Universidad Pública de Navarra - Nafarroako Univertsitate Publikoa
Public University of Navarre
| Course code: 507109 | Subject title: DATA STRUCTURES | ||||
| Credits: 6 | Type of subject: Mandatory | Year: 1 | Period: 2º S | ||
| Department: Estadística, Informática y Matemáticas | |||||
| Lecturers: | |||||
| AMOZARRAIN PEREZ, UGAITZ (Resp) [Mentoring ] | |||||
Contents
Stack and Queues. Tree programming. Graphs. Recursion. Modularity. Introduction to file handling.
Learning outcomes
RA01. Apply acquired analytical and abstract thinking skills, intuition, and logical reasoning to identify and analyze complex problems, and to search for and formulate solutions in a multidisciplinary environment. TYPE: Knowledge or content
RA04. Be able to use theoretical and applied processes to extract information from homogeneous or heterogeneous datasets, particularly when dealing with large volumes of data. TYPE: Knowledge or content
RA10. Demonstrate the ability to work in multidisciplinary and multicultural teams. TYPE: Skills or abilities
RA11. Demonstrate the ability to work on a project basis. TYPE: Skills or abilities
RA14. Manage techniques for representing and merging data and information. TYPE: Competencies
RA18. Understand the fundamentals of computer programming, program efficiency, and the application and limitations of basic data structures that can be used in program design. TYPE: Competencies
Methodology
|
Methodology-Activity |
Attendance (hours) |
Self-study (hours) |
|
A1- Lecture / Collaborative classes |
26 |
|
|
A2- Lab Sessions |
30 |
|
|
A5- Study and autonomous work of the student |
|
86 |
|
A6- Tutoring |
|
4 |
|
A7- Assessment tests |
4 |
|
|
Total |
60 |
90 |
Evaluation
| Assessment activity |
Weight (%) | It allows test resit |
Minimum required grade |
|---|---|---|---|
|
Theoretical/Practical exam (Individually performed). |
50 | YES | 5 |
|
Deliverables and practical exams |
40 | YES | |
|
Continuous assessment. Active participation in the course |
10 | YES |
All evaluation activities will be subject to recovery during the resit examination.
Agenda
- The Stack Abstract Data Type (ADT);
- The Queue & Double Ended Queue (Deque) ADTs;
- The List ADT;
- Introduction to Computational Complexity Analysis
- Introduction to Recursion
- The Binary Tree ADT;
- The Binary Search Tree (BST) ADT;
- Introduction to Graphs;
- Programming features: Modularity with Python, Files with Python
Experimental practice program
The practical sessions will consist of developing a series of projects to be carried out either in 1, 2 or 3 weeks. They will serve to apply all the theoretical concepts and strengthen the knowledge of structured programming with Python. The projects will be known at the beginning of the course, and all the technical features will be introduced, and progressively solved, in each session.
Bibliography
Access the bibliography that your professor has requested from the Library.
The basic bibliography of the course is:
- Kent D. Lee, Steve Hubbard, Data Structures and Algorithms with Python, Ed. Cham. Springer International Publishing.
The complementary bibliography of the course is:
- Jim Knowlton, Python: Create ¿ Modify ¿ Reuse, Wrox Press, 2008.