Towards Sophisticated Air Traffic Control System Using Formal Methods

We propose a general formal modeling and verification of the air traffic control system (ATC). This study is based on the International Civil Aviation Organization (ICAO), Federal Aviation Administration (FAA), and National Aeronautics and Space Administration (NASA) standards and recommendations. It provides a sophisticated assistance system that helps in visualizing aircrafts and presents automatic bugs detection. In such a critical safety system, the use of robust formal methods that assure bugs absence is highly required. Therefore, this work suggests a formalism of discrete transition systems based on abstraction and refinement along proofs. These ensure the consistency of the system by means of invariants preservation and deadlock freedom. Hence, all invariants hold permanently providing a handy solution for bugs absence verification. It follows that the said deadlock freedom ensures a continuous running of a given system. This specification and modeling technique enable the system to be corrected by construction. Document type: Articl

Formal Specification of QoS Negotiation in ODP System

The future of Open Distributed Processing systems (ODP) will see an increasing of components number, these components are sharing resources. In general, these resources are offering some kind of services. Due to the huge number of components, it is very difficult to offer the optimum Quality of service (QoS). This encourages us to develop a model for QoS negotiation process to optimize the QoS in an ODP system. In such system, there is a High risk of software or hardware failure. To ensure good performance of a system based on our model, we develop it using a formal method. In our case, we will use Event-B to get in the end of our development a system correct by construction

Towards Sophisticated Air Traffic Control System Using Formal Methods

We propose a general formal modeling and verification of the air traffic control system (ATC). This study is based on the International Civil Aviation Organization (ICAO), Federal Aviation Administration (FAA), and National Aeronautics and Space Administration (NASA) standards and recommendations. It provides a sophisticated assistance system that helps in visualizing aircrafts and presents automatic bugs detection. In such a critical safety system, the use of robust formal methods that assure bugs absence is highly required. Therefore, this work suggests a formalism of discrete transition systems based on abstraction and refinement along proofs. These ensure the consistency of the system by means of invariants preservation and deadlock freedom. Hence, all invariants hold permanently providing a handy solution for bugs absence verification. It follows that the said deadlock freedom ensures a continuous running of a given system. This specification and modeling technique enable the system to be corrected by construction

Impact of Aircraft Performance and Time of the Day on Flight Arrival Delays Prediction in the United States: a Machine Learning Classification

The excessive growth of air traffic, with the limited airspace and airports capacity, results in a flight demand-capacity imbalance leading to air traffic delays. This paper explores the factors associated with delay in both microscopic and macroscopic ways. The aim is to develop a model which analyzes and predicts the occurrence of flight arrival delays using US domestic flight data for the year 2018. It will provide passengers, airlines and airport managers with reliable flight arrival schedules, and consequently reduce economic losses and enhance passengers trust. Beside database features, the proposed model is to the best of our knowledge the first attempt to predict flight arrival delays using three new features which are contributive factors to delays: Departure Time and Arrival Time of the day in which the flight was performed (Early morning, late morning, noon, afternoon, evening or night) and model of aircraft. Four Machine Learning classifiers namely Random Forest, Decision Trees, K-Nearest Neighbors and Naive Bayes were used. In order to find the best parameters of each algorithm, we implemented Grid Search technique. The performance of each classifier was compared in terms of hyperparameters tuning, classification metrics and features description. The experimental results showed that the proposed system was able to predict flight arrival delays with the best Random Forest accuracy of 0.9356 and a higher number of correctly classified flights. To prove the importance of our findings, we compared our model to that of existing literature studies

The Semantic of Business Vocabulary and Business Rules: An Automatic Generation From Textual Statements

In the early phases of the software development process, specifications are mostly written in a natural language rather than formal models, which is not supported by the Model Driven Architecture (MDA). For this reason, the Semantic of Business Vocabulary and Rules (SBVR) is proposed by the Object Management Group to represent the textual specifications in a language comprehensible by both of humans and machines, to facilitate its integration in the MDA lifecycle. However, businesspeople are usually not familiar with SBVR standard. In this paper we present an approach to automatically transform textual business rules to an SBVR model, to facilitate its integration in nowadays information technology infrastructures. Our approach is distinguished from existing works in that it uses an in-depth Natural Language Processing to extract a more comprehensible SBVR model that includes the semantic formulation of each business rule statement, coupled with a Terminological Dictionary of extracted concepts, to which we have added further specifications such as definitions and synonyms. The evaluation of our approach shows that for three sets of business rules statements taken from different domains, we could generate the correct meaning with an average of F1-score exceeding 87%