模糊综合与分解：一种复合的能力识别方法
Reconciling Synthesis and Decomposition: A Composite Approach to Capability Identification
摘要：
利益相关者的期望和技术在大规模计算机系统的漫长开发周期中不断发展。因此，确定要求基线的传统方法导致一个不能令人满意的系统，因为它没有能力适应这种变化。相比之下，基于能力构建的系统更具变化容忍性;能力是功能抽象，既不像用户需求那样无定形，也不像系统需求那样刚性。或者，能力是从用户的需求中捕获所需功能的集合，并且被设计为表现出高内聚、低耦合和最佳抽象级别的所需软件工程特性。为了制定这些功能抽象，我们开发和研究两种算法的能力识别：合成和分解。综合算法将系统的详细基本元素聚集在一起形成能力。相反，分解算法通过递归地将系统的总体任务划分为更详细的实体来确定能力。对一个小型计算机图书馆系统的实证分析表明，这两种方法本身都是不够的。然而，一个复合算法的基础上的一个互补的方法，调和两个极性的观点，结果在一个更可行的能力。特别地，复合算法使用由分解算法定义的内聚和耦合度量以及由合成算法确定的抽象级别来制定能力。
英文摘要：
Stakeholders' expectations and technology constantly evolve during the lengthy development cycles of a large-scale computer based system. Consequently, the traditional approach of baselining requirements results in an unsatisfactory system because it is ill-equipped to accommodate such change. In contrast, systems constructed on the basis of Capabilities are more change-tolerant; Capabilities are functional abstractions that are neither as amorphous as user needs nor as rigid as system requirements. Alternatively, Capabilities are aggregates that capture desired functionality from the users' needs, and are designed to exhibit desirable software engineering characteristics of high cohesion, low coupling and optimum abstraction levels. To formulate these functional abstractions we develop and investigate two algorithms for Capability identification: Synthesis and Decomposition. The synthesis algorithm aggregates detailed rudimentary elements of the system to form Capabilities. In contrast, the decomposition algorithm determines Capabilities by recursively partitioning the overall mission of the system into more detailed entities. Empirical analysis on a small computer based library system reveals that neither approach is sufficient by itself. However, a composite algorithm based on a complementary approach reconciling the two polar perspectives results in a more feasible set of Capabilities. In particular, the composite algorithm formulates Capabilities using the cohesion and coupling measures as defined by the decomposition algorithm and the abstraction level as determined by the synthesis algorithm.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
