Universidad Pública de Navarra - Nafarroako Univertsitate Publikoa
Public University of Navarre
| Course code: 505108 | 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.
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 |
Assessment activity |
Weight (%) | It allows test resit |
Minimum required grade |
|---|---|---|---|---|
|
RA8, RA9, RA10, RA12, RA13 |
Theoretical/Practical exam (Individually performed). |
50 | YES | 5 |
|
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
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.