Programming II

Credits
7.5
Types
Compulsory
Requirements
This subject has not requirements, but it has got previous capacities
Department
CS
In this course, modular design and object-oriented design are introduced, using C++ programming language; new data structures are presented, both linear (stacks, queues, lists) and hierarchical (binary, n-ary and general trees); iterative design and recursive design are studied in depth, emphasizing the importance of reasoning about the correctness of a given design, and the detection and improvement of ineficient solutions; finally, implementations of linear and tree data structures are presented, using recursive data types.

Teachers

Person in charge

  • Borja Valles Fuente ( )
  • Guillem Godoy Balil ( )
  • Juan Luis Esteban Ángeles ( )

Others

  • Albert Calvo Ibañez ( )
  • Alejandro Ivan Paz Ortiz ( )
  • Alfonso Valverde Ruiz ( )
  • Jorge Castro Rabal ( )
  • Jose Carmona Vargas ( )
  • M. Luisa Bonet Carbonell ( )
  • Maria Josefina Sierra Santibañez ( )
  • Pau Fernandez Duran ( )
  • Santiago Marco Sola ( )
  • Xavier Messeguer Peypoch ( )

Weekly hours

Theory
2
Problems
0
Laboratory
3
Guided learning
0.3
Autonomous learning
7.2

Competences

Transversal Competences

Teamwork

  • G5 [Avaluable] - To be capable to work as a team member, being just one more member or performing management tasks, with the finality of contributing to develop projects in a pragmatic way and with responsibility sense; to assume compromises taking into account the available resources.
    • G5.1 - Capacity to collaborate in a unidisciplinary environment. To identify the objectives of the group and collaborate in the design of the strategy and the working plan to achieve them. To identify the responsibilities of each component of the group and assume the personal compromise of the assigned task. To evaluate and present the own results. To identify the value of the cooperation and exchange information with the other components of the group. To exchange information about the group progress and propose strategies to improve its operation.
  • CT3 - Ability to work as a member of an interdisciplinary team, as a normal member or performing direction tasks, in order to develop projects with pragmatism and sense of responsibility, making commitments taking into account the available resources.
  • CTR3 - Capacity of being able to work as a team member, either as a regular member or performing directive activities, in order to help the development of projects in a pragmatic manner and with sense of responsibility; capability to take into account the available resources.

Entrepreneurship and innovation

  • G1 - To know and understand the organization of a company and the sciences which govern its activity; capacity to understand the labour rules and the relation between planning, industrial and business strategies, quality and benefit. To develop creativity, entrepreneur spirit and innovation tendency.
  • CT1 - Know and understand the organization of a company and the sciences that govern its activity; have the ability to understand labor standards and the relationships between planning, industrial and commercial strategies, quality and profit. Being aware of and understanding the mechanisms on which scientific research is based, as well as the mechanisms and instruments for transferring results among socio-economic agents involved in research, development and innovation processes.
  • CTR1 - Capacity for knowing and understanding a business organization and the science that rules its activity, capability to understand the labour rules and the relationships between planning, industrial and commercial strategies, quality and profit. Capacity for developping creativity, entrepreneurship and innovation trend.

Appropiate attitude towards work

  • G8 - To have motivation to be professional and to face new challenges, have a width vision of the possibilities of the career in the field of informatics engineering. To feel motivated for the quality and the continuous improvement, and behave rigorously in the professional development. Capacity to adapt oneself to organizational or technological changes. Capacity to work in situations with information shortage and/or time and/or resources restrictions.
  • CT5 - Capability to be motivated for professional development, to meet new challenges and for continuous improvement. Capability to work in situations with lack of information.
  • CTR5 - Capability to be motivated by professional achievement and to face new challenges, to have a broad vision of the possibilities of a career in the field of informatics engineering. Capability to be motivated by quality and continuous improvement, and to act strictly on professional development. Capability to adapt to technological or organizational changes. Capacity for working in absence of information and/or with time and/or resources constraints.

Reasoning

  • G9 - Capacity of critical, logical and mathematical reasoning. Capacity to solve problems in her study area. Abstraction capacity: capacity to create and use models that reflect real situations. Capacity to design and perform simple experiments and analyse and interpret its results. Analysis, synthesis and evaluation capacity.
  • CT6 - Capability to evaluate and analyze on a reasoned and critical way about situations, projects, proposals, reports and scientific-technical surveys. Capability to argue the reasons that explain or justify such situations, proposals, etc..
  • CTR6 - Capacity for critical, logical and mathematical reasoning. Capability to solve problems in their area of study. Capacity for abstraction: the capability to create and use models that reflect real situations. Capability to design and implement simple experiments, and analyze and interpret their results. Capacity for analysis, synthesis and evaluation.

