Synthesis of positive logic programs for checking a class of definitions with infinite quantification

We describe a method based on unfold/fold transformations that synthesizes positive logicprograms P(r)with the purpose of checking mechanically definitions of the form D(r) =∀X(r(X) ⇔QYR(X, Y))where ris the relation defined by the formula QYR(X, Y), Xis a set of variables to be instantiated at runtime by ground terms, QYis a set of quantifiedvariables on infinite domains (Qis the quantifier) and R(X, Y)a quantifier-free formulain the language of a first-order logic theory. This work constitutes a first step towards theconstruction of a new type of assertion checkers with the ability of handling restrictedforms of infinite quantification

Proceedings of the MoDELS'05 Workshop on Tool Support for OCL and Related Formalisms -- Needs and Trends

This Technical Report comprises the final versions of the technical papers presented at the workshop 'Tool Support for OCL and Related Formalisms -- Needs and Trends' held in Montego Bay (Jamaica), October 4, 2005. The workshop was co-located with the ACM/IEEE 8th International Conference on Model Driven Engineering Languages and Systems (MoDELS)

An Early Warning System For Risk Management

isk management in healthcare has solved a wide range of healthcare-related issues in Saudi Arabia. However, the limitation of risk management teams working under special conditions (needing to solve critical health-related issues) has highlighted the urgent need for an early risk warning system (ERWS) in healthcare. The influences of changing weather conditions demand that diabetic patients and doctors in Saudi Arabia have a continuous check on health conditions. The number of diabetic patients is increasing rapidly in Saudi Arabia. Hence, risk management teams in healthcare must be supported with a system that alerts to changes before the changes become a significant risk/problem. Our proposed approach does the following: 1) predicts changes in BP and blood sugar level within hospital environment at runtime. 2) Continually checks patient health status with respect to health condition at runtime. 3) Alerts to the changes as detected (e.g. risk or unknown parameter), and also provides feedback for patient and doctor. We present a computational model that defines the interaction and communication of the system components and describes the prediction and checking process in our proposed approach. We designed the architecture for our proposed approach with respect to the computational model. The thesis proposes an early risk warning system approach, which predicts and checks patient health conditions with respect to the ideal conditions according to medical standards. The health status of a patient will be communicated to doctors and patients on an emergency note if the predicted values are outside normal conditions. In this way, the risk can be mitigated before the occurrence of damage to patient health at runtime. To implement the proposed approach, neural networks is used for developing the prediction component using Java programming. The results of this research successfully predicted the health condition of a patient by checking outputs against medical standards. The risks defined in this research include hyperglycaemia, hypoglycaemia, hypertension and hypotension. Appropriate results were obtained for almost every patient when checked with four input parameters for 200 patients. Consistent results were produced by the risk prediction component and the alerts were generated after every five (5) seconds to communicate to the patients and doctors at runtime. Health status of all 200 patients can also be seen to check the changes in health conditions in the hospital environment. Finally, a case study with different scenarios based on changes in patient health status with respect to ideal conditions revealed evaluated the approach.Saudi Cultural Burea

Evaluation of assertion support for the Java programming language

There is some evidence, that assertion techniques, i.e., preconditions, postconditions and invariants have a positive effect on the overall software quality. Unfortunately only a limited number of commercially relevant programming languages support assertion techniques (e.g., Eiffel). Even modern programming languages like Java have very limited built-in support for assertions. Nevertheless a number of systems exist for the the Java programming language, that support assertion techniques in different ways (language extensions, preprocessors, metaprogramming approaches). In order to make these different approaches comparable we developed a set of criteria and used these criteria to evaluate these systems.