Identifying Data 2023/24
Subject (*) Programming II Code 614G01006
Study programme
Grao en Enxeñaría Informática
Descriptors Cycle Period Year Type Credits
Graduate 2nd four-month period
 First Basic training 6
Language
Spanish
Galician
English
Teaching method Face-to-face
Prerequisites
Department Ciencias da Computación e Tecnoloxías da Información
Computación
Coordinador
Vilares Ferro, Jesus
 E-mail
jesus.vilares@udc.es
Lecturers
Alonso Pardo, Miguel angel
Cabado Lousa, Bruno
Cabrero Canosa, Mariano Javier
Guerreiro Santalla, Sara
Guijarro Berdiñas, Berta M.
Hernandez Pereira, Elena Maria
Magaz Romero, Samuel
Morán Fernández, Laura
Naya Varela , Martín
Paz Ruza, Jorge
Pérez Sánchez, Beatriz
Perez-Campoamor Manzaneque, Antonio
Rodríguez Arias, Alejandro
Romero Montero, Alejandro
Sanchez Maroño, Noelia
Suárez Marcote, Samuel
Vilares Calvo, David
Vilares Ferro, Jesus
Zamaraeva , Olga
 E-mail
miguel.alonso@udc.es
bruno.cabado@udc.es
mariano.cabrero@udc.es
sara.guerreiro@udc.es
berta.guijarro@udc.es
elena.hernandez@udc.es
s.magazr@udc.es
laura.moranf@udc.es
martin.naya@udc.es
j.ruza@udc.es
beatriz.perezs@udc.es
a.perez-campoamor@udc.es
alejanro.rodriguez.arias@udc.es
alejandro.romero.montero@udc.es
noelia.sanchez@udc.es
s.suarez.marcote@udc.es
david.vilares@udc.es
jesus.vilares@udc.es
olga.zamaraeva@udc.es
Web http://campusvirtual.udc.gal
General description A materia céntrase na programación con estruturas de datos dinámicas e complexas, tratadas baixo a óptica dos tipos de datos abstractos. Pertence ao bloque de materias de Linguaxes e Programación do Módulo de Formación Básica da titulación. Presenta unha forte interrelación coas materias do Módulo Común á Rama de Informática, sendo as relacións mais estreitas con Programación I, Bases de Datos, Algoritmos e Deseño Software. Tamén presenta certa relación co bloque temático de Matemáticas, especialmente coa materia Matemática Discreta. Respecto ao perfil profesional, moitas áreas da computación requiren a habilidade de traballar coas estruturas de datos que se estudan nesta materia que permitirá aos/as estudantes mellorar as súas habilidades como programadores/as.

Study programme competencies
Code Study programme competences
A3 Capacidade para comprender e dominar os conceptos básicos de matemática discreta, lóxica, algorítmica e complexidade computacional e a súa aplicación para a resolución de problemas propios da enxeñaría.
A4 Coñecementos básicos sobre o uso e a programación dos ordenadores, sistemas operativos, bases de datos e programas informáticos con aplicación na enxeñaría.
B1 Capacidade de resolución de problemas
B3 Capacidade de análise e síntese
C3 Utilizar as ferramentas básicas das tecnoloxías da información e as comunicacións (TIC) necesarias para o exercicio da súa profesión e para a aprendizaxe ao longo da súa vida.
C6 Valorar criticamente o coñecemento, a tecnoloxía e a información dispoñible para resolver os problemas cos que deben enfrontarse.

Learning aims
Learning outcomes Study programme competences
Understanding the mechanisms of dynamic memory management. A4
 B1
 C6
Understanding the mechanisms of abstraction in the design of data structures. A4
 B1
B3
 C3
C6
Building specifications, designing the abstract type from them, using appropriate data structures. A3
A4
 B1
B3
 C3
C6
Using appropriate data structures and program algorithms to solve real problems. A3
A4
 B1
B3
 C3
C6
Assuming the need for a good specification and a good design as steps prior to coding. A4
 B3
 C6
Internalizing good programming practices. A4
 B3

Contents
Topic Sub-topic
Dynamic Memory Management Program memory organization.
Definition of pointer variables.
Dynamic memory allocation and deallocation.
Pointer assignment and comparison.
Introduction to Abstract Data Types (ADT) Abstraction in programming: Concept, Evolution through computer programming history, ADT and Object Oriented Programming.
Modularity in programming.
Abstract Data Types: Definition and concept, Differences between datatype, data structure and ADT, ADT construction, Advantages of data abstraction.
Lists Informal specification of List ADT.
Implementations of List ADT.
Ordered list ADT: specification and implementations.
Multilists and multiordered lists: concept, representations and usage.
Stacks Informal specification of Stack ADT.
Implementations of Stack ADT.
Applications on computer science.
Queues Informal specification of Queue ADT.
Implementations of Queue ADT.
Queue variants. Priority queues.
Applications on computer science.
Trees Tree definition and terminology.
Binary Tree ADT: Informal specification, Implementation.
Binary Tree traversals.
Binary Search Trees Binary Search Trees.
AVL Trees.

