• Description

When designing a program it is very important to take efficiency into account, that is to say, let it consume the minimum quantity of resources in order to carry out its goal. Therefore, computational time and memory space to store the data is to be minimized, as well as the number of messages to be sent through the network, the amount of consumed energy, etc.

There exist two fundamental tools to achieve this: data structures and algorithmic schemes:

• The data structures focus on how information is managed: they consist of strategies to organise data and reduce the access and manipulation time, as well as the storage space required.
• Algorithmic schemes focus on the computational process: they are general patterns that describe the necessary steps to reach a solution and they have to be particularized for the specific problem to solve.

This course presents the concepts on data structures and algorithms necessary for research. In particular, the subject reviews fundamental concepts of algorithmic complexity (space and temporary costs, calculation of the cost of an algorithm, typical orders of magnitude) as well as basic concepts of data structures (abstract data types, management of pointers and memory, etc). From this base, the subject deepens in usual data structures (stacks, queues, lists, trees, heaps, hash tables) and presents an introduction to algorithms on graphs (paths, shortest paths, tree generators, etc.).

• The subject within the syllabus as a whole

Data structures and algorithms is an optional course of the Interuniversity Master in Computational and Mathematical Engineering.

The knowledge acquired in this course will be useful in the development of practical activities in other courses of the master. In particular, it is recommended to enroll this course before enrolling Combinatorial optimisation.

• Professional fields to which it applies

The concepts acquired in this course are essential to develop software that efficiently uses any available computational resources. For this reason, this course is relevant to any work related to the design and implementation of software, especially in the field of R&D or applied mathematics.

• Prior knowledge

This course requires basic knowledges of algorithmics: knowing the basics of programming (loops, conditionals, etc.) and understanding algorithms described in pseudocode. Also it requires a previous knowledge of the Java object-oriented programming language sufficient to write, execute and test programs.

On the other hand, the central materials of the course are in English. By this reason, having a good level of written comprehension of technical English is recommended.

• Information prior to enrolment

Before enrolling this subject, it is necessary to have previous knowledge about algorithmics and Java programming and have a good level of technical English for written comprehension.

• Learning objectives and results

The general competences of the master taught in this course are:

• Understanding and applying advanced knowledge about computing and numerical or computational methods to engineering problems.
• Applying the mathematical and computational methods to the resolution of technological and engineering problems, particularly in tasks of research, development and innovation.
• Design, implement and validate algorithms using the most convenient structures.

The specific competences of this course are:

• Knowing the concept of abstract data type and knowing how to define an abstract data type for a concrete problem.
• Knowing the sequential abstract data types (stacks, queues, lists) and their operations, and knowing how to use them to resolve problems.
• Knowing the concept of asymptotic complexity, knowing how to calculate it for a given algorithm and being able to use it to compare two different algorithms from efficienncy point of view.
• Knowing different sorting algorithms, their advantages and disadvantages and how to choose the most appropriate in a concrete context.
• Knowing different strategies of information search (hashing, search trees), their advantages and disadvantages and know how to choose the most appropriate in a specific context.
• Knowing the main algorithms on graphs, their complexity and being able to use them to resolve concrete problems.
• Being able to choose the most appropriate data structure for a problem according to efficiency criteria and justify the decision.

• Content

The course is structured in four thematic blocks:

• View the UOC learning resources used in the subject

• Additional information on support tools and learning resources

The central material of the course is a book of reference in this field: "Algorithms, 4th Edition", by Robert Sedgewick and Kevin Wayne. The contents of the book go further of what we will study in the course and will be useful as a reference during your professional career.

To guide the study of the book and highlight the important contents of the book within the course, there will be a study guide in the classroom every week with advice on how to review the contents of the book.

As complementary material, there are some didactic UOC modules titled "Design of data structures". These materials can be used to solve any doubts that you may have when reviewing the book of the course. However, these materials mainly focus on how the data structures are implemented, whereas in this course we will focus more in knowing how to use them and the criteria to choose the most appropriate.

• Guidelines on assessment at the UOC

The assessment process is based on students' own work and the assumption that this work is original and has been carried out by them.

In assessment activities, the following irregular behaviours, among others, may have serious academic and disciplinary consequences: someone else being involved in carrying out the student's assessment test or activity, or the work being not entirely original; copying another's work or committing plagiarism; attempting to cheat to obtain better academic results; collaborating in, covering up or encouraging copying; or using unauthorized material, software or devices during assessment.

If students are caught engaging in any of these irregular behaviours, they may receive a fail mark (D/0) for the assessable activities set out in the course plan (including the final tests) or in the final mark for the course. This could be because they have used unauthorized materials, software or devices (e.g. social networking sites or internet search engines) during the tests, because they have copied text fragments from an external source (internet, notes, books, articles, other student's projects or activities, etc.) without correctly citing the source, or because they have engaged in any other irregular conduct.

In accordance with the UOC's academic regulations , irregular conduct during assessment, besides leading to a failing mark for the course, may be grounds for disciplinary proceedings and, where appropriate, the corresponding punishment, as established in the UOC's coexistence regulations.

In its assessment process, the UOC reserves the right to:

• Ask the student to provide proof of their identity, as established in the university's academic regulations.
• Request that students provide evidence of the authorship of their work, throughout the assessment process, both in continuous and final assessment, by means of an oral test or by whatever other synchronous or asynchronous means the UOC specifies. These means will check students' knowledge and competencies to verify authorship of their work, and under no circumstances will they constitute a second assessment. If it is not possible to guarantee the student's authorship, they will receive a D grade in the case of continuous assessment or a Fail in the case of final assessment.

  For this purpose, the UOC may require that students use a microphone, webcam or other devices during the assessment process, in which case it will be the student's responsibility to check that such devices are working correctly.

• View the assessment model