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: | |||||
| PINA CALAFI, ALFREDO (Resp) [Mentoring ] | ARMENDARIZ IÑIGO, JOSÉ ENRIQUE [Mentoring ] | ||||
Contents
Stack and Queues. Tree programming. Graphs. Recursion. Modularity. Introduction to file handling.
General proficiencies
- CT4. Ability to work in muldisciplinary and multicultural teams.
- CT5. Ability to perform project-oriented work
Specific proficiencies
- CG1. Applying analytical and abstraction thinking, intuition and logical thinking to identify and analyze complex problems, and to search and pose solutions in a multidisciplinary environment.
- CG4. Using theoretical and practical thinking to extract information from homogeneous/heterogeneous datasets, particularly from large datasets.
- CE2. Using techniques to represent and fuse data and information.
- CE6. Knowing fundamentals of computer programming, including code efficiency and the limitations of basic data structures in code design.
Learning outcomes
- RA8. Identifying problems with natural recursive solutions.
- RA9. Understanding the concepts of stack and queue in the context of computer programming.
- RA10. Understanding the concepts of graph and tree in the context of computer programming.
- RA11. Designing modular programs for complex problem solution.
- RA12. Using efficient file handling in data analysis.
- RA13. Identifying the relationships between files and databases.
Methodology
|
Methodology-Activity |
Attendance (hours) |
Self-study (hours) |
|
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
|
Learning outcome |
Evaluation system |
Weight (%) |
Retake policy |
|
RA8, RA9, RA10, RA12, RA13 |
Theoretical/Practical exam (Individually performed). Every student must get at least 50% in this exam to average with the rest of the evaluable aspects. |
50 |
Yes |
|
RA8, RA9, RA10, RA11, RA12, RA13 |
Deliverables and practical exams |
40 |
No |
|
RA8, RA9, RA10, RA11, RA12, RA13 |
Continuous assessment. Active participation in the course |
10 |
No |
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¿
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.