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Reactive rules are used for programming rule-based Web agents, which have the ability to detect events and respond to them automatically and can have complex structure and unpredictable behavior. The aim of this paper is to provide an appropriate formal framework for analyzing such rules.

To achieve this goal, the authors give two alternative semantics for the basic reactive rules’ families which allow us to specify reactive rule-based agents and verify their intended behavior. The first approach expresses the functionality of production and event condition action rules in terms of equations, whereas the second methodology is based in the formalism of rewriting logic. Both semantics can be expressed within the framework of CafeOBJ algebraic specification language, which then offers the verification support and have their advantages and downsides.

The authors report on experiences gained by applying those methodologies in a reactive rule-based system and compare the two methodologies.

Finally, the authors demonstrate a tool that translates a set of reactive rules into CafeOBJ rewrite rules, thus making the verification of reactive rules possible for inexperienced users.

The OTS/CafeOBJ method can be used to formally model, specify and verify distributed systems such as security protocols and railroad systems. A distributed system is modeled as an OTS, a kind of transition system, and the OTS is specified and verified with CafeOBJ, an algebraic specification language. Case analysis (or case splitting) is one of the most intellectual pieces of work in verification. Case analysis should be done entirely by hand in the OTS/CafeOBJ method, which is errorprone. It is indispensable to cover all cases and find necessary lemmas for some sub‐cases where desired results are not obtained in case analysis. We propose two methods of mechanically supporting case analysis, which concern these two issues. A case study that the proposed methods are effectively applied to a railroad signaling system is also reported.

This purpose of this paper is to identify and prioritize the critical factors impacting knowledge sharing (KS) in technology-intensive manufacturing organizations in the United Arab Emirates (UAE) and to propose a decision-making framework for KS.

Analytical Hierarchical Process method is used to identify these critical factors impacting KS in technology-intensive manufacturing organizations in the UAE.

Results show that organizational leadership and culture are the most critical factors impacting KS in the technology-intensive manufacturing organizations.

The data are collected from technology-intensive manufacturing organizations in the UAE; therefore, these cannot be generalized to other locations. Future research in different countries is required.

To implement successful KS practices in technology-intensive manufacturing organizations, it is essential that all impacting factors and sub-factors are well understood within the organizations.

This study is among the first studies in the region that presents a comprehensive framework for KS in manufacturing sector.