Fine-Grained Metrics of Cohesion Lack for Service Interfaces

Abstract

A design issue that often appears in real-world services is that their interfaces are not cohesive, i.e., they consist of many and possibly unrelated operations. This issue may complicate the comprehension of the services functionalities and the maintenance of the applications that use them. Currently, the state of the art on case studies that focus on the evaluation of the cohesion of services offered by major service providers is limited, while research efforts on corresponding cohesion metrics are at a quite early stage. In particular, there exist coarse-grained metrics of cohesion lack, which consider that the operations of a service interface are related if the types of certain of their input/output data exactly match. The problem in this approach is that operations which operate on data characterized by similar, but not exactly matching, types are treated as being totally unrelated. Consequently, the aforementioned metrics may overestimate the cohesion lack of service interfaces. In this paper, we undertake a more elaborate approach to evaluate a set of real world services provided by Amazon. Specifically, we propose two fine-grained metrics of cohesion lack, which are defined with respect to the structural similarity of the input/output data types of interface operations. The proposed metrics are formally defined and analytically assessed with respect to fundamental properties of software metrics. Finally we report the results from our case study.