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signature. Therefore, more input from process designers is needed; and
(3) in our practice of business process engineering, every solution
generated by automatic algorithms must be examined and refined
before it is put into real execution.
Thus, our solution approach can be extended to the scenario that
allows choices and loops. However, in this chapter, we focus on a
conflict-free approach to quickly identify the relevant part inside the
service portfolio and generate solution backbones. These backbones
can be combined and merged to form solutions that can contain choices
and loops when required.
3.7 SUMMARY
It is necessary to have a method that enhances the reusability of a service
portfolio by generating composition guidance when fulfilling a business
requirement. This research can be seen as an important step towards the
effort to bridge the gap between business and service domains in building
enterprise SOA solutions. We utilize data relations in both domains and
add data mediation constructs to make the data model in these domains
complete and coherent. We devise three composition rules: sequential,
parallel, and choice, based on the augmented data model. Based on the
data relations and composition rules, we propose a formal method to
derive all the possible composition candidates, given a service portfolio.
First, we obtain a connected service net from the given service portfolio;
then, we reduce the service net with respect to the given requirement
(i.e., the input/output signature); and finally, we decompose the reduced
service net into subnets, each of which represents a composition candi-
date. A prototype system is developed, and an example is given to
validate our approach as well as the algorithm.
In summary, through our approach, we can quickly choose opera-
tions related to the business requirement and chain them together as a
process. The contributions of this chapter are summarized as follows:
1. A lightweight approach making the best use of the existing
service portfolio in enterprise SOA solutions. It does not need
additional semantic information. What we need is data type
and data relation definition in both business and service
domains. Such information can be obtained by parsing
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