Introduction and 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.
The official plan of this course is hosted in FCUP here.
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.
Syllabus
 Algorithm correctness
 Complexity: worst/bestcase analysis
 Fundamentals of asymptotic analysis
 Averagecase and randomized algorithms
 Recursive algorithms
 Amortized analysis
 Data structures  Collections and Dictionaries
Lectures
 23 Sep 24: Introduction (1intro.pdf) and algorithm correctness: specifying problems logically (2correctness.pdf  pages 112)
 30 Sep 24: Algorithm correctness: partial and complete correctness (2correctness.pdf  pages 1336)
 7 Out 24: Motivation for performance analysis; Algorithms complexity: best and worst case analysis; Counting steps (3countingsteps.pdf  pages 143)
Literature and Material
Slides
 Introduction to the course
 Algorithm correctness
 Counting steps and asymptotic notation
 Averagetime and probabilistic algorithms
Main book
 Introduction to algorithms, Cormen Thomas H. et al.; ISBN: 9780262033848
Example Tests
 Intermediate test, used on the 10th Nov 2023, covering around 30% of the topics
 Final test (or improvement test), used on the 15th Dec 2023, covering the remaining 70% of the topics
Previous years
 Content from 2023/24 (very similar to this year) https://cisterlabs.github.io/alg2324/
 Slides from Pedro Ribeiro (2018/19): https://www.dcc.fc.up.pt/~pribeiro/aulas/alg1819/material.html#slides
 Content from Ana Paula Tomás (2021/22): https://www.dcc.fc.up.pt/~apt/Aulas/ALGO2223.html
 Slides from similar courses:
 By E. Demaine, C.E. Leiserson, MIT, 2001 (companion of the main book  more on the course)
 By Skiena, Stony Brook University, 2012
 By J. Barros, J.S. Pinto et. al, U. Minho (2022/23) (no content online)
Complementary Bibliography
 The algorithm design manual; Skiena Steven S.; ISBN: 9781848000698
 Competitive Programming 3: The New Lower Bound of Programming Contests; Steven Halim and Felix Halim; 2023
 Rigorous Software Development – An Introduction to Program Verification; José Bacelar Almeida, Maria João Frade, Jorge Sousa Pinto, Simão Melo de Sousa 2011; ISBN: 9780857290175
 Algorithms; Sedgewick Robert; ISBN: 0201066734
 Algorithm Design; Jon Kleinberg and Éva Tardos; 2005. ISBN: 9780321295354
 Tópicos Avançados em Algoritmos; Armando Matos; DCC/FCUP, 2008 (In Portuguese  some lecture notes)
 Desenho e Análise de Algoritmos – Alguns Apontamentos; Ana Paula Tomás; DCC/FCUP, 2013
Teaching methods and learning activities
Lectures; intermediate test and final test, 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 (%) 

Exam  70,00 
Test  30,00 
Amount of time allocated to each course unit
designation  Time (hours) 

Home study  120,00 
Attendance time  42,00 
Total:  162,00 
Eligibility for exams
All students will be admitted to the exam.
Calculation formula of final grade

(IT) intermediate midterm test: 30% (done during a lesson, required >=5.5)

(FT) final test: 70% (done during the normal exam period, required >=5.5)

(ER) final exam: 100% (done during “recurso” period, required >=9.5)
1st (“Normal”) classification: C = IT0.3+ FT0.7 >= 9.5
2nd (“Recurso”) classification: C = ER >= 9.5
Lecturer


 José Proença

 DCC 1.69
 jose.proenca(at)fc.up.pt
 meet: thu afternoon (email before)



 Pedro RIbeiro

 DCC 1.47
 pribeiro(at)fc.up.pt
 meet: tba

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