Adaptation of software components to the requirements is one of the key concerns in Component Based Software Development (CBSD). In this paper, we propose a formal approach to compose component based systems which are adaptable to the requirements. We focus on the functional aspects of software components and requirements, which are expressed in S-sorted functions. Those S-sorted functions are transformed into Colored Petri Nets (CPN) models in order to evaluate connectivity between the components, and to evaluate adaptability of composed systems to the requirements. The connectivity is measured based on colors or data types in CPN, while the adaptability is measured based on functional equivalency. We introduce simple glue codes to connect the components each other. The paper focuses on business applications, however the proposed approach can be applied to any other domains as far as the functional adaptability is concerned.

It is one of the difficulties in enterprise modeling that we must deal with many fragmented pieces of knowledge provided by various domain-experts, which are usually based on mutually different viewpoints of them. This paper presents a formal approach to integrate those pieces into enterprise-wide model units using Rough Set Theory (RST). We focus on business processes in order to recognize and identify the constituents or units of enterprise models, which would compose the model expressing the various aspects of the enterprise. We defined five model unit types of "resource," "organization," "task," "function," and "behavior. " The first three types represent the static aspect of the enterprise, whereas the last two types represent the dynamic aspect of it. Those units are initially elicited from each domain-expert as his/her own individual model units, then they are integrated into enterprise-wide units using RST. Our approach is methodology-free, and any methodologies can include it in their early stage to identify what composes the enterprise.

Adaptability evaluation of software systems is one of the key concerns in both software engineering and requirements engineering. In this paper, we present a formal and systematic approach to evaluate adaptability of software systems to requirements in enterprise business applications. Our approach consists of three major parts, that is, the common modeling method for both business realms and software realms, functional adaptability evaluation between the models with Σ algebra and behavioral adaptability evaluation with process algebra. By our approach, one can rigorously and uniquely determine whether a software system is adaptable to the requirements, either totally or partially. A sample application from an order processing is illustrated to show how this approach is effective in solving the adaptability evolution problem.

Software Composition is one of the major concerns in component based software development (CBSD). In this paper, we present a formal approach to construct software systems from requirements models using available components. We focus on the knowledge resides in the requirements and the components in order to deal with those heterogeneous concepts. This approach consists of three steps. The first step is selecting adaptable components to the requirements model. The requirements and the components are transformed into the form of Σ algebra, and the component adaptability is evaluated by Σ homomorphism. Rough Set Theory (RST) is used to make carriers of two Σ algebras common, which are derived from the requirements and the components. The second step is identifying the control structure of the requirements. Decision tables are used for representing the knowledge on the requirements, and RST is used to optimize the control structure. The third step is to implement the control structure as glue codes which would perform the components appropriately. This approach mainly focuses on enterprise back-office applications in this paper, however, it can be easily applied to other domains, since it assumes the requirements to be expressed in Colored Petri Nets (CPN), and CPN can express various problem domains other than enterprise back-office applications.