Algorithms
Keywords |
Classification |
Keyword |
OFICIAL |
Computer Science |
Instance: 2016/2017 - 1S
Cycles of Study/Courses
Teaching language
Suitable for English-speaking students
Objectives
This course is about designing algorithms for computational problems, and how to think clearly about analyzing correctness and running time. The main goal is to provide the intellectual tools needed for designing and analyzing your own algorithms for new problems you need to solve in the future.
Learning outcomes and competences
Students should be able to understand the relationship between algorithm design, correctness proof and complexity analysis. Students should learn algorithmic techniques of general applicability and get to know some major algorithms in a few common domains. They will also obtain practical experience in applying generic algorithms to specific problems.
Working method
Presencial
Program
- Fundamentals of asymptotic analysis
- Divide and conquer design pattern and how to solve recurrences
- Amortized analysis
- Probabilistic analysis and randomized algorithms
- Linear sorting and selection algorithms
- Greedy and dynamic programming design patterns
- String matching algorithms
- Fundamentals of NP-completeness
- Introduction to Approximation Algorithms
Mandatory literature
Cormen Thomas H. 070;
Introduction to algorithms. ISBN: 9780262033848 hbk
Complementary Bibliography
Armando Matos; Tópicos Avançados em Algoritmos, DCC/FCUP, 2008 (In Portuguese - some lecture notes (http://www.dcc.fc.up.pt/~acm/aulas/aa/t1.pdf))
Steven Halim and Felix Halim; Competitive Programming 3: The New Lower Bound of Programming Contests, 2013 (https://sites.google.com/site/stevenhalim/)
Skiena Steven S.;
The algorithm design manual. ISBN: 978-1-84800-069-8
Sedgewick Robert;
Algorithms. ISBN: 0-201-06673-4
Jon Kleinberg and Éva Tardos; Algorithm Design, 2005. ISBN: 978-0321295354 (http://www.cs.princeton.edu/~wayne/kleinberg-tardos/)
Ana Paula Tomás; Desenho e Análise de Algoritmos – Alguns Apontamentos, DCC/FCUP, 2013 ((Some additional notes: http://www.dcc.fc.up.pt/~apt/aulas/DAA/1314/ApontamentosDAA.pdf))
Teaching methods and learning activities
Lectures; homework (exercises and paper reading); oral presentation of homework in class; intermediate tests or final exam.
The lectures mix the presentation of new material (introducing concepts, main algorithms and some results) with interactive discussion of their application when solving real problems.
The homework focus is on practical application of algorithmic concepts, consolidating the learned material.
The final exam and intermediate tests (closed book), globally evaluates the knowledge acquired by the students.
Evaluation Type
Distributed evaluation with final exam
Assessment Components
designation |
Weight (%) |
Exame |
80,00 |
Prova oral |
20,00 |
Total: |
100,00 |
Calculation formula of final grade
- (H1+H2) Two assignments (oral presentation of a topic): 20%
- (E) Final Exam: 80% of your final grade
- (T) Multiple "smaller" tests: Two tests, T1 and T2 will be offered during the semester (one midterm and one near the end). You can use them to get exemption from the final exam. T = 0.5*T1 + 0.5*T2. Required T1,T2 >= 8.
1st Exam ("Normal") classification: C = max(E,T)*0.8 + H1+H2 >= 9.5
2nd Exam ("Recurso") classification: C = E*0.8 + H1+H2 >= 9.5