2019-2020 / INFO0027-2

Programming techniques

Duration

24h Th, 24h Pr, 70h Proj.

Number of credits

 Bachelor of Science (BSc) in Computer Science5 crédits 
 Master of Science (MSc) in Data Science5 crédits 
 Master of Science (MSc) in Computer Science and Engineering5 crédits 
 Master of Science (MSc) in Data Science and Engineering5 crédits 
 Master in mathematics (120 ECTS)6 crédits 
 Master in mathematics (60 ECTS)6 crédits 

Lecturer

Laurent Mathy

Language(s) of instruction

English language

Organisation and examination

Teaching in the second semester

Schedule

Schedule online

Units courses prerequisite and corequisite

Prerequisite or corequisite units are presented within each program

Learning unit contents

The course runs as two parts: the first part addresses algorithmic problem solving and describes examples of advanced algorithms, using C as the reference programming language. The second part provides an introduction to programming design patterns, using Java as the reference programming language.
Specifically, the first part content comprises the following topics: programming as problem solving; advanced sorting; balanced search; radix search; external algorithms; algorithms on graphs.

Learning outcomes of the learning unit

In this course, the students learn: - the principles of complex program decomposition; - to write efficient programs - knowledge of advanced algorithmic techniques - to apply programming patterns

Prerequisite knowledge and skills

Knowledge of basic algorithms. Practical knowledge of the C and Java programming languages.
INFO0902 or INFO2050
INFO0062

Planned learning activities and teaching methods

Lectures and practicals, both involving problem solving in class. The students carry out several assignments: some individual  programming assignments and some group mini-projects. The exact number and type of assignment varies depending on the year, although the student workload is kept similar.

Mode of delivery (face-to-face ; distance-learning)

Weekly lectures and practicals, Q2

Recommended or required readings

Optional recommended readings: Introduction to algorithms; Cormen, Leiserson, Rivest and Stein; MIT press.
Algorithms in C; Sedgewick; Addison Wesley.
Design patterns; Gamma, Helm, Johnson, Vlissides; Addison-Wesley.

Assessment methods and criteria

Written exam and assignments.The assignments count towards 40% of the final mark, while the exam counts towards 60% of the final mark. Each part of the course bears equal weight in the final mark.
During the written exam, the students can use the lecture and practical notes that were officially distributed on the myULiege course page (and only those).
Students who do not submit at least half the projects receive an absence mark for the corresponding exam session.

There is no guaranteed support for projects to be resubmitted for the resit session.

Work placement(s)

Organizational remarks

Contacts

  • Coordinator: L. Mathy, mailto: Laurent.Mathy@uliege.be
  • Assistant: Gaulthier Gain , mailto: gaulthier.gain@uliege.be

Adaptation of teaching commitments following the COVID-19 pandemic for the May-June 2020 session

Teaching methods implemented : distance-learning

Remote live lectures

Assessment subjects

Overall course material

Assessment methods

 Videoconference oral exam, time-limited MCQ and assignments. The assignments count towards 40% of the final mark, while the oral exam and the MCQ count towards 60% of the final mark.
Students who do not submit at least half the projects receive an absence mark for the corresponding exam session.
There is no guaranteed support for projects to be resubmitted for the resit session.

Contacts

  • Coordinator: L. Mathy, Laurent.Mathy@uliege.be
  • Assistant: Gaulthier Gain , gaulthier.gain@uliege.be et Sami Ben Mariem sami.benmariem@uliege.be

Adaptation of teaching commitments following the COVID-19 pandemic for the Aug-Sept 2020 session

Assessment subjects

Overall course material

Assessment methods

Videocall oral exam, time-limited on-line MCQ and group assignments. The assignments count towards 40% of the final mark, while the oral exam and MCQ count towards 60% of the final mark. For the resit exam session, students can resubmit coursework for which they did not obtain 10/20 or more, but can elect to keep marks from the first exam session. There is no guaranteed support for projects to be resubmitted for the resit session. If students resubmit the same work as in the first submission, they will get the same mark, including any potential late submission penalties. All submissions are INDIVIDUAL. Projects have the same weight as previously. There is no late submission possibility. Students who did not submit at least 2 projects across the two sessions will receive an absence mark for the corresponding exam session Submission deadline: 28/8 11:59pm

Contacts