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Postgraduate Studies
Courses Catalogue

Course details

Code

CS-546

Name

Types and Programming Languages

Program

Postgraduate

Areas

Software engineering and programming languages

Algorithms and systems analysis

Computer systems, parallel and high performance computing

(Algorithms and Systems Analysis)

(Information Systems and Human-Computer Interaction)

(Parallel and Distributed Systems)

Description

CS546 focuses on type systems and their application in the design and implementation of programming languages. The course also explores type system applications in tools that automatically analyze programs and assist programmers, such as compiler optimizers, debuggers, verifiers, analyzers, model checkers, etc.

LEARNING OUTCOMES
1. Knowledge: Having attended and succeeded in the course, the student will understand semantics, terminology and concepts around programming languages, enough to be able to follow the current scientific literature on the topic.
2. Understanding: Having attended and succeeded in the course, the student will be able to understand categories of problems that are solvable using static analysis, understand differences in the design and implementation of programming languages, and describe static analysis techniques used in state-of-the-art production tools.
3. Application: Having attended and succeeded in the course, the student is able to read and understand the recent scientific literature in the area of programming languages, type systems, static analysis and compilers, and to also apply these in existing tools, languages, and compilers.
4. Analysis: Having attended and succeeded in the course, the student is able to understand complex code analysis algorithms as combinations and applications of simple theoretical methods, and analyze the differences and interactions that occur.
5. Synthesis: Having attended and succeeded in the course, the student is able to search relevant literature on problems in code analysis, understand it, and apply it in practical tools.
6. Evaluation: Having attended and succeeded in the course, the student is able to understand qualitatively and measure quantitatively the performance of various solutions to static code analysis problems, and compare them.

STUDENT PERFORMANCE EVALUATION
Class attendance/participation
Exercises/projects
Oral/written exams

ECTS

Prerequisites

CS-255, CS-280

Course website

https://www.csd.uoc.gr/~hy546/

Courses catalog

A+

A-

Offered Postgraduate Cousres
Code	Course Name	ECTS(ΔΜ)	Prerequisites	Suggested	Areas
CS-500	Introduction to Research	2	--
CS-508	Technical Writing in English	4	--
CS-523	Digital Systems CAD Laboratory	6	CS-220, CS-225		A, A1
CS-527	Parallel Computer Architecture	6	CS-345, CS-425		A, A1, A2, Γ
CS-529	Multicore Architecture Programming	6	CS-345, HY425		A, A2, B1, B2, Γ
CS-531	Topics in Information theory	6	N/A		B, B2, B4
CS-533	Introduction to Research on Computer Networks	6	CS-335		A3, A4, B
CS-534	Packet Switch Architecture	6	CS-225, CS-335		A, A1, A4, B
CS-539	Advanced Topics on Wireless Networks and Mobile Systems	6	CS-335, CS-345		A4, B, Γ
CS-540	Advanced Topics in Programming Languages Development	6	CS-340		B1, B3, Z, Δ
CS-541	Wireless Sensor Networks	6	CS-335, CS-215		B, C1, Θ
CS-543	Software Systems and Technologies for Big Data Applications	6	CS-360, CS-252,or instructor permission.		B2, B4, Γ, Δ
CS-546	Types and Programming Languages	6	CS-255, CS-280		A2, B1, B3, Z, Γ, Δ
CS-548	Cloud-native Software Architectures	6	CS-335, CS-345		A2, Γ
CS-553	Interactive Computer Graphics	6	CS-358		C3, E, Δ, Θ
CS-558	Internet Technologies and Systems	6	CS-345		A3, A4, B, Γ, Δ
CS-559	Infrastructure Technologies for Large-Scale Service-Oriented Systems	6	CS-345, CS-360		A2, A3, B2, H, Γ, Δ
CS-561	Web Data Management	6	CS-460		B2, C3, Δ
CS-562	Advanced Database Topics	6	CS-360		B2, Δ
CS-563	Advanced Topics in Information Retrieval Systems	6	CS-463		B2, B4, Δ
CS-565	Process Management Systems	6	CS-360	CS-460	A3, A4, B1, H, Δ, Θ
CS-567	Knowledge Representation and Reasoning	6	CS-380, CS-387		B2, B4, Δ, Θ
CS-569	Human – Computer Confluence	6	CS-364	CS-359, CS-469	C3, H, Δ, Θ
CS-570	Statistical Signal Processing	6	CS-370, CS-217		B, B4, C1, C2, E, Θ
CS-573	Optimization Methods	6	CS-110, CS-119		B4, C2, E, Z
CS-575	Robotic Navigation Laboratory	6	CS-475		C2, E
CS-577	Machine Learning	6	CS-150, CS-217, CS-380		B4, C1, C2, C4, E, H, Z, Δ
CS-578	Voice Processing	6	CS-370		B, C1, Θ
CS-580	Topics in Algorithm Design	6	CS-240, CS-280, CS-380		B1, C4, Z
CS-583	Graph Algorithms	6	CS-240, CS-380		B1, C4, Z
CS-586	Distributed Computing	6	CS-380		A3, B1, Z, Γ
CS-587	Neural Networks and Learning of Hierarchical Representation	6	CS-217, CS-119 or Μ-105		B4, C1, C2, C4, Z
CS-588	Brain Network Analysis and Modeling	6	CS-217, CS-215, CS-240		B, B4, C4, H
CS-590.31	IoT for Smart Cities	6	CS-335, CS-150		A4, B, B2, Δ
CS-590.45	Modern Topics in Scalable Storage Systems	6	CS-345, CS-360		A3, B2, Γ
CS-590.72	Introduction to Bioinformatics for Computer Scientists	3	Basic knowledge in the areas of theoretical computer science (algorithms, data structures) and technical computer science (sequential optimization in C or C++, computer architectures, parallel programming, vector processors) is required.		C4, H
CS-590.73	Seminar in Reproducibility in Bioinformatics	3	CS-590.72		C4, H
CS-647	Modern Storage Systems	6	CS-345		A2, B2, Γ
CS-672	Advanced Topics in Computational Vision	6	CS-472		B4, C2, C3, E
CS-673	Introduction to Deep Generative Modelling	6	CS-217, CS-119		B4, C2, E, Z, Θ
CS-690.1-4	Teaching Assistantship	3	--
CS-693	Introduction to Game Theory	6			B, B1, B4, Z
CS-695	Supervised Personal Study	3	--
CS-697	Bibliographic Search	15
CS-698	Assessment of Research Direction and Development of a Research Plan	15
CS-699	Research for M.Sc. Thesis	30
CS-700	Seminar Courses	3	--