Algorithms and data structure

lsinc1121  2026-2027  Charleroi

Algorithms and data structure
5.00 credits
30.0 h + 30.0 h
Q1
> Schedule

  This learning unit is not open to incoming exchange students!

Teacher(s)
Schaus Pierre;
Language
French
Prerequisites
This course assumes the mastery of programming and program design in an object-oriented language such as Java, knowledge of elementary data structures and notions of recursion and computational complexity as targeted by the course LEPL1402.
The prerequisite(s) for this Teaching Unit (Unité d’enseignement – UE) for the programmes/courses that offer this Teaching Unit are specified at the end of this sheet.

The prerequisite(s) for this Teaching Unit (Unité d’enseignement – UE) for the programmes/courses that offer this Teaching Unit are specified at the end of this sheet.
Main themes
  • Complexity measures of an algorithm and complexity analysis methods.
  • Dichotomic sorting and search algorithms.
  • Basic data structures (lists, trees, binary search trees): study of their abstract properties, their concrete representations, their application and the main algorithms that manipulate them.
  • Advanced data structures (union-find, hash tables, heaps, balanced binary trees, graph representation and manipulation, textual data processing, dictionaries).
Learning outcomes

At the end of this learning unit, the student is able to :

Given the learning outcomes of the "Bachelor in Engineering" program, this course contributes to the development, acquisition and evaluation of the following learning outcomes:
  • AA1.1, AA1.2
  • AA2.4, AA2.5, AA2.7
  • AA3.2
  • AA4.3
Given the learning outcomes of the "Bachelor in Computer science" program, this course contributes to the development, acquisition and evaluation of the following learning outcomes:
  • S1.I1, S1.I3
  • S2.2, S2.3, S2.4
  • S4.3
  • S5.4
  • S6.1, S6.3
Students who have successfully completed this course will be able to :
  • make an informed choice on the use of the main data structures used to represent collections;
  • make good use of existing algorithms to manipulate these data structures and analyze their performance;
  • design and implement variants of the algorithms studied;
  • test algorithms and data structures;
  • make good use of algorithms and data structures documented in an API;
  • abstract, model and implement effective solutions to algorithmic puzzle problems.
Students will have developed methodological and operational skills. In particular, they will have developed their ability to:
  • analyze critically a problem;
  • to test and debug algorithmic programs;
  • effectively implement short but non-trivial algorithms.learn for themselves in a reference book and in the complementary technical documentation.
 
Content
  • Computational complexity,
  • Trees, binary search trees,
  • Balanced trees,
  • Dictionaries and hash tables,
  • Priority queues and heaps
  • Graphs,
  • Text processing (pattern matching, compression algorithms)
Teaching methods
The active pedagogy method followed in this course is inspired by reverse classes. There are six two-week modules. Each module includes an introductory course to the subject, theoretical exercises to prepare, chapters from the reference book to read, a practical work on correcting exercises in the middle of the model, work on inginious to be carried out (Java programs) and finally a restructuring course at the end of the module. One of the essential components of this pedagogy consists in making each student learn by himself. The success of the learning process therefore presupposes a significant involvement of each student. The actual learning remains the responsibility of each student. To pass the exam it is imperative that the student programs regularly.
Evaluation methods

Computer-based exam using INGInious

The exam will be held on a computer using INGInious: ⁠https://inginious.info.ucl.ac.be.
Generative AI tools may not be used during the individual exam. No collaboration or communication is permitted during the exam. The exam questions are written in English.
An algorithmic programming contest will also be organized. Active participation in the contest, corresponding to successfully solving at least one question, will earn you 1 additional point on the exam. In this case, the exam will be graded out of 19 instead of 20, and the point earned in the contest will be added to this grade.
Participation in the contest is optional: not participating will not result in any penalty.
 
Other information
Background: 
  • master an object-oriented programming language (p.e. Java)
  • know an use correctly basic data structures (stacks, queues, lists, etc..)
  • have basic knowledge of recursion and computational complexity.
This background is part of the content of LEPL1401 and LEPL1402.
Online resources
https://moodle.uclouvain.be/course/view.php?id=1049 (mainly for communications with students)
https://pschaus.github.io/LINFO1121/ (main website, with the exercices to do each week)
Bibliography
Livre obligatoire:
Algorithms, 4th Edition by Robert Sedgewick and Kevin Wayne, Addison-Wesley Professional.
ISBN-13: 978-0321573513
ISBN-10: 032157351X

Et plus généralement les documents (énoncés des missions, conseils pour l'examen, ...) disponibles sur : http://moodleucl.uclouvain.be/course/view.php?id=7682
Faculty or entity
> SINC


Programmes / formations proposant cette unité d'enseignement (UE)

Title of the programme
Sigle
Credits
Prerequisites
Learning outcomes
Bachelor in Computer Science
SINC1BA
5
LSINC1402