Automata-network methods for analysis of discrete systems

Course: Software engineering

Structural unit: Faculty of Computer Science and Cybernetics

Title
Automata-network methods for analysis of discrete systems
Code
ВК.1.07.
Module type
Вибіркова дисципліна для ОП
Educational cycle
Second
Year of study when the component is delivered
2023/2024
Semester/trimester when the component is delivered
4 Semester
Number of ECTS credits allocated
3
Learning outcomes
LO01. Know and systematically apply methods of analysis and modeling of the application area, identification of information needs and collection of raw data for software design. LO03. Know and apply the basic concepts and methodologies of modeling information processes. LO08. To conduct an analytical study of the parameters of the functioning of software systems for their validation and verification, as well as to conduct an analysis of selected methods, means of automated design and implementation of software. LO13. Acquire new scientific and professional knowledge, improve skills, forecast the development of software systems and information technologies.
Form of study
Distance form
Prerequisites and co-requisites
Successful completion of courses: 1. Discrete mathematics. 2. Formal grammars and languages, basics of programming. 3. Mathematical logic and theory of algorithms. Know: a) Basics of the theory of automata, general and linear algebra. b) Properties of relations and operations on relations. c) Object-oriented programming in the Java language. Be able to: 1) Perform an analysis of an emerging problem. 2. Build mathematical (logical) models of relevant subject areas 3. Create specifications and perform verification of models resulting from problem analysis. 4. To check the fulfillment of specifications on the models. 5. Program in procedural, functional, logical and object-oriented styles.
Course content
The main tasks of the discipline are mastering the basic algebraic methods of software analysis, in accordance with the qualification of an information technology specialist. In particular, to develop: - Ability to abstract thinking, analysis and synthesis; Ability to effectively manage financial, human, technical and other project resources. The ability to develop and coordinate processes, phases and iterations of the life cycle of software systems based on the application of relevant software development models, methods and technologies conducting theoretical and applied research at the appropriate level. - Ability to analyze subject areas, form, analyze and model software requirements. - Ability to design software, including modeling its architecture, behavior and processes of functioning of individual systems and modules. - Ability to plan and conduct scientific research, prepare the results of scientific works on software engineering for publication).
Recommended or required reading and other learning resources/tools
1.Huynh D. T. The Complexity of the Equivalence Problem for Commutative Semigroups and Symmetric Vector Addition Systems. Proceedings of the 17-th Annual ACM Symposium on Theory of Computing. – 1985. –P. 405 – 412. 2. Jancar P. Decidability Questions for Bisimularity of Petri Nets and Some Related Problems. STACS'94. –LNCS. – 1994. – № 775. – P. 581–594. 3. Jensen K., Kristensen L.M. Colored Petri Nets: Мodelling and Validation of Concurrent Systems. Springer-Verlag: Berlin Heidelberg. – 2009. – 384 p. 4. Jones N. D., Landweber L. H., Lien Y. E. Complexity of Some Problems in Petri Nets Theoretical Comp. Sci. – 1974. – № 4. – P. 277 – 299. 5. Keller R. M. A Fundamental Theorem of Asynchronous Parallel Computation Parallel Processing. – LNCS. –1975. – № 24. – P. 102–112. 6. Kosaraju S. R. A Decidability of Reachability in Vector Addition Systems. 14-th Annual ACM Symposium on Theory of Computing, San Francisco. – 1982. P. 267–281.
Planned learning activities and teaching methods
Lectures, laboratory classes, independent work, tests, homework, defense of laboratory work, exam.
Assessment methods and criteria
Intermediate assessment: -The maximal number of available points is 60: 1. Test work no. 1: LO 1.1, LO 1.2 – 10/6 points. 2. Test work no. 2: LO 1.2, LO 1.3 – 10/6 points. 3. Laboratory work no. 1: LO 1.2, LO 1.3, LO 2.1, LO 3.1– 8/4 points. 4. Laboratory work no. 2: LO 1.2, LO 1.3, LO 2.1, LO 3.1– 8/4 points. Final assessment (in the form of exam): - maximal number of available points is 40; - results of study to be assessed are LO 1.1, LO 1.2, LO 1.3, LO 2.1; - form of exam: writing.
Language of instruction
Ukrainian

Lecturers

This discipline is taught by the following teachers

Serhii L. Kryvyi
Department of Intelligent Software Systems
Faculty of Computer Science and Cybernetics

Departments

The following departments are involved in teaching the above discipline

Department of Intelligent Software Systems
Faculty of Computer Science and Cybernetics