Planning
Methodologies / tests Competencies Ordinary class hours Student’s personal work hours Total hours
Guest lecture / keynote speech A3 A4 B1 B3 30 30 60
Problem solving A3 B1 B3 C6 10 14 24
Laboratory practice A4 B1 B3 C3 C6 20 26 46
Objective test A3 A4 B1 B3 3 15 18
 
Personalized attention 2 0 2
 
(*)The information in the planning table is for guidance only and does not take into account the heterogeneity of the students.

Methodologies
Methodologies Description
Guest lecture / keynote speech Used for face-to-face theory lectures. The teacher will make a brief description of the topics and objectives , in order to provide students with an overview of the subject. In addition, they will establish relationships with other concepts previously acquired to build a timeline, and set out the recommended bibliography. They will then develop the theoretical contents.
Problem solving In the problem solving lectures, practical cases directly related with the theoretical concepts will be presented in order to reinforce those concepts. Initially, they will be resolved by the teacher to guide students. As the development of theoretical content advances, students will solve problems organized into working groups.

When the examples used in problem solving lectures or theoretical explanations involve coding or pseudocode, they will be developed showing the successive steps of top-down design. The reason is twofold: (a) to get the student used to employ this method; and (b) to avoid getting lost in the details of the particular syntax and features of the language, instead of paying attention to the understanding and design of the solution.

Additional exercises will be assigned as extra-classroom activities. The student must solve them and comment/correct them with the teacher during group and/or individual tutoring . The purpose is to encourage the participation of students and promote, as far as possible, open dialogue and evaluation of solutions.
Laboratory practice Practical lectures will consist in the development of continuous and incremental practicals that require the students to program data structures in a high-level language. Regular delivery milestones will be proposed as follow-ups to encourage continued study. Practical project instructions will detail the nature of the problem to solve and its specifications, which must be strictly observed. These instructions will be provided sufficiently in advance for the students to read it carefully and analyze it in depth. Subsequently, the role of the teacher will be to oversee the practical sessions, solving doubts and correcting misunderstandings, bad programming habits and syntax errors, etc.
Objective test Summative evaluation of the student through a final exam at the end of the fourth-month period, so that the student can demonstrate that he/she has acquired the required skills on abstraction, design, implementation and use of ADTs, and that he/she is sufficiently trained to use the precise skills to solve practical cases involving the application of such structures.

Personalized attention
Methodologies
Problem solving
Laboratory practice
Objective test
Description
The development of theory lectures, problem-solving sessions and practical sessions will be carried out taking into account the progress of the students. The general progress of the class will be combined with specific attention to give additional support or expand knowledge.

Laboratory practices will be carried out, in part, as autonomous work. For its correct development, periodic monitoring will be necessary to allow students to clarify errors of concept as soon as possible and to ensure the quality of the work.

In both cases, Moodle will be used to make available to the students "thematic forums" that resolve the general doubts detected related to specific activities such as the practices or problems proposed.

Individual tutoring should not be used to extend the contents with new concepts, but to clarify the concepts already discussed in class. The teacher will use them as an interaction that allows him/her to draw conclusions about the degree of assimilation of the subject by the students. Attention is maintained in the official tutoring hours through the following channels:
- Email: Of use to make short answer queries.
- Teams: virtual meetings preferably upon request via email.

Assessment
Methodologies Competencies Description Qualification
Problem solving A3 B1 B3 C6 The results, form and conditions of completion of various assessable works that will be detailed during the course and that will be resolved during the SMALL GROUP TUTORIALS will be assessed.

The result of the activity, as well as the discussion and active participation in class, will be valued in the final grade.

This grades of these activities will only be added to the remaining grades once the course is passed. 		10
Laboratory practice A4 B1 B3 C3 C6 The practical works are mandatory according to the conditions stablished in each problem assignment. There will be a periodic follow-up of the development of these practicals throughout the course that will influence their grades.

Students must present all the practical assignments and obtain a global minimum of 4.5 out of 10 points to pass the subject.

