Object-Oriented Programming

Objectives

This subject complements Fundamentals of Programming from a methodological point of view to acquire a good programming base and allow the student to become familiar with the object-oriented methodology and be able to tackle complex problems and generate robust and reusable code.

It also delves into the Python language from an object-oriented point of view, and shows how to use and implement data structures such as dictionaries, stacks, queues or ordered lists.

Learning outcomes

• Know the basic structures of programming.
• Develop programs using the most appropriate data structures of a programming language.
• He knows how to build complex programs efficiently.
• Acquire and demonstrate advanced knowledge of the theoretical and practical aspects and working methodology in the multimedia field.
• Solves problems using technical skills and technological resources.
• Define own learning objectives and design development processes that are consistent and realistic with these objectives and with the time available.

Skills

General skills

• Combine scientific knowledge with technical skill and technological resources to deal with difficulties in professional practice.

Specific skills

• Analyze, design and implement applications for the web, mobile devices, video games or general purposes, using programming languages and development tools.
• Develop and manage software and hardware in a multimedia environment.

Core skills

• Display professional skills in complex multidisciplinary contexts, working in networked teams, whether face-to-face or online, through use of information and communication technology.

Content

1. Modular programming: top-down design
2. Dictionaries
3. Introduction to Object Orientation (OO)
   • Classes and objects
   • methods
   • Inheritance
   • Entry and exit
4. Implementing data structures with OO: stacks, queues and ordered lists

Evaluation

Assessment is based on continuous monitoring of the student's academic work throughout the course. They are evaluated: active attendance in the classroom; participation in debates and directed team work; the performance of objective written tests; the presentation and exhibition of individual or group works; the completion of problems, practices with a computer, exercises and theoretical questions. The weighting is as follows:

• Participation observation: 5%
• Follow-up of work done: 10%
• Specific assessment tests (exams): 40%
  • Test 1: 10%, non-recoverable
  • Test 2: 30%, recoverable (minimum grade: 3.5)
• Completion of required work or projects: 40%
  • Practice 1 (groups of 1 or 2): 20%
  • Practice 2 (groups of 1 or 2): 20%
• Public defense of projects: 5%

Methodology

The classes are theoretical and practical and the entire syllabus that the student must know is explained.

Work is monitored in class.

The virtual campus is used to transmit general information about the subject, to publish related documents and to consult the subject's virtual support.

Bibliography

Key references

• Fernández, M. (2019). Introducción práctica a la programación con Python. Retrieved from https://ucercatot.uvic-ucc.cat/permalink/34CSUC_UVIC/1nl2ep/alma991001118811506718
• Lutz, M., Ascher, D. (2013). Learn Python (2 ed.). O'Reilly.
• Trejos, O. & Muñoz, L. (2021). Introducción a la Programación con Python. Retrieved from https://ucercatot.uvic-ucc.cat/permalink/34CSUC_UVIC/1nl2ep/alma991001120918106718
• Van Rossum, Guido (2017). Tutorial Python. Retrieved from http://docs.python.org.ar/tutorial
• Vancells, J., López, E. (1992). Programació: Introducció a l'algorísmica. Eumo Editorial.