11th IEEE International Software Metrics Symposium (METRICS'05)最新文献_第3页

Measurement-driven dashboards enable leading indicators for requirements and design of large-scale systems 测量驱动的仪表板为大型系统的需求和设计提供了领先的指标

11th IEEE International Software Metrics Symposium (METRICS'05) Pub Date : 2005-09-19 DOI: 10.1109/METRICS.2005.31

R. Selby

{"title":"Measurement-driven dashboards enable leading indicators for requirements and design of large-scale systems","authors":"R. Selby","doi":"10.1109/METRICS.2005.31","DOIUrl":"https://doi.org/10.1109/METRICS.2005.31","url":null,"abstract":"Measurement-driven dashboards provide a unifying mechanism for understanding, evaluating, and predicting the development, management, and economics of large-scale systems and processes. Dashboards enable interactive graphical displays of complex information and support flexible analytic capabilities for user customizability and extensibility. Dashboards commonly include software requirements and design metrics because they provide leading indicators for project size, growth, and stability. This paper focuses on dashboards that have been used on actual large-scale projects as well as example empirical relationships revealed by the dashboards. The empirical results focus on leading indicators for requirements and design of large-scale systems. In the first set of 14 projects focusing on requirements metrics, the ratio of software requirements to source-lines-of code averaged 1:46. Projects that far exceeded the 1:46 requirements-to-code ratio tended to be more effort-intensive and fault-prone during verification. In the second set of 16 projects focusing on design metrics, the components in the top quartile of the number of component internal states had 6.2 times more faults on average than did the components in the bottom quartile, after normalization by size. The components in the top quartile of the number of component interactions had 4.3 times more faults on average than did the components in the bottom quartile, after normalization by size. When the number of component internal states was in the bottom quartile, the component fault-proneness was low even when the number of component interactions was in the upper quartiles, regardless of size normalization. Measurement-driven dashboards reveal insights that increase visibility into large-scale systems and provide feedback to organizations and projects","PeriodicalId":402415,"journal":{"name":"11th IEEE International Software Metrics Symposium (METRICS'05)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132743796","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 14

What should you optimize when building an estimation model? 在构建评估模型时应该优化什么?

11th IEEE International Software Metrics Symposium (METRICS'05) Pub Date : 2005-09-19 DOI: 10.1109/METRICS.2005.55

C. Lokan

引用次数: 35

An empirical analysis of software productivity over time 软件生产力随时间变化的实证分析

11th IEEE International Software Metrics Symposium (METRICS'05) Pub Date : 2005-09-19 DOI: 10.1109/METRICS.2005.8

Rahul Premraj, M. Shepperd, B. Kitchenham, Pekka Forselius

引用次数: 87

Can We Teach Empirical Software Engineering? 我们能教实证软件工程吗?

11th IEEE International Software Metrics Symposium (METRICS'05) Pub Date : 2005-09-19 DOI: 10.1109/METRICS.2005.16

M. L. Jaccheri, Thomas Østerlie

引用次数: 9

Product Metrics for Automatic Identification of "Bad Smell" Design Problems in Java Source-Code 在Java源代码中自动识别“臭味”设计问题的产品度量

11th IEEE International Software Metrics Symposium (METRICS'05) Pub Date : 2005-09-19 DOI: 10.1109/METRICS.2005.38

