Teaching GuideTerm
Faculty of Computer Science
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Grao en Enxeñaría Informática
 Subjects
  Algorithms
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Identifying Data 2017/18
Subject (*) Algorithms Code 614G01011
Study programme
Grao en Enxeñaría Informática
Descriptors Cycle Period Year Type Credits
Graduate 1st four-month period
Second Obligatoria 6
Language
Spanish
English
Teaching method Face-to-face
Prerequisites
Department Computación
Coordinador
Valderruten Vidal, Alberto
E-mail
alberto.valderruten@udc.es
Lecturers
Aguado Martin, Maria Felicidad
Cabalar Fernandez, Jose Pedro
Casanova Crespo, Jose Maria
Fontenla Romero, Oscar
Gómez Rodríguez, Carlos
Hernandez Pereira, Elena Maria
Jorge Castro, Jose Santiago
Perez Vega, Gilberto
Valderruten Vidal, Alberto
Vidal Martin, Concepcion
E-mail
felicidad.aguado@udc.es
pedro.cabalar@udc.es
jose.casanova.crespo@udc.es
oscar.fontenla@udc.es
carlos.gomez@udc.es
elena.hernandez@udc.es
santiago.jorge@udc.es
gilberto.pvega@udc.es
alberto.valderruten@udc.es
concepcion.vidalm@udc.es
Web http://www.dc.fi.udc.es/~alg
General description This course on Algorithms allows the computer science engineering student to delve into algorithm design techniques, taking into account qualitative and quantitative factors in their evaluation. On the one hand, it completes the training on the writing of efficient and correctly structured programs. On the other hand, it approaches the most common problem-solving techniques that an engineer can find. It is worth noting that the conduction of experiments involving runtime measurements on different algorithms provides an empirical approach that is usually highly regarded by the student, who can thus establish the concrete interpretation of the complexities found. The difficulties that arise in some of the studied cases allow for a complementary reflection on aspects like computing resource management, process execution details, architectures and operating systems used, etc. The study and analysis of an important set of fundamental algorithms is also worth remarking, covering a large range of algorithmic techniques and their applications. The possibility of using different techniques for the resolution of some problems results naturally into thinking about the advantages and disadvantages of the different strategies, and the need to know how to choose the best alternative for each particular scenario. Lastly, it is important to develop the necessary rigor to develop solutions that not only adapt to a given specification, but also do so in an efficient way from the viewpoint of the needed computational resources. This will be illustrated by means of various practical cases where the existence of known efficient algorithms leads us to reject alternative designs, even when they look very natural at a first glance.
(*)The teaching guide is the document in which the URV publishes the information about all its courses. It is a public document and cannot be modified. Only in exceptional cases can it be revised by the competent agent or duly revised so that it is in line with current legislation.
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