syllabus
1. Information regarding the programme
1.1 Higher education institution 	Babes-Bolyai University	
1.2 Faculty	Faculty of Mathematics and Computer Science	
1.3 Department	Department of Computer Science	
1.4 Field of study	Computer Science	
1.5 Study cycle	Master	
1.6 Study programme / Qualification 	Software Engineering	

2. Information regarding the discipline 
2.1 Name of the discipline	Computational Models for Embedded Systems	
2.2 Course coordinator 	PhD Lecturer  Andreea Vescan 	
2.3 Seminar coordinator	PhD Lecturer Andreea Vescan	
2.4. Year of study	2	2.5 Semester	4	2.6. Type of evaluation	E	2.7 Type of discipline	compulsory	

3. Total estimated time (hours/semester of didactic activities) 
3.1 Hours per week 	4	Of which: 3.2 course	2	3.3 seminar/laboratory	2	
3.4 Total hours in the curriculum 	48	Of which: 3.5 course	24	3.6 seminar/laboratory	24	
Time allotment:	hours	
Learning using manual, course support, bibliography, course notes	24	
Additional documentation (in libraries, on electronic platforms, field documentation) 	36	
Preparation for seminars/labs, homework, papers, portfolios and essays	48	
Tutorship	20	
Evaluations	24	
Other activities: ..................	0	
3.7 Total individual study hours 	152	
3.8 Total hours per semester	200	
3.9 Number of ECTS credits	8	

4. Prerequisites (if necessary)
4.1. curriculum	•		
4.2. competencies	•		

5. Conditions (if necessary)
5.1. for the course	•		
5.2.  for the seminar /lab activities	•		

6. Specific competencies acquired 
Professional competencies	•	Understanding and working with basic concepts in software engineering;
•	Capability of analysis and synthesis;
•	Modeling and solving real-life problems;	
Transversal competencies	•	Ability to understand and approach problems of modeling nature from other sciences
•	Good programming skills in high-level languages;
•	Abilities to develop and maintain software systems;
•	Ability to analyze, synthesize and model fenomena and processes from various fields using adequate mathematical, statistical, computational and computer science methods.	

7. Objectives of the discipline (outcome of the acquired competencies)
7.1 General objective of the discipline
	Modeling is an essential technique and serves various purposes, so it is important to understand its fundamental concepts. These concepts relate basically to the way a modeling paradigm allows one to deal with the great properties of system: time, computation, data and communication.

In general, when modeling a system, we want to be able to formulate particular questions on it:
Will a system ever enter a particular state?
Will it always be able to avoid a particular dangerous state?
Will it always eventually reach some desired state?
The classical theory of computation focuses on the function that a program computes. To understand embedded computation, we need to focus on the reactive nature of the interaction of a component with its environement and requirements concerning safety, timeliness, stability, and performance.

•	The main objectives of this cours are to provide an understanding of the fundamentals concepts of software modeling, more precise for embedded computation; to develop skills in modeling and to describe and verify safety and liveness properties of the system being modeled.	
7.2 Specific objective of the discipline
	•	Students will learn the models of computations for embedded systems.
•	Students will know to specify, design and verify an embedded system
•	Students will know how to model a system and specify restrictions on functionalities.	

8. Content
8.1 Course	Teaching methods	Remarks	
1.	Introduction. Model: Why?what? how? Types of systems.	Presentation, Conversation, Didactic demonstration, Problematizations		
2.	Requirements and Safety Requirements. Model checking.	Presentation, Conversation, Didactic demonstration, Problematizations		
3.	Synchronous models. 	Presentation, Conversation, Didactic demonstration, Problematizations		
4.	Finite State Machines 	Presentation, Conversation, Didactic demonstration, Problematizations		
5.	Finite State Machines (cont.)			
6.	Petri Nets 	Presentation, Conversation, Didactic demonstration, Problematizations		
7.	Petri Nets (cont.)			
8. Asynchronous models 	Presentation, Conversation, Didactic demonstration, Problematizations		
9. Dynamical systems	Presentation, Conversation, Didactic demonstration, Problematizations		
10. Timed Models	Presentation, Conversation, Didactic demonstration, Problematizations		
11. Hybrid systems	Presentation, Conversation, Didactic demonstration, Problematizations		
     12. Reserved subject			
Bibliography

[1] C. Baier, J.-P. Katoen, Principles of Model Checking, ISBN 978-0-262-02649-9, 2008
[2] M. Ben-Ari, Principles of the Spin Model Checker, ISBN 978-1-84628-769-5
[3] Taylor Booth (1967) Sequential Machines and Automata Theory, John Wiley and Sons, New York. Library of Congress Catalog Card Number: 67-25924.
[4] D. Harel, "Statecharts: A Visual Formalism for Complex Systems", Sci. Comput. Programming 8 (1987), 231-274
[5] Petri, CA (1966) Communication with automata. DTIC Research Report AD0630125
[6] Hoare, CAR (2004) (1985), Communicating Sequential Processes, Prentice Hall International
Optional references 
Internet resources and conferences

8.2 Seminar / laboratory	Teaching methods	Remarks	
Lab 1 (weeks 1-2) 
       Choose project theme.	Presentation, Conversation, Problematizations, Discovery, Individual study, Exercises		
Lab 2 (theme 1, weeks 3-4) 
       Specifying safety and liveness requirements.
       Model checking.	Presentation, Conversation, Problematizations, Discovery, Individual study, Exercises		
Lab 3 (theme 2, weeks 5-6) 
       Using Finite State Machines to model an embedded system.
	Presentation, Conversation, Problematizations, Discovery, Individual study, Exercises		
Lab 4 (theme 3, weeks 7-8) 
       Using PetriNets to model an embedded system.
	Presentation, Conversation, Problematizations, Discovery, Individual study, Exercises		
Lab 5 (theme 2,3, weeks 9-10) 
      Using Finite State Machines and PetriNets to model an embedded system.
	Presentation, Conversation, Problematizations, Discovery, Individual study, Exercises		
Lab 6 (weeks 11-12) 
      Project presentation and documentation delivery.
	Presentation		
Bibliography

	

9. Corroborating the content of the discipline with the expectations of the epistemic community, professional associations and representative employers within the field of the program

•	 Students will know how to model, specify, design and test embedded systems.
•	Students will learn various computational models for embedded systems.	

10. Evaluation
Type of activity	10.1 Evaluation criteria	10.2 Evaluation methods	10.3 Share in the grade (%)	
10.4 Course	GF=GradeFinal = graded paper at the final exam	Written examination
Passing the final exam is conditioned by the grade GF being at least 5.	60	
	GP=GradeProjects = documentations and projects	Specification, design and analysis, presentation of the project	40	
10.6 Minimum performance standards	
•	Students will know various computational models for embedded systems.
•	At least grade 5 (from a scale of 1 to 10) at written exam and project work.	

Date				Signature of course coordinator 	Signature of seminar coordinator
09.24.2012			Lect. PhD. Andreea Vescan               Lect.PhD.  Andreea Vescan	

Date of approval  					  Signature of the head of department	
...........................................				    Prof. PhD. Bazil Parv