Before developing any Service-Oriented Architecture (SOA) based software, effort estimation will be inevitably required for many purposes ranging from budget analysis to cost-benefit balance. Therefore, effort estimation plays a vital role in SOA implementations. Nevertheless, effort estimation for SOA implementation confronts many challenges due to both the complexity of SOA and the diversity of SOA projects. The current approaches based on traditional techniques are normally not adequate for estimating the effort of SOA implementations. Meanwhile, there is a lack of work on effort estimation for SOA implementation within the published literature. To decrease the complexity and difficulty of the problems of effort estimation before building SOA systems, this thesis concentrates on one particular type of SOA projects: service composition based SOA implementations. As enterprises move to having more and more services, and business applications increasingly rely on subscribing services, the major problem in SOA implementations will be service composition and may be less on development of new services. Moreover, it has been identified that the benefits of SOA cannot be fully realized until reaching the level of service composition. Therefore, it is worthwhile to narrow down our concerns from generic SOA implementations to service composition based SOA implementations that do not take into account service migration or new service development. Considering Web service is the de facto representation of service in practice, we can further focus on Web service composition (WSC) based SOA implementations.Considering the limitations to empirically implementing SOA projects by using various WSC approaches, ?learning by doing? is nearly an impossible way to collect development data for quantitatively unfolding the research into effort estimation for WSC-based SOA implementations. Fortunately, ?learning by analogy? is a feasible alternative to investigate distributed systems like SOA systems. After comprehending generic SOA implementations from an organizational perspective and viewing WSC-based SOA systems as mechanistic organizations, we borrow Divide-and-Conquer (D&C) from the organization theory domain as a generic strategy of effort judgment for WSC-based SOA implementations. Through the generic strategy D&C, the work on effort judgment for a whole WSC-based SOA implementation can be further narrowed down to that for individual WSCs. When it comes to the effort judgment for individual WSC approaches, it is necessary to draw some classification, and thereby facilitate the effort judgment for different type of WSC approaches. To overcome the deficiencies of existing classifications for WSC, this thesis introduces a novel classification matrix aimed at putting the influence on the effort involved in WSC. The matrix uses clarified terminology, and differentiates the classifications between the Context and Process dimensions. The Context dimension includes five effort-related contexts, while the Process dimension is divided into three process models. Considering the different influences of different contexts and processes on the composition effort, those process models and context types in the classification matrix can be viewed as effort factors when composing Web services. Therefore, we can use this classification matrix to facilitate the effort judgment for different WSC approaches. After applying a set of qualitative effort-related hypotheses to WSC effort factors that are identified by the aforementioned classification matrix, this thesis employs several rules to assign effort scores to different factors and different types of WSC approaches. These effort scores are used to facilitate qualitatively judging different effort between different types of WSC approaches, and eventually construct an effort checklist for WSC approaches. For a certain WSC-based SOA implementation, designers and developers can use this effort checklist together with the D&C algorithm to further calculate effort scores of different implementation proposals, and therefore conveniently and qualitatively compare the effort required by different proposals.