M. Munro

{"title":"Product Metrics for Automatic Identification of \"Bad Smell\" Design Problems in Java Source-Code","authors":"M. Munro","doi":"10.1109/METRICS.2005.38","DOIUrl":"https://doi.org/10.1109/METRICS.2005.38","url":null,"abstract":"Refactoring can have a direct influence on reducing the cost of software maintenance through changing the internal structure of the source-code to improve the overall design that helps the present and future programmers evolve and understand a system. Bad smells are a set of design problems with refactoring identified as a solution. Locating these bad smells has been described as more a human intuition than an exact science. This paper addresses the issue of identifying the characteristics of a bad smell through the use of a set of software metrics. Then by using a pre-defined set of interpretation rules to interpret the software metric results applied to Java source-code, the software engineer can be provided with significant guidance as to the location of bad smells. These issues are addressed in a number of ways. Firstly, a precise definition of bad smells is given from the informal descriptions given by the originators Fowler and Beck. The characteristics of the bad smells have been used to define a set of measurements and interpretation rules for a subset of the bad smells. A prototype tool has been implemented to enable the evaluation of the interpretation rules in two case studies.","PeriodicalId":402415,"journal":{"name":"11th IEEE International Software Metrics Symposium (METRICS'05)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123230010","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 237

An empirical assessment of function point-like object-oriented metrics 功能点类面向对象度量的经验评估

11th IEEE International Software Metrics Symposium (METRICS'05) Pub Date : 2005-09-19 DOI: 10.1109/METRICS.2005.9

V. D. Bianco, L. Lavazza

引用次数: 12

The clients' impact on effort estimation accuracy in software development projects 客户对软件开发项目中工作量估算准确性的影响

11th IEEE International Software Metrics Symposium (METRICS'05) Pub Date : 2005-09-19 DOI: 10.1109/METRICS.2005.47

Stein Grimstad, M. Jørgensen, Kjetil Moløkken-Østvold

引用次数: 19

Finding predictors of field defects for open source software systems in commonly available data sources: a case study of OpenBSD 在通常可用的数据源中为开源软件系统寻找领域缺陷的预测器:OpenBSD的一个案例研究

11th IEEE International Software Metrics Symposium (METRICS'05) Pub Date : 2005-09-19 DOI: 10.1109/METRICS.2005.26

P. Li, J. Herbsleb, M. Shaw

{"title":"Finding predictors of field defects for open source software systems in commonly available data sources: a case study of OpenBSD","authors":"P. Li, J. Herbsleb, M. Shaw","doi":"10.1109/METRICS.2005.26","DOIUrl":"https://doi.org/10.1109/METRICS.2005.26","url":null,"abstract":"Open source software systems are important components of many business software applications. Field defect predictions for open source software systems may allow organizations to make informed decisions regarding open source software components. In this paper, we remotely measure and analyze predictors (metrics available before release) mined from established data sources (the code repository and the request tracking system) as well as a novel source of data (mailing list archives) for nine releases of OpenBSD. First, we attempt to predict field defects by extending a software reliability model fitted to development defects. We find this approach to be infeasible, which motivates examining metrics-based field defect prediction. Then, we evaluate 139 predictors using established statistical methods: Kendall's rank correlation, Pearson's rank correlation, and forward AIC model selection. The metrics we collect include product metrics, development metrics, deployment and usage metrics, and software and hardware configurations metrics. We find the number of messages to the technical discussion mailing list during the development period (a deployment and usage metric captured from mailing list archives) to be the best predictor of field defects. Our work identifies predictors of field defects in commonly available data sources for open source software systems and is a step towards metrics-based field defect prediction for quantitatively-based decision making regarding open source software components","PeriodicalId":402415,"journal":{"name":"11th IEEE International Software Metrics Symposium (METRICS'05)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116934466","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 55

Refactoring for changeability: a way to go? 为可变性而重构:一种可行的方法?

11th IEEE International Software Metrics Symposium (METRICS'05) Pub Date : 2005-09-19 DOI: 10.1109/METRICS.2005.40

B. Geppert, A. Mockus, F. Rößler

引用次数: 50

On refactoring support based on code clone dependency relation 基于代码克隆依赖关系的重构支持

11th IEEE International Software Metrics Symposium (METRICS'05) Pub Date : 2005-09-19 DOI: 10.1109/METRICS.2005.36

Norihiro Yoshida, Yoshiki Higo, Toshihiro Kamiya, S. Kusumoto, Katsuro Inoue

引用次数: 34