Study programme 2021-2022Français
Data Structures
Programme component of Master's in Computer Science (Charleroi (Hor. décalé)) à la Faculty of Science

CodeTypeHead of UE Department’s
contact details
Teacher(s)
US-M1-INFO60-009-CCompulsory UEBRUYERE VéroniqueS829 - Informatique théorique
  • BRUYERE Véronique
  • MASLOWSKI Dany

Language
of instruction
Language
of assessment
HT(*) HTPE(*) HTPS(*) HR(*) HD(*) CreditsWeighting Term
  • Français
Français301500055.001st term

AA CodeTeaching Activity (AA) HT(*) HTPE(*) HTPS(*) HR(*) HD(*) Term Weighting
S-INFO-105Data Structures3015000Q1100.00%

Programme component

Objectives of Programme's Learning Outcomes

  • Have acquired highly specialised and integrated knowledge and broad skills in the various disciplines of computer science, which come after those within the Bachelor's in computer science.
  • Carry out development or innovation projects in IT.
    • Apply, mobilise, articulate and promote the knowledge and skills acquired in order to contribute to the achievement of a development or innovation project.
  • Develop and integrate a high degree of autonomy.
    • Aquire new knowledge independently.

Learning Outcomes of UE

To understand how to efficiently solve problems of sorting and dictionnary management, thanks to adapted data structures. To be able to use them.

Content of UE

Advanced algorithms and data structures for the search, insertion and deletion of a data inside a set of data, as well as the sort of a set of data. Study of binary search trees, AVL trees, B-trees, hash tables, quicksort, optimal sorts. Study of the correctness of the algorithms, and of their complexity in the worst case and the average case.

Prior Experience

Basic algorithmics and data structures

Type of Assessment for UE in Q1

  • Written examination

Q1 UE Assessment Comments

Written examination 100%

Type of Assessment for UE in Q3

  • Written examination

Q3 UE Assessment Comments

Written examination 100%

Type of Resit Assessment for UE in Q1 (BAB1)

  • N/A

Q1 UE Resit Assessment Comments (BAB1)

Not applicable

Type of Teaching Activity/Activities

AAType of Teaching Activity/Activities
S-INFO-105
  • Cours magistraux
  • Exercices dirigés

Mode of delivery

AAMode of delivery
S-INFO-105
  • Face to face

Required Reading

AA
S-INFO-105

Required Learning Resources/Tools

AARequired Learning Resources/Tools
S-INFO-105Not applicable

Recommended Reading

AA
S-INFO-105

Recommended Learning Resources/Tools

AARecommended Learning Resources/Tools
S-INFO-105Not applicable

Other Recommended Reading

AAOther Recommended Reading
S-INFO-105Introduction to algorithms, by Thomas H. Cormen, Charles E. Leiserson, Ronald L.Rivest (1991). The MIT Press, Mc Graw-Hill.

Grade Deferrals of AAs from one year to the next

AAGrade Deferrals of AAs from one year to the next
S-INFO-105Authorized
(*) HT : Hours of theory - HTPE : Hours of in-class exercices - HTPS : hours of practical work - HD : HMiscellaneous time - HR : Hours of remedial classes. - Per. (Period), Y=Year, Q1=1st term et Q2=2nd term
Date de dernière mise à jour de la fiche ECTS par l'enseignant : 12/05/2021
Date de dernière génération automatique de la page : 06/05/2022
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Tél: +32 (0)65 373111
Courriel: info.mons@umons.ac.be