Algorithmics and advanced data structures Field of study: Computer Science
Programme code: W4-S2INA19.2020

Module name: Algorithmics and advanced data structures
Module code: W4-INA-S2-20-1-AiZSD
Programme code: W4-S2INA19.2020
Semester: summer semester 2020/2021
Language of instruction: English
Form of verification: exam
ECTS credits: 4
Description:
Algorithmics is the science of algorithms. It includes algorithm design, i.e. the art of building a schema that effectively solves a specific problem or class of problems and algorithm analysis. This module introduces the participant to advanced algorithm design methods and issues of algorithms and data structures analysis.
Prerequisites:
(no information given)
Key reading:
1. T.H. Cormen, C.E. Leiserson, R.L.Rivest: Introduction to algorithms. 2. R.L.Graham, D.E.Knuth, O.Patashnik: Concrete mathematics.
Learning outcome of the module Codes of the learning outcomes of the programme to which the learning outcome of the module is related [level of competence: scale 1-5]
The student knows advanced methods of determining the computational complexity of algorithms; knows and understands classes of algorithms complexity. [M_001]
 K_W01 [2/5] K_W04 [2/5]
The student knows advanced paradigms of algorithms constructing, e.g. exhaustive search or greedy strategies; knows and understands basics of operation and advantages and disadvantages of these algorithms. [M_002]
 K_W04 [4/5]
The student knows graph algorithms [M_003]
 K_W01 [1/5] K_W04 [3/5]
The student understands the concept of approximation algorithm and knows examples of such algorithms using different approaches, e.g. combinatorial or based on the theory of linear programming [M_004]
 K_W01 [1/5] K_W04 [3/5]
The student knows examples of Monte-Carlo and Las-Vegas randomised algorithms. [M_005]
 K_W01 [1/5] K_W04 [3/5]
The student can designate computational complexity of recurrent algorithms and record their complexity, e.g. as a recurrent equation, and solve such an equation. [M_006]
 K_W01 [2/5] K_W04 [2/5]
The student can choose and implement an appropriate, basic or advanced algorithm construction paradigm to solve a problem and justify such a choice. [M_007]
 K_U08 [1/5] K_U09 [3/5]
The student can implement an appropriate algorithm to solve a problem and select a suitable data structure. [M_008]
 K_U09 [3/5]
The student is aware of the significant impact of the algorithms' characteristics such as complexity or correctness, constituting the essential components of larger systems, such as modules, functions or procedures, on the final efficiency, correctness and safety of these systems. [M_009]
 K_U09 [2/5] K_K01 [1/5]
Type Description Codes of the learning outcomes of the module to which assessment is related
Written exam [W_001]
The exam is designed to verify the knowledge based on the content presented during lectures
 M_001 M_002 M_003 M_004 M_005 M_006 M_009
Reports [W_002]
The students complete the assigned tasks and elaborate them in the form of reports.
 M_006 M_007 M_008 M_009
Form of teaching Student's own work Assessment of the learning outcomes
Type Description (including teaching methods) Number of hours Description Number of hours
lecture [Z_001]
The lectures have an audiovisual form with the additional use of some written educational aids.
 30
The students are required to self-study for the exam.
 30 Written exam [W_001]
laboratory classes [Z_002]
The students prepare for solving tasks individually by studying the proceeding method and the sequence of operations.
 30
Classes prepare the students for completing the assigned tasks individually during the laboratory class. They are also required to elaborate on reports.
 30 Reports [W_002]
Attachments
Module description (PDF)
Information concerning module syllabuses might be changed during studies.
Syllabuses (USOSweb)
Semester Module Language of instruction
(no information given)