The course builds on the student’s prior knowledge of unstructured and structured programming, and provides tools aimed at achieving efficient and high-quality software development.
Additionally, the course covers modular programming and the supporting tools associated with this programming paradigm. Modular programming is the natural evolution of structured programming and serves as a preliminary step toward object-oriented programming.
The purpose of the subject is to achieve knowledge oriented towards obtaining quality software in an efficient manner.
Titular Professors
Professors
Programming Fundamentals.
The aim of this course is for students to acquire the knowledge and develop the skills needed to analyze and solve problems through programming. It seeks to foster the ability to understand and abstract real-world problems, design correct and efficient solutions, and develop algorithmic thinking.
Additionally, the course introduces the fundamentals of structured and modular programming, the use of pseudocode and an imperative programming language such as C, as well as the ability to interpret and build programs. Finally, it promotes the development of consistent study and work habits.
- Files
- Pointers and Dynamic Memory
- Linear Data Structures
- Introduction to Recursion
The teaching methodology is based on an active and theory-practice approach aimed at the progressive acquisition of the course learning outcomes. The course combines lectures, practical sessions, and students’ independent work, ensuring an appropriate integration of theory and practice.
Lectures focus on introducing fundamental concepts and explaining the basic principles of programming. These are complemented by practical sessions, where students apply the acquired knowledge through problem-solving and guided exercises.
On a continuous basis, students complete weekly exercises that reinforce content understanding and foster the development of algorithmic thinking. In addition, more comprehensive practical assignments are proposed, aimed at the design and implementation of complete solutions, including an individual project or assignment that allows students to consolidate their learning independently.
The methodology is complemented by assessment activities, such as exams, and by students’ personal study, which is essential for consolidating the knowledge and skills developed in class. Overall, it promotes a progressive learning process that combines guided work, applied practice, and independent study, in line with the established workload.
The assessment elements for the subject are practicals, continuous assessment and final exams.
The student will be assessed on:
- The ability to apply computational thinking in solving exercises.
- The understanding and correct application of basic algorithmic concepts.
- The correct use of the C programming language to solve problems and exercises.
- The preparation of documentation that clearly and comprehensively explains the developed programs.
- The ability to understand the requirements of a problem and propose a solution in the form of an algorithm.
- Carmen, Thomas H.; Leiserson Charles E.; Rivest Ronald L; Stein Clifford. Introduction to Algorithms, The MIT Press, 2009.
- García-Bermejo, J.R. Programación Estructurada en C, Pearson/Prentice-Hall, 2008.
- Hanly, Jerry R.; Koffman, Elliot B.; Problem Solving and Program Design in C, Pearson Education, 2013.
- Joyanes, L. Fundamentos de la programación. Algoritmos y Estructura de Datos, McGraw-Hill, 2008.
- Kernighan, Brian W.; Ritchie, Dennis M. El lenguaje de programación C, Prentice-Hall Hispanoamericana, 1991.
- Kruse, Robert Leroy; Tondon, Clovis L.; Leung, Bruce P. Data structures and program design in C, Prentice-Hall, 1997.
- Weiss, Mark Allen. Estructuras de datos y algoritmos, Addison-Wesley Iberoamericana, 1995.
Only the basic bibliography is required.