Sustainability and social commitment

  • G2 - To know and understand the complexity of the economic and social phenomena typical of the welfare society. To be capable of analyse and evaluate the social and environmental impact.
  • CT2 - Capability to know and understand the complexity of economic and social typical phenomena of the welfare society; capability to relate welfare with globalization and sustainability; capability to use technique, technology, economics and sustainability in a balanced and compatible way.
  • CTR2 - Capability to know and understand the complexity of the typical economic and social phenomena of the welfare society. Capacity for being able to analyze and assess the social and environmental impact.

Third language

  • G3 - To know the English language in a correct oral and written level, and accordingly to the needs of the graduates in Informatics Engineering. Capacity to work in a multidisciplinary group and in a multi-language environment and to communicate, orally and in a written way, knowledge, procedures, results and ideas related to the technical informatics engineer profession.
  • CT5 - Achieving a level of spoken and written proficiency in a foreign language, preferably English, that meets the needs of the profession and the labour market.

Effective oral and written communication

  • G4 - To communicate with other people knowledge, procedures, results and ideas orally and in a written way. To participate in discussions about topics related to the activity of a technical informatics engineer.

Information literacy

  • G6 - To manage the acquisition, structuring, analysis and visualization of data and information of the field of the informatics engineering, and value in a critical way the results of this management.
  • CT4 - Capacity for managing the acquisition, the structuring, analysis and visualization of data and information in the field of specialisation, and for critically assessing the results of this management.
  • CTR4 - Capability to manage the acquisition, structuring, analysis and visualization of data and information in the area of informatics engineering, and critically assess the results of this effort.

Autonomous learning

  • G7 - To detect deficiencies in the own knowledge and overcome them through critical reflection and choosing the best actuation to extend this knowledge. Capacity for learning new methods and technologies, and versatility to adapt oneself to new situations.

Analisis y sintesis

  • CT7 - Capability to analyze and solve complex technical problems.

Basic

  • CB6 - Ability to apply the acquired knowledge and capacity for solving problems in new or unknown environments within broader (or multidisciplinary) contexts related to their area of study.
  • CB7 - Ability to integrate knowledge and handle the complexity of making judgments based on information which, being incomplete or limited, includes considerations on social and ethical responsibilities linked to the application of their knowledge and judgments.
  • CB8 - Capability to communicate their conclusions, and the knowledge and rationale underpinning these, to both skilled and unskilled public in a clear and unambiguous way.
  • CB9 - Possession of the learning skills that enable the students to continue studying in a way that will be mainly self-directed or autonomous.
  • CB1 - That students have demonstrated to possess and understand knowledge in an area of ??study that starts from the base of general secondary education, and is usually found at a level that, although supported by advanced textbooks, also includes some aspects that imply Knowledge from the vanguard of their field of study.
  • CB2 - That the students know how to apply their knowledge to their work or vocation in a professional way and possess the skills that are usually demonstrated through the elaboration and defense of arguments and problem solving within their area of ??study.
  • CB3 - That students have the ability to gather and interpret relevant data (usually within their area of ??study) to make judgments that include a reflection on relevant social, scientific or ethical issues.
  • CB4 - That the students can transmit information, ideas, problems and solutions to a specialized and non-specialized public.
  • CB5 - That the students have developed those learning skills necessary to undertake later studies with a high degree of autonomy
  • CB10 - Possess and understand knowledge that provides a basis or opportunity to be original in the development and/or application of ideas, often in a research context.

Transversals

  • CT1 - Entrepreneurship and innovation. Know and understand the organization of a company and the sciences that govern its activity; Have the ability to understand labor standards and the relationships between planning, industrial and commercial strategies, quality and profit.
  • CT2 - Sustainability and Social Commitment. To know and understand the complexity of economic and social phenomena typical of the welfare society; Be able to relate well-being to globalization and sustainability; Achieve skills to use in a balanced and compatible way the technique, the technology, the economy and the sustainability.
  • CT3 - Efficient oral and written communication. Communicate in an oral and written way with other people about the results of learning, thinking and decision making; Participate in debates on topics of the specialty itself.
  • CT4 - Teamwork. Be able to work as a member of an interdisciplinary team, either as a member or conducting management tasks, with the aim of contributing to develop projects with pragmatism and a sense of responsibility, taking commitments taking into account available resources.
  • CT5 - Solvent use of information resources. Manage the acquisition, structuring, analysis and visualization of data and information in the field of specialty and critically evaluate the results of such management.
  • CT6 - Autonomous Learning. Detect deficiencies in one's own knowledge and overcome them through critical reflection and the choice of the best action to extend this knowledge.
  • CT7 - Third language. Know a third language, preferably English, with an adequate oral and written level and in line with the needs of graduates.

Gender perspective

  • CT6 - An awareness and understanding of sexual and gender inequalities in society in relation to the field of the degree, and the incorporation of different needs and preferences due to sex and gender when designing solutions and solving problems.

