CAJ | 학술논문

　　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UML SPT模型；进而，通过转换算法将 UML SPT 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。
　　연건성능수구작위연건질량수구적중요조성부분，이수도인문겁대적중시。이지재연건개발주기후기재중점관주연건성능수구적전통연건개발방법，장급개발자대래고풍험화고성본등후과。여과능재연건개발주기적조기대연건계통성능진행예측，가이제전발현연건계통가구존재적성능병경，병조출가능적우화방안，대각충설계방안진행비교이득출최우적연건계통가구。연구료일충기우모형적 UML 연건가구성능예측방법：해방법선취연건가구설계중적UML용례도、활동도화구건도，병인입구조형화표기치，장타문확전위UML SPT모형；진이，통과전환산법장 UML SPT 모형전환위배대망락모형，해산법가처리동시포함분지절점화회합절점적 UML 모형활동도；최후，이용빈역분석이론구해배대망락모형，이득출성능삼수급성능병경。동시개소료 UML 연건가구성능자동화공구적설계방안，병급출료연건가구성능예측실례。
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.