Automatic discovery and composition of Web services is an important research area in Web service technology, in which the specification of Web services is a key issue. This paper presents a Web service capability description framework based on the environment ontology. This framework depicts Web services capability in two aspects： the operable environment and the environment changes resulting from behaviors of the Web service. On the basis of the framework, a requirement-driven Web service composition model has been constructed. This paper brings forward the formalization of Web service interactions with π calculus. And an automatic mechanism converting conceptual capability description to the formal process expression has been built. This kind of formal specification assists in verifying whether the composite Web service model matches the requirement.
HOU Lishan1,3,JIN ZHi1,2 & WU Budan1,4 1. Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100080, China
The first part of this paper reviews our efforts on knowledge-based software engineering, namely PROMIS, started from 1990s. The key point of PROMIS is to generate applications automatically based on domain knowledge as well as software knowledge. That is featured by separating the development of domain knowledge from the development of software. But in PROMIS, we did not find an appropriate representation for the domain knowledge. Fortunately, in our recent work, we found such a carrier for knowledge modules, i.e. knowware. Knowware is a commercialized form of domain knowledge. This paper briefly introduces the basic definitions of knowware, knowledge middleware and knowware engineering. Three life circle models of knowware engineering and the design of corresponding knowware implementations are given. Finally we discuss application system automatic generation and domain knowledge modeling on the J2EE platform, which combines the techniques of PROMIS, knowware and J2EE, and the development and deployment framework, i.e. PROMIS/KW＊＊.
The role the quantum entanglement plays in quantum computation speedup has been widely disputed. Some believe that quantum computation's speedup over classical computation is impossible if entan-glement is absent,while others claim that the presence of entanglement is not a necessary condition for some quantum algorithms. This paper discusses this problem systematically. Simulating quantum computation with classical resources is analyzed and entanglement in known algorithms is reviewed. It is concluded that the presence of entanglement is a necessary but not sufficient condition in the pure state or pseudo-pure state quantum computation speedup. The case with the mixed state remains open. Further work on quantum computation will benefit from the presented results.
DING ShengChao1,3 & JIN Zhi1,2,1 Institute of Computing Technology,Chinese Academy of Sciences,Beijing 100080,China
Knowledge engineering stems from E. A. Figenbaum＇s proposal in 1977, but it will enter a new decade with the new challenges. This paper first summarizes three knowledge engineering experiments we have undertaken to show possibility of separating knowledge development from intelligent software development. We call it the ICAX mode of intelligent application software generation. The key of this mode is to generate knowledge base, which is the source of intelligence of ICAX software, independently and parallel to intelligent software development. That gives birth to a new and more general concept ＂knowware＂. Knowware is a commercialized knowledge module with documentation and intellectual property, which is computer operable, but free of any built-in control mechanism, meeting some industrial standards and embeddable in software/hardware. The process of development, application and management of knowware is called knowware engineering. Two different knowware life cycle models are discussed： the furnace model and the crystallization model. Knowledge middleware is a class of software functioning in all aspects of knowware life cycle models. Finally, this paper also presents some examples of building knowware in the domain of information system engineering.
Understanding the meaning of requirements can help elicit the real world requirements and refine their specifications. But what do the requirements of a desired software mean is not a well-explained question yet though there are many software development methods available. This paper suggests that the meaning of requirements could be depicted by the will-to-be environments of the desired software, and the optative interactions of the software with its environments as well as the causal relationships among these interactions. This paper also emphasizes the necessity of distinguishing the external manifestation from the internal structure of each system component during the process of requirements decomposition and refinement. Several decomposition strategies have been given to support the continuous decomposition. The external manifestation and the internal structure of the system component have been defined. The roles of the knowledge about the environments have been explicitly described. A simple but meaningful example embedded in the paper illustrates the main ideas as well as how to conduct the requirements decomposition and refinement by using these proposed strategies.
