The high level language for system specification: A model-driven approach to systems engineering

2016 ◽  
Vol 07 (01) ◽  
pp. 1641003 ◽  
Author(s):  
Hamzat Olanrewaju Aliyu ◽  
Oumar Maïga ◽  
Mamadou Kaba Traoré
Keyword(s):  
Systems Engineering ◽  
Discrete Event ◽  
Discrete Event System ◽  
High Level Language ◽  
System Specification ◽  
Model Driven ◽  
Event System ◽  
Visual Formalisms ◽  
Devs Formalism ◽  
High Level

We present HiLLS (High Level Language for System Specification), a graphical formalism that allows to specify Discrete Event System (DES) models for analysis using methodologies like simulation, formal methods and enactment. HiLLS’ syntax is built from the integration of concepts from System Theory and Software Engineering aided by simple concrete notations to describe the structural and behavioral aspects of DESs. This paper provides the syntax of HiLLS and its simulation semantics which is based on the Discrete Event System Specification (DEVS) formalism. From DEVS-based Modeling and Simulation (M&S) perspective, HiLLS is a platform-independent visual language with generic expressions that can serve as a front-end for most existing DEVS-based simulation environments with the aid of Model-Driven Engineering (MDE) techniques. It also suggests ways to fill some gaps in existing DEVS-based visual formalisms that inhibit complete specification of the behavior of complex DESs. We provide a case study to illustrate the core features of the language.

scholarly journals A DSDEVS-Based Model for Verifying Structural Constraints in Dynamic Business Processes

2020 ◽  
Vol 44 (2) ◽  
pp. 257-273
Author(s):  
Sofiane Boukelkoul ◽  
Ramdane Maamri
Keyword(s):  
Business Processes ◽  
Discrete Event ◽  
Dynamic Structure ◽  
Discrete Event System ◽  
Structural Constraints ◽  
System Specification ◽  
Discrete Event System Specification ◽  
Event System ◽  
Proposed Model ◽  
Structure Properties

This paper presents a DSDEVS-based model “Dynamic Structure Discrete Event System specification” for modeling and simulating business processes with dynamic structure regarding to different contexts. Consequently, this model, formally, improves the reuse of configurable business processes. Thus, the proposed model allows the analysts to personalize their configurable business processes in a sound manner by verifying a set of structure properties, such as, the lack of synchronization and the deadlock by means of simulation. The implementation was done in DEVS-Suite simulator, which is based on DEVSJAVA models.

scholarly journals Modeling and simulation of oncology clinic operations in discrete event system specification

SIMULATION ◽  
2017 ◽  
Vol 94 (2) ◽  
pp. 105-121 ◽  
Author(s):  
Michelle M Alvarado ◽  
Tanisha G Cotton ◽  
Lewis Ntaimo ◽  
Eduardo Pérez ◽  
William R Carpentier
Keyword(s):  
Operations Management ◽  
Discrete Event ◽  
Treatment Method ◽  
Discrete Event System ◽  
Arrival Process ◽  
System Specification ◽  
Operation Performance ◽  
Discrete Event System Specification ◽  
Event System ◽  
Chemotherapy Patients

Oncology clinics are often burdened with scheduling large volumes of cancer patients for chemotherapy under limited resources, such as nurses and chemotherapy chairs. Chemotherapy is a cancer treatment method that is administered orally or intravenously at an outpatient oncology clinic. Chemotherapy patients require a treatment regimen, which is a series of appointments over several weeks or months prescribed by the oncologist. The timing of these appointments is critical to the effectiveness of the chemotherapy treatment on cancer. This motivates the need for new methods for making efficient appointment schedules and for assessing clinic operation performance from both patient and management perspectives. This work uses a classic modeling approach based on systems theory to develop a discrete event system specification (DEVS) simulation model for oncology clinic operations called DEVS-CHEMO. DEVS-CHEMO is configurable to any oncology clinic and provides several capabilities for oncology clinic managers. For example, it can simulate scheduling of chemotherapy patients, clinic resources, and the arrival process of the patients to the clinic on the day of their appointment. This model simulates oncology clinic operations as patients receive chemotherapy treatments and thus allows for assessing scheduling algorithms using both patient and management perspectives. DEVS-CHEMO has been tested and validated using historical data from a real outpatient oncology clinic and the simulation results reported in this paper provide several insights regarding oncology clinic operations management.

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