What is Mid-Level Splitting Technique

With service-oriented systems driving the economies around the world there has been an exponential rise in the number and choices of available services. As a result of this, for most tasks there are a large number of services that can adequately cater to the requirements of the customers. Choosing the service that best conforms to the requirements from the set of functionally equivalent services is non-trivial. Research in the past has utilized the non-functional attributes of such services to select the best service. These efforts however make the assumption that the services with the best non-functional attributes are the ones that most closely conform to the requirements of the customer. This is not always true since the customer may sometimes prefer to settle for a slightly “inferior” service owing to price constraints. In this chapter, we apply the Mid-level Splitting technique to better assess the requirements of the customer and make a more judicious service selection. Furthermore, we also address the issue of assignment of weights to the various non-functional attributes of the services. These weights are reflective of the emphasis that the concerned customer wants to put on the various non-functional attributes of the service. These weights are normally assigned based on the intuition of certain expert personnel and are prone to human error and incorrect judgment. We utilize the Hypothetical Equivalents and Inequivalents technique to more systematically assign weights to the services based on customer preferences. The techniques are demonstrated with a real world example.