Laboratory of Software Engineering and Information Systems 1

Course Description

The laboratory assignments grouped in 4 areas, designed to complement the material covered in lectures. Advanced Algorithms and Data Structures: information storage and retrieval using advanced list and tree structures and hashing techniques, graph algorithms and optimisation routines. Advanced databases: multimedia contents, XML for data interchange. Distributed systems: point-to-point and group communication, synchronous and asynchronous distributed algorithms, message passing, distributed objects, distributed data; client-server applications, peer-to-peer systems, publish-subscribe systems. Object-oriented design: software construction using basic building blocks to illustrate the objective paradigm.

General Competencies

In-depth understanding of the principles and theoretical background of data storage and retrieval building blocks: algorithms and data structures encapsulated into reusable objects, usage of these objects to achieve given functionality. Acquaintance with advanced database features and ability to deal with heterogeneous and spatially distributed systems.

Learning Outcomes

  1. select the best algorithm for a known problem
  2. apply the acquired knowledge about database system architecture
  3. apply the acquired knowledge about distributed database systems characteristics
  4. design object-oriented, object-relational, temporal, spatial and NoSQL databases
  5. apply the principles of data warehouse development
  6. apply object-oriented software design

Forms of Teaching

Lectures

Theoretical fundations and paradigms exposed during the lectures are illustrated with practical examples.

Laboratory Work

Applying the knowledge acquired on lectures on previously unknown practical examples.

Consultations

By arrangement.

Programming Exercises

By arrangement.

E-learning

Self-activity.

Other Forms of Group and Self Study

By arrangement.

Grading Method

Continuous Assessment Exam
Type Threshold Percent of Grade Threshold Percent of Grade
Seminar/Project 0 % 100 % 0 % 0 %

Week by Week Schedule

  1. Advanced Algorithms and Data Structures: information storage and retrieval using advanced list and tree structures and hashing techniques.
  2. Advanced Algorithms and Data Structures: information storage and retrieval using advanced list and tree structures and hashing techniques.
  3. Advanced Algorithms and Data Structures: information storage and retrieval using advanced list and tree structures and hashing techniques.
  4. Advanced databases: object, object-relational, temporal, spatial and NoSQL databases.
  5. Advanced databases: object, object-relational, temporal, spatial and NoSQL databases.
  6. Advanced databases: object, object-relational, temporal, spatial and NoSQL databases.
  7. Advanced databases: object, object-relational, temporal, spatial and NoSQL databases.
  8. Advanced databases: object, object-relational, temporal, spatial and NoSQL databases.
  9. Advanced databases: object, object-relational, temporal, spatial and NoSQL databases.
  10. Advanced databases: object, object-relational, temporal, spatial and NoSQL databases.
  11. Advanced databases: object, object-relational, temporal, spatial and NoSQL databases.
  12. Distributed systems: basic programming models. Point-to-point and group communication models, synchronous and asynchronous distributed algorithms, message passing and distributed objects, distributed data model. Selected examples: client-server applications, peer-to-peer systems, publish-subscribe systems.
  13. Distributed systems: basic programming models. Point-to-point and group communication models, synchronous and asynchronous distributed algorithms, message passing and distributed objects, distributed data model. Selected examples: client-server applications, peer-to-peer systems, publish-subscribe systems.
  14. Distributed systems: basic programming models. Point-to-point and group communication models, synchronous and asynchronous distributed algorithms, message passing and distributed objects, distributed data model. Selected examples: client-server applications, peer-to-peer systems, publish-subscribe systems.
  15. Distributed systems: basic programming models. Point-to-point and group communication models, synchronous and asynchronous distributed algorithms, message passing and distributed objects, distributed data model. Selected examples: client-server applications, peer-to-peer systems, publish-subscribe systems.

Study Programmes

University graduate
Software Engineering and Information Systems (profile)
(1. semester)

Literature

(.), Lecture notes and recommended literature for the courses. Lecturers FER 2006,
Ralph Kimball, Margy Ross (2013.), The Data Warehouse Toolkit, 3rd edition, Wiley

Associate Lecturers

Laboratory exercises

General

ID 35238
  Winter semester
5 ECTS
L0 English Level
L1 e-Learning
30 Lectures
0 Exercises
60 Laboratory exercises
0 Project laboratory

Grading System

85 Excellent
75 Very Good
65 Good
50 Acceptable