Educational guide
IDENTIFYING DATA 2024_25
Subject ESTRUCTURAS DE DATOS Code 00717009
Study programme
0717 - GRADO INGENIERÍA DATOS INTELIGENCIA ARTIFICIAL
Descriptors Credit. Type Year Period
6 Basic Training First Second
Language
Castellano
Prerequisites
Department ING.MECANICA,INFORMAT.AEROESP.
Coordinador
CUERVO FERNÁNDEZ , EVA MARÍA
E-mail emcuef@unileon.es
jmalip@unileon.es
Lecturers
ALIJA PÉREZ , JOSÉ MANUEL
CUERVO FERNÁNDEZ , EVA MARÍA
Web http://agora.unileon.es
General description This course aims to familiarize the student with the different types of data structures and their management techniques. Emphasis is placed on the analysis of the characteristics of the information that justify the choice of a type of structure that facilitates the operations to be performed with that information.
Tribunales de Revisión
Tribunal titular
Cargo Departamento Profesor
Presidente ING.MECANICA,INFORMAT.AEROESP. FERNANDEZ DIAZ , RAMON ANGEL
Secretario ING.MECANICA,INFORMAT.AEROESP. PEREZ GARCIA , HILDE
Vocal CONDE GONZALEZ , MIGUEL ANGEL
Tribunal suplente
Cargo Departamento Profesor
Presidente ING.MECANICA,INFORMAT.AEROESP. PANIZO ALONSO , LUIS
Secretario FERNANDEZ ROBLES , LAURA
Vocal ING.MECANICA,INFORMAT.AEROESP. RODRIGUEZ LERA , FRANCISCO JAVIER

Competencias
Code  
A18986
A18987
B5800
B5803
B5806
B5809
C2 CMECES2 That students know how to apply their knowledge to their work or vocation in a professional manner and possess the skills that are usually demonstrated through the development and defense of arguments and the resolution of problems within their area of study.
C5 CMECES5 That students have developed those learning skills necessary to undertake further studies with a high degree of autonomy

Learning aims
Competences
Students know, design and efficiently use the most appropriate data types and structures to solve a problem. A18986
A18987
Students now the basic programming principles for writing code that implements and/or uses data structures. A18986
 B5800
B5803
B5806
B5809
 C2
C5

Contents
Topic Sub-topic
Block I: BASIC DATA STRUCTURES Topic 1: OBJECT ORIENTED PROGRAMMING FOUNDATIONS
Basic concepts of Object Oriented Programming.

Topic 2: ABSTRACT DATA TYPES AND INTERFACES.

Topic 3: INTRODUCTION TO ALGORITHM ANALYSIS.

Topic 4: STACKS

Topic 5: QUEUES

Topic 6: LISTS

Topic 7: RECURSION

Topic 8: ORDERING AND SEARCHING
Block II - ADVANCED DATA STRUCTURES Topic 1: TREES

Topic 2: GRAPHS

Topic 3: HASH TABLES

Planning
Methodologies  ::  Tests
  Class hours Hours outside the classroom Total hours
Lecture 28 44 72
 
Laboratory practicals 24 48 72
 
Personal tuition 2 0 2
 
Mixed tests 6 6 12
Practical tests 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
Lecture Presentation of basic concepts and presentation of solutions to typical exercises of each topic.
Laboratory practicals Practical classes in which the teacher poses problems and the student solves them based on the concepts introduced in the lectures and the teacher's advice. These exercises must be handed in to be evaluated.
Personal tuition Attention to specific difficulties with the topics explained and the problems proposed.

Personalized attention
 
Personal tuition
Description
The personalized tutorials will help the student to solve specific doubts about the theoretical concepts or about some of the proposed exercises.
They will be carried out by e-mail or in person in the teacher's office or in the computer room.

Assessment
  Description Qualification
Mixed tests Quizzes or partial exams to be taken throughout the semester. They can be either multiple-choice quizzes, short questions or requests for small code fragments. (At least a 4 out of 10 is required in each of them in order to pass the course).
 60%
Practical tests Several practical exercises will be proposed and must be handed in on the established date. The practical exercises that are submitted late will be penalized in the score:
- Up to one week: one point less (out of 10).
- Between one and two weeks: three points less (out of 10).
- Deliveries after two weeks of the deadline will have a maximum grade of 5 (out of 10).
Each of the practicals must have a minimum grade of 4 in order to pass.
The teacher can call the students to take a practical exam on the practices carried out if he/she considers it appropriate.
 35%
This grade will be added when a minimum grade of 4 has been obtained in each of the mixed tests.
Others Personal evaluation of the teacher based on the student's attendance and participation.
 5%
 
Other comments and second call

In the case of not taking developmental tests, that 5% will be added to the mixed tests that would be worth 55% of the final grade of the course.

In the second call it will be possible to recover the pending part of the mixed tests and the practical tests. The conditions will be the same as in the first call. There will be two partial exams in which at least a 4 must be obtained in each one of them (the grade of the partial and practical exams passed in the first call will be kept). All the proposed practices must be handed in, obtaining at least a 4 in each one of them. The professor can call the students to take a practical exam on the practices carried out if he/she considers it appropriate.

Both the work and the practices presented by the students may be reviewed with an anti-plagiarism program that can perform checks between the work of the students of the current call, the previous calls and other external sources. If plagiarism is detected, the exam will be immediately withdrawn, the student will be expelled and the work or practice submitted will be graded as failed. In any case, the provisions of the internal regulations of the ULE included in the document "Guidelines for action in cases of plagiarism, copying or fraud in exams or evaluation tests" (Approved by the Standing Committee of the Governing Council 29/01/2015) will be taken into account.

Sources of information
Access to Recommended Bibliography in the Catalog ULE

Basic , , ,
, , ,
Alfred V. Aho, Data structures and algorithms, Prentice Hall, 1998
Michael T. Goodrich, Tamassia, Goldwasser, Data Structures and Algorithms in Python, Wiley, 2013
yang hu, Easy Learning Data Structures and Algorithms Python 3, , 2021

Complementary Bruno R. Preiss, Data Structures and Algorithms with Object-Oriented design patterns in Java, John Willey &Sons, 2000
Bruce Eckel, Piensa en JAVA, Pearson. Prentice Hall, 2007


Recommendations


Subjects that it is recommended to have taken before
PROGRAMACIÓN / 00717005