One of the main characteristics of business rules is their propensity for frequent change, due to internal or external factors to an enterprise.As these rules change, their immediate dissemination across people and systems in an enterprise becomes vital.The delay in dissemination can adversely impact the reputation of the enterprise, and cause significant loss of revenue.The current BRMS are often maintained by the IT group within a company, therefore the modifications of the BRs intended by executive management would not be instantaneous, since they have to be coded, and tested before being deployed.Moreover, the executives might not have the possibility to take the best decisions, without having the benefit of analyzing historical data, and quickly simulating what-if scenarios to visualize the effects of a set of rules on the business.Some of the systems that provide this functionality are prohibitively expensive.This paper addresses these challenges by using the power of Big Data analysis to source, clean and analyze historical data that is used for mining business rules, which can be visualized, tested on what-if scenarios, and immediately deployed without the intervention of the IT group.The proposed approach is instantiated in this paper by using open source components to mine stop loss rules for financial systems.

The easy path wavelet transform (EPWT) has recently been proposed by one of the authors as a tool for sparse representations of bivariate functions from discrete data, in particular from image data. The EPWT is a locally adaptive wavelet transform. It works along pathways through the array of function values and exploits the local correlations of the given data in a simple appropriate manner. However, the EPWT suffers from its adaptivity costs that arise from the storage of path vectors. In this paper, we propose a new hybrid method for image approximation that exploits the advantages of the usual tensor product wavelet transform for the representation of smooth images and uses the EPWT for an efficient representation of edges and texture. Numerical results show the efficiency of this procedure.

A workflow management system determines the flow of work according to predefined business process definitions. It manages the resources required to meet goals and provides monitoring facilities and control capabilities. Resources can become important decision factors when combined with control flow information. This is particularly true in an emergency response system where large quantities of resources, including emergency responders, ambulances, fire trucks, medications, food, clothing, etc., are required. In this paper, we introduce a resource-constrained and decision support workflow model. This model enables users to specify resource consumption and production when executing a task, and decision policies to choose a path at a given situation where multiple execution branches are available. The paper also presents an efficient resource requirement analysis algorithm that can be used to decide the minimum resource set that, if satisfied, the workflow can be executed along any possible path till finish without the occurrence of resource shortage. A case study is presented to show the use of the proposed approach.

The workflow management of incident command systems (ICSs) has been challenged by the systems' special requirements on flexibility, intuitiveness, and capacity of correctness verification. The significance of applying formal approaches to the modeling and analysis of workflows has been well recognized, and many such approaches have been proposed. However, these approaches require users to master considerable knowledge of the particular formalisms, which impacts the application of these approaches on a larger scale. This paper presents a new formal, yet intuitive, approach for the modeling and analysis of workflows, which attempts to overcome the aforementioned problem. In addition to the abilities of supporting workflow validation and enactment, this new approach possesses the distinguishing feature of allowing users who are not proficient in formal methods to build up and dynamically modify the workflow models that address the flexibility needs of ICSs.

Business processes are often constrained by resource availability. This is particularly true in an emergency response system where large quantity of resources, including emergency responders, ambulances, fire trucks, medications, food, clothing, etc., are required. In our previous work, we introduced WIFA model to meet the needs of incident command systems workflow modeling and analysis. In this paper, we extend WIFA to take resources into account when modeling and enacting workflows. A formal resource-constrained workflow model is defined and the state transitions rules are established to support workflow analysis. An example is given to illustrate the use of the model.

The dynamics and volunteer-based workforce characteristics of incident command systems raise a challenge to workflow management. Incident command systems must be able to adapt to the ever changing surroundings and tasks during an incident. Furthermore, during an incident, the majority of workers are volunteers that vary in their knowledge of the fundamentals of workflows. To address these challenges, we developed an intuitive, yet formal approach to workflow modeling, enactment and validation. On the other hand, Event-Driven Process Chains (EPC), an informal workflow engine, has been widely used for business process modeling. In this paper, we consider how to convert a workflow model built using EPC engine to a Workflow Intuitive Formal Approach (WIFA) model, so that the well-formedness of the workflow model can be formally verified. This also allows heterogeneous inter-organizational workflow interaction.

This paper presents the main lessons learned over 16 years in offering a graduate degree in software engineering at Monmouth University. It covers the challenges in delivering a program that meets the needs of industry and students in a highly dynamic field. The evolution of the curriculum induced by the continuous advances in the field and industry practice is presented. This evolution is an example of a transition from a "computer science curriculum with an engineering flavor", towards a software engineering curriculum. The special meaning of continuous course content development in software engineering is argued through issues pertaining to dated textbooks, ever-changing programming languages, operating systems, and software tools. The paper also presents our experience in dealing with the diversity of the student body, and its influence on the curriculum and course content. We conclude with the presentation of future directions for this program.

This paper started from the observation that there is a need among the existing software process models to adapt to the size and scope of the product being developed. Therefore, we propose here the Layered Software Development Framework, which recasts classical software development models in light of the architectural levels described in Helm's Scalability Model. It describes the development of software as a set of specific development activities limited to individual architectural levels and the interactions between them, rather than as a set of general development activities distributed across all architectural levels. The framework can be tailored to the specific product being developed, and practices followed by a development organization.

Business rules are statements about the enterprise's way of doing business. They become requirements that govern the operational system of the enterprise and determine constraints for any system developed or procured for an enterprise. This paper addresses an architecture for the specification, enforcement and distribution of business rules, as a way of achieving the interoperability of distributed information systems that support an enterprise. We explore the XML encoding of business rules, which allows their multiple representations, necessary for dealing with the heterogeneity of software and platforms inherent in large companies, or in e-commerce applications. Our ideas are illustrated with examples implemented in Oracle's framework for developing e-business solutions.

The business rules that underlie an enterprise emerge as a new category of system requirements that represent decisions about how to run the business, and which are characterized by their business-orientation and their propensity for change. We introduce a decision making methodology which addresses several aspects of the business rules lifecycle: acquisition, deployment and evolution. We describe a meta-model for representing business rules in terms of an enterprise model, and also a decision support sub-model for reasoning about and deriving the rules. A technique for automatically extracting business rules from the decision structure is described and illustrated using business rules examples inspired by the London Ambulance Service case study. A system based on the metamodel has been implemented, including the extraction algorithm.