The work submitted must be the student's original work. According to Article 11, Section 4 b) of the UDC Student Disciplinary Regulations ("Reglamento disciplinar del estudiantado de la Universidad de A Coruña"). the submission of non-original work or work with duplicate parts (either by copying among classmates, obtaining from other sources, etc.) will result in a grade of FAIL with 0 points in that full ANNUAL CALL for both the group that employed copied material and the group that provided it.
 40
Objective test A3 A4 B1 B3 Mandatory realization. It implies a global treatment of the contents covered throughout the course. It will be eminently practical so that students can demonstrate that they have acquired the necessary knowledge of abstraction, design, implementation and use of ADTs and that they have trained sufficiently in the skills required by the course.

A minimum grade of 4,5 out of 10 is required to pass the course. 		60
 
Assessment comments

On attending
the practical classes

Repeated
non-attendance could carry a penalty in the grade according to the specific
conditions that will be detailed at the beginning of the course.

On shared
responsibility for group work

In the activities carried out in groups, such as practicals,
all members of the group will be jointly liable for the work carried out and
delivered, as well as the consequences arising from non-compliance with the
rules of authorship of the work.

About the final
note of the minutes

In the event
that the conditions for the joint calculation of the grade between the final
test and the practicals are not met (that is, if either of the two is less than
4.5 out of 10), the minutes will include the minimum mark between 4.5 and the
one resulting from the joint calculation.

Second Chance Evaluation

The mark of the exam ("Objective test") is NOT kept between opportunities.

The marks of the "Laboratory practices" as
well as the block of "Problem Solving" will be kept for the second
opportunity. Only lab practicals qualified with FAIL ("Suspenso") or NOT SUBMITTED ("No Presentado") in the first
opportunity may be delivered in the second, always according to the statement
that is proposed for it.

In line with the UDC evaluation regulations, those grades derived from other activities developed throughout the course as
part of the continuous evaluation (introductory practicals, follow-ups of lab practicals, tests in
Small Tutoring Groups, etc.) will not be recoverable for the second opportunity.

Regarding the evaluation criteria, the second
opportunity will keep the same as the first one.

Part-time
enrollment

In the case of students with part-time enrollment,
the obligation to attend practical lectures is eliminated. However, they will
have to deliver the assessable activities under the specific conditions and
deadlines that will be established during the course. It is the responsibility
of these students to inform the teacher of their circumstances.

Advanced 
Opportunity in December

The evaluation of this advanced opportunity will be based
exclusively on a written test.

Sources of information
Basic Ignacio Zahonero y Luis Joyanes Aguilar (2004). Algoritmos y estructuras de datos: Una perspectiva en C. McGraw-Hill
Narasimha Karumanchi (2017). Data Structures and Algorithms Made Easy, 5th Edition. CareerMonk Publications
Kyle Loudon (1999). Mastering Algorithms with C. O'Reilly Media

Complementary Aaron M. Tenenbaum, Yedidyah Langsam & Moshe J. Augenstein (1989). Data Structures Using C. Prentice Hall
Reema Thareja (2014). Data Structures Using C - Second Edition. Oxford University Press
Richard F. Gilberg & Behrouz A. Forouzan (2005). Data Structures: A Pseudocode Approach with C (2nd Ed). Cengage Learning
Ignacio Zahonero, Lucas García Sánchez, Luis Joyanes Aguilar y Matilde Fernández Azuela (2005). Estructuras de datos en C (Serie Schaum). McGraw-Hill
Luis Joyanes Aguilar, Andrés Castillo Sanz, Lucas Sánchez García e Ignacio Zahonero Martínez (2002). Programación en C. Libro de problemas. McGraw-Hill
Ignacio Zahonero y Luis Joyanes Aguilar (2005). Programación en C. Metodología, Algoritmos y Estructura de Datos, 2º Edición. McGraw-Hill

Official page of CLion integrated development environment: https://www.jetbrains.com/clion/

Recommendations
Subjects that it is recommended to have taken before
Programming I/614G01001
Computer Science Preliminaries/614G01002
Discrete Mathematics/614G01004

Subjects that are recommended to be taken simultaneously

Subjects that continue the syllabus
Algorithms/614G01011
Databases/614G01013
Programming Paradigms/614G01014
Software Design/614G01015

Other comments

DISCREPANCIES BETWEEN LANGUAGES

In case of discrepancies in the interpretation of the different translations of the Teaching Guide of this course, the Galician Teaching Guide will be taken as a reference.

GENDER PERSPECTIVE

As stated in the different regulations applicable to university teaching, this course incorporates the gender perspective. The intervention of male and female students in class will be encouraged, and work will be done to identify and modify sexist prejudices and attitudes, and the environment will be influenced to modify them and promote values of respect and equality. Situations of gender discrimination should be detected and actions and measures to correct them will be proposed.


(*)The teaching guide is the document in which the URV publishes the information about all its courses. It is a public document and cannot be modified. Only in exceptional cases can it be revised by the competent agent or duly revised so that it is in line with current legislation.