DIP203 Data Structures

Code DIP203
Name Data Structures
Status Compulsory/Courses of Limited Choice
Level and type Undergraduate Studies, Academic
Field of study Computer Science
Faculty
Academic staff Aleksejs Jurenoks, Natālija Prokofjeva, Igors Ščukins, Lāsma Lēruma, Padmaraj Nidagundi, Valdis Saulespurēns, Inese Simkeviča
Credit points 3.0 (4.5 ECTS)
Parts 1
Annotation The study course provides the following information: data structure (DS) concept and classification, logical and physical data structures, DS creation methods and representation techniques. The study course covers linear data structures (arrays, lists, tables, stacks, rows, dequeues) and nonlinear data structures (trees, graphs), as well as describes several types of lists and trees, their specification, representation, creation and use..
Contents
Content Full- and part-time intramural studies Part time extramural studies
Contact hours Independent work Contact hours Independent work
The aim and tasks of the study course. Data structure definition. Data type concept. Data structure classification. 5 5 0 0
Data type classification. Pointers, references. Arrays, their types, specification, representation and creation. Records, variant records. Strings. Tables. Files. 5 5 0 0
Special arrays and their use. Diagonal matrix, triangle matrix, symmetric matrix, sparse matrix. 5 5 0 0
Algorithm concept and properties. Algorithm efficiency criteria: time, complexity. Sorting concept. Classification of sorting algorithms. String search algorithms. 5 5 0 0
The concept and types of linear data structure. Lists, their characteristics and processing operations. List displayed in vector form. 5 5 0 0
Linked list. Doubly linked list. Circular list. Multi-linked list. Ordered list. 5 5 0 0
Stack. Stack specification, representation and creation. 5 5 0 0
Queue. Creating a circular queue. The dequeue concept. 5 5 0 0
The concept and characteristics of a tree data structure. Tree classification. Types of classification of binary trees, representation and principles of creation. Binary tree traversal. 5 5 0 0
Binary search tree. AVL tree. Balance factor of AVL tree. Types of AVL rotations. 5 5 0 0
Heap. Heap conditions. The concept and use of B-tree. 5 5 0 0
Graph concept. Graph traversal and its implementation methods. Graph representation techniques. 5 5 0 0
Total: 60 60 0 0
Goals and objectives
of the course in terms
of competences and skills 		The aim of the study course is to provide knowledge and skills about data type and data structure (DS) specifications, data structure creation methods and representation techniques, and efficient algorithms for working with frequently used data structures. Tasks of the study course: - to acquaint students with the concept, meaning and classification principles of data structures, as well as the development and description of DS model, design and implementation; - to teach students to choose the most efficient DS and their processing algorithms and to use them in practice in the software development process.
Learning outcomes
and assessment 		Is able to create data structures and implement their processing operations. - Independently performed and positively evaluated laboratory works.
Is able to create various types of data structures, describe and implement the functions for their processing. - Independently performed and positively evaluated homework.
Knows general questions about data structures, their representation models, specifications, and processing operations. - Completed and positively evaluated tests.
Knows the concept, meaning and classification principles of data structures, as well as types and technologies for representing data structures. - Passed the exam with a positive grade.
Evaluation criteria of study results
Laboratory works - 30%
Homework - 20%
Tests - 10%
Exam - 40%
 
Course prerequisites Algorithmization and Programming of Solutions.
Course planning
Part CP ECTS Hours Tests
Lectures Practical Lab. Test Exam Work
1 3.0 4.5 2.0 0.0 1.0 *
[Extended course information PDF]