Universidad Pública de Navarra - Nafarroako Univertsitate Publikoa
Public University of Navarre
| Course code: 506108 | Subject title: DATA STRUCTURES | ||||
| Credits: 6 | Type of subject: Basic | 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
RA10. Demonstrate ability to work in multidisciplinary and multicultural teams TYPE: Skills or abilities.
RA11. Demonstrate ability to work on a project basis TYPE: Skills or competences.
RA15. Understand the fundamentals of programming, the efficiency of programs, and the application and limitations of basic data structures in program design. TYPE: Competences.
Methodology
|
Methodology - Activity |
Face-to-face instruction |
Out-of-class work |
|
A1- Lecture / Collaborative classes |
26 |
|
|
A2- Lab Sessions |
30 |
|
|
A3- Study and autonomous work of the student |
|
86 |
|
A4- Tutoring |
|
4 |
|
A5- 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 | - |
If the minimum requirement is not met in any of the activities, the maximum final grade for the course will be 4.9 out of 10 (fail).
All assessment activities can be retaken in the resit exam.
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.