Reconciling Synthesis and Decomposition: A Composite Approach to Capability Identification

TL;DR

This paper introduces a composite algorithm combining synthesis and decomposition methods for identifying system Capabilities, enhancing change-tolerance in large-scale software development by balancing aggregation and partitioning techniques.

Contribution

It proposes a novel composite approach that integrates synthesis and decomposition algorithms for Capability identification, improving flexibility and design quality.

Findings

Neither synthesis nor decomposition alone suffices for effective Capability identification.

The composite algorithm yields more feasible and balanced Capabilities.

Empirical analysis on a library system demonstrates the effectiveness of the combined approach.

Abstract

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.