FORMAL ANALYSIS OF DDML
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FORMAL ANALYSIS OF DDML
Chapter one
Chapter 1: Introduction.
The framework presented in this paper is designed to officially examine and evaluate DDML models. DDML is a modelling language intended for use with the DEVS formalism of modelling and simulation (M & S).
Modelling and simulation is a large subject of study that applies to computer science by automating and monitoring simulations of real-world situations in science and engineering.
Computer simulations are used in a wide range of industries, including the study of real-world systems to acquire information and make strategic decisions. To get into the meat of this study, it is necessary to first provide an overview of the M & S field, including its significance, applications, and principles.
1.1 Modelling and Simulation
Modelling and simulation is a paradigm that allows you to represent problems and reason about them in order to propose a solution, approach, or absorb relevant facts to solve them.
Concepts Modelling and simulation consist of five basic principles that assist define the process and its components. The following are the definitions of such concepts:
An object is a real-world entity with specified structure and behaviour.
A system is a well-defined object in the real world with particular conditions that define its structure and behaviour.
A model is an abstract representation of an item, including properties, structure, and behaviour. This representation can be logical, mathematical, or physical.
Experimental Frame: Specifies the model’s criteria for use. It summarises the experiment’s objectives as well as the model’s elements that will be tracked.
Simulation involves executing a model to get insight into changes in system behaviour, structure, and properties. It aids in the observation and inference of the system’s dynamic behaviour by demonstrating its implementation over time.
Modelling and simulation are the processes of creating a model of a real-world system and working on the model in order to study and absorb new information. In computer science, modelling and simulation are used to explore the attributes, structure, and behaviour of systems, as well as to collect and infer new information about them.
Modelling and simulation have become widely utilised in many areas of science, including business, to analyse events and activities using models that are similar to real-world settings.
This is because virtual experimentation with models is less expensive, more feasible, and even safer to research for vital systems such as aviation, health care, medication manufacture, electrical/electronic systems, oil production, supply chain management and logistics, military intelligence, and defence systems. In computer science, modelling and simulation can be used to provide formal analysis of DDML.
On page 5, Soremekun Olamide Ezekiel outlines the many stages of development, including requirements engineering, design, implementation, project management, and installation. The figure below depicts how modelling and simulation are used in the field of computer science.
Figure 1 depicts the use of modelling and simulation in computer science. Benefits Modelling and simulation can provide numerous benefits to both the user and the environment at large.
Modelling and simulation assist users in better understanding the system, optimising its performance, and ensuring the reliability and safety of these systems. The user can utilise modelling and simulation to check various limitations and circumstances that cannot be checked in the real world.
Simulation of these models can be used to perform life-critical scenarios in the healthcare system, drug use, and even microscopic level of detail material evaluation.
Furthermore, modelling and simulation have been used to assist validate systems by executing models of current systems and checking for flaws or bugs in order to avoid devastating occurrences in real life.
Models of the European road and rail transport systems, as well as the United States’ air traffic control system, have been evaluated and validated using modelling and simulation [1, 2].
Formal Analysis of DDML
Soremekun Olamide Ezekiel. Page 6
Furthermore, modelling and simulation are necessary for effective system design and evaluation, as they aid in the development of a dependable and well-designed product or system.
This is accomplished by examining the proposed system’s operation over time using its model and enhancing its performance by adjusting constraints and conditions that affect the system in order to compute the appropriate set of constraint variables for optimal performance.
This allows the impacts of changes in conditions on the system to be determined without changing the real system or having to create the system to test for such changes. The diagram in Figure 2 helps to summarise the multiple benefits of modelling and simulation in modern culture.
Finally, modelling and simulation allow you to solve real-world problems or even unforeseen or future defects in systems. Simulation can condense the time effect of long processes, allowing us to visualise the possible future outcomes of processes and defects that may arise during future operations.
Identifying such flaws can help businesses and governments make critical decisions about the system in order to avoid flaws or potential disasters.
Aside from that, a real-world problem, such as the spread of a specific illness, can be modelled and stopped by monitoring the pace or direction of spread during the simulation and implementing the necessary decisive methods to prevent it.
Figure 2 shows the multiple advantages of modelling and simulation.
Formal Analysis of DDML
Soremekun Olamide Ezekiel. Page 7
Importance The importance of modelling and simulation is highlighted by its strengths. It is significant because it reduces costs associated with system testing.
Modelling and simulations are less expensive than building the system and running test cases on it, which would require building numerous replica systems that might be destroyed after each test case.
However, with a good system model, test cases can be conducted without having to spend a lot of money repeatedly constructing the same system. Aside from that, Modelling and Simulation (M&S) offers a level of detail that is adaptable to system size.
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