位置:成果数据库 > 期刊 > 期刊详情页
一种UML软件架构性能预测方法及其自动化研究
  • ISSN号:1660-9336
  • 期刊名称:软件学报
  • 时间:0
  • 页码:-
  • 分类:TP311[自动化与计算机技术—计算机软件与理论;自动化与计算机技术—计算机科学与技术]
  • 作者机构:[1]浙江工商大学信息与电子工程学院,浙江杭州310018
  • 相关基金:国家重点基础研究发展计划(973)(2012cB315902);国家自然科学基金(61102074,61170215);国家高技术研究发展计划(863)(SQ2009AA01XK1485130);浙江省教育厅项目(Y201018208);浙江省科技计划(201IC21049);浙江省重点科技创新团队资助项目(2011R50010)
  • 相关项目:ForCES传输映射层(TML)关键技术问题研究
中文摘要:

软件性能需求作为软件质量需求的重要组成部分,已受到人们极大的重视.而只在软件开发周期后期才重点关注软件性能需求的传统软件开发方法,将给开发者带来高风险和高成本等后果.如果能在软件开发周期的早期对软件系统性能进行预测,可以提前发现软件系统架构存在的性能瓶颈,并找出可能的优化方案,对各种设计方案进行比较以得出最优的软件系统架构.研究了一种基于模型的UML软件架构性能预测方法:该方法选取软件架构设计中的UML用例图、活动图和构件图,并引入构造型和标记值,将它们扩展为UMLSPT模型;进而,通过转换算法将UMLSPT模型转换为排队网络模型,该算法可处理同时包含分支节点和汇合节点的UML模型活动图:最后,利用频域分析理论求解排队网络模型,以得出性能参数及性能瓶颈.同时介绍了UML软件架构性能自动化工具的设计方案,并给出了软件架构性能预测实例.

英文摘要:

The requirement of software performance as an important part of the software quality requirements is very concerning. The traditional software development methods that focus on the software performance issues later in the development process will bring high risks and high costs. If the performance of software architecture can be predicted at the early phases of the development cycle, the performance bottlenecks can be found in advance, and the possible optimization also can be worked out. In this paper, a model-based UML software architectures performance prediction method is introduced. This method selects and uses case diagrams, activity diagrams and component diagrams, and extends them to UML SPT (schedulability, performance and time) model by introducing the stereotypes and tagged values. It then transforms these UML SPT models into queueing network model through an algorithm which can handle the activity diagram with both branch nodes and confluence nodes. At last, uses the analysis theory of frequency domain to solve queuing network model to derive the performance parameters and performance bottlenecks. At the same time, the design of an automatic performance analysis tool for UML software architecture is introduced, and an instance of performance prediction is given.

同期刊论文项目
期刊论文 4 会议论文 8 获奖 6 专利 5
同项目期刊论文