured average scrum-driven value of 0.81 versus a statistically different average sMBSAP-driven value of 0.94. Similarly, the average sprint velocity (SV) for the scrum-driven sprints was 26.8 versus 31.8 for the MBSAP-driven sprints. The average defect density (DD) for the scrum-driven sprints was 0.91, while that of the sMBSAP-driven sprints was 0.63. The average defect leakage (DL) for the scrum-driven sprints was 0.20, while that of the sMBSAP-driven sprints was 0.15. The t-test analysis concluded that the sMBSAP-driven sprints were associated with a statistically significant larger mean CR, SV, DD, and DL than that of the scrum-driven sprints. The overall results demonstrate formal quantitative benefits of an agile MBSE approach compared to an agile alone, thereby strengthening the case for considering agile MBSE methods within the software development community. Future work might include comparing agile and agile MBSE methods using alternative research designs and further software development objectives, techniques, and metrics.\",\"PeriodicalId\":50378,\"journal\":{\"name\":\"IET Software\",\"volume\":\"43 1\",\"pages\":\"\"},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2023-07-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IET Software\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.3390/software2030015\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, SOFTWARE ENGINEERING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IET Software","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.3390/software2030015","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
Comparing Measured Agile Software Development Metrics Using an Agile Model-Based Software Engineering Approach versus Scrum Only
This study compares the reliability of estimation, productivity, and defect rate metrics for sprints driven by a specific instance of the agile approach (i.e., scrum) and an agile model-Bbased software engineering (MBSE) approach called the integrated Scrum Model-Based System Architecture Process (sMBSAP) when developing a software system. The quasi-experimental study conducted ten sprints using each approach. The approaches were then evaluated based on their effectiveness in helping the product development team estimate the backlog items that they could build during a time-boxed sprint and deliver more product backlog items (PBI) with fewer defects. The commitment reliability (CR) was calculated to compare the reliability of estimation with a measured average scrum-driven value of 0.81 versus a statistically different average sMBSAP-driven value of 0.94. Similarly, the average sprint velocity (SV) for the scrum-driven sprints was 26.8 versus 31.8 for the MBSAP-driven sprints. The average defect density (DD) for the scrum-driven sprints was 0.91, while that of the sMBSAP-driven sprints was 0.63. The average defect leakage (DL) for the scrum-driven sprints was 0.20, while that of the sMBSAP-driven sprints was 0.15. The t-test analysis concluded that the sMBSAP-driven sprints were associated with a statistically significant larger mean CR, SV, DD, and DL than that of the scrum-driven sprints. The overall results demonstrate formal quantitative benefits of an agile MBSE approach compared to an agile alone, thereby strengthening the case for considering agile MBSE methods within the software development community. Future work might include comparing agile and agile MBSE methods using alternative research designs and further software development objectives, techniques, and metrics.
期刊介绍:
IET Software publishes papers on all aspects of the software lifecycle, including design, development, implementation and maintenance. The focus of the journal is on the methods used to develop and maintain software, and their practical application.
Authors are especially encouraged to submit papers on the following topics, although papers on all aspects of software engineering are welcome:
Software and systems requirements engineering
Formal methods, design methods, practice and experience
Software architecture, aspect and object orientation, reuse and re-engineering
Testing, verification and validation techniques
Software dependability and measurement
Human systems engineering and human-computer interaction
Knowledge engineering; expert and knowledge-based systems, intelligent agents
Information systems engineering
Application of software engineering in industry and commerce
Software engineering technology transfer
Management of software development
Theoretical aspects of software development
Machine learning
Big data and big code
Cloud computing
Current Special Issue. Call for papers:
Knowledge Discovery for Software Development - https://digital-library.theiet.org/files/IET_SEN_CFP_KDSD.pdf
Big Data Analytics for Sustainable Software Development - https://digital-library.theiet.org/files/IET_SEN_CFP_BDASSD.pdf