Technical Competences

Common technical competencies

  • CT1 - To demonstrate knowledge and comprehension of essential facts, concepts, principles and theories related to informatics and their disciplines of reference.
    • CT1.1A - To demonstrate knowledge and comprehension about the fundamentals of computer usage and programming, about operating systems, databases and, in general, about computer programs applicable to the engineering.
    • CT1.1B - To demonstrate knowledge and comprehension about the fundamentals of computer usage and programming. Knowledge about the structure, operation and interconnection of computer systems, and about the fundamentals of its programming.
    • CT1.2B - To interpret, select and value concepts, theories, uses and technological developments related to computer science and its application derived from the needed fundamentals of mathematics, statistics and physics. Capacity to understand and dominate the physical and technological fundamentals of computer science: electromagnetism, waves, circuit theory, electronics and photonics and its application to solve engineering problems.
  • CT2 - To use properly theories, procedures and tools in the professional development of the informatics engineering in all its fields (specification, design, implementation, deployment and products evaluation) demonstrating the comprehension of the adopted compromises in the design decisions.
  • CT3 - To demonstrate knowledge and comprehension of the organizational, economic and legal context where her work is developed (proper knowledge about the company concept, the institutional and legal framework of the company and its organization and management)
    • CT3.6 - To demonstrate knowledge about the ethical dimension of the company: in general, the social and corporative responsibility and, concretely, the civil and professional responsibilities of the informatics engineer.
  • CT4 - To demonstrate knowledge and capacity to apply the basic algorithmic procedures of the computer science technologies to design solutions for problems, analysing the suitability and complexity of the algorithms.
    • CT4.1 - To identify the most adequate algorithmic solutions to solve medium difficulty problems.
    • CT4.2 - To reason about the correction and efficiency of an algorithmic solution.
  • CT5 - To analyse, design, build and maintain applications in a robust, secure and efficient way, choosing the most adequate paradigm and programming languages.
    • CT5.1 - To choose, combine and exploit different programming paradigms, at the moment of building software, taking into account criteria like ease of development, efficiency, portability and maintainability.
    • CT5.2 - To know, design and use efficiently the most adequate data types and data structures to solve a problem.
    • CT5.3 - To design, write, test, refine, document and maintain code in an high level programming language to solve programming problems applying algorithmic schemas and using data structures.
    • CT5.4 - To design the programs¿ architecture using techniques of object orientation, modularization and specification and implementation of abstract data types.
  • CT6 - To demonstrate knowledge and comprehension about the internal operation of a computer and about the operation of communications between computers.
  • CT7 - To evaluate and select hardware and software production platforms for executing applications and computer services.
  • CT8 - To plan, conceive, deploy and manage computer projects, services and systems in every field, to lead the start-up, the continuous improvement and to value the economical and social impact.
    • CT8.6 - To demonstrate the comprehension of the importance of the negotiation, effective working habits, leadership and communication skills in all the software development environments.

Technical competencies

  • CE1 - Skillfully use mathematical concepts and methods that underlie the problems of science and data engineering.
  • CE2 - To be able to program solutions to engineering problems: Design efficient algorithmic solutions to a given computational problem, implement them in the form of a robust, structured and maintainable program, and check the validity of the solution.
  • CE3 - Analyze complex phenomena through probability and statistics, and propose models of these types in specific situations. Formulate and solve mathematical optimization problems.
  • CE4 - Use current computer systems, including high performance systems, for the process of large volumes of data from the knowledge of its structure, operation and particularities.
  • CE5 - Design and apply techniques of signal processing, choosing between different technological tools, including those of Artificial vision, speech recognition and multimedia data processing.
  • CE6 - Build or use systems of processing and comprehension of written language, integrating it into other systems driven by the data. Design systems for searching textual or hypertextual information and analysis of social networks.
  • CE7 - Demonstrate knowledge and ability to apply the necessary tools for the storage, processing and access to data.
  • CE8 - Ability to choose and employ techniques of statistical modeling and data analysis, evaluating the quality of the models, validating and interpreting them.
  • CE9 - Ability to choose and employ a variety of automatic learning techniques and build systems that use them for decision making, even autonomously.
  • CE10 - Visualization of information to facilitate the exploration and analysis of data, including the choice of adequate representation of these and the use of dimensionality reduction techniques.
  • CE11 - Within the corporate context, understand the innovation process, be able to propose models and business plans based on data exploitation, analyze their feasibility and be able to communicate them convincingly.
  • CE12 - Apply the project management practices in the integral management of the data exploitation engineering project that the student must carry out in the areas of scope, time, economic and risks.
  • CE13 - (End-of-degree work) Plan and design and carry out projects of a professional nature in the field of data engineering, leading its implementation, continuous improvement and valuing its economic and social impact. Defend the project developed before a university court.

Especifics

  • CE1 - Develop efficient algorithms based on the knowledge and understanding of the computational complexity theory and considering the main data structures within the scope of data science
  • CE2 - Apply the fundamentals of data management and processing to a data science problem
  • CE3 - Apply data integration methods to solve data science problems in heterogeneous data environments
  • CE4 - Apply scalable storage and parallel data processing methods, including data streams, once the most appropriate methods for a data science problem have been identified
  • CE5 - Model, design, and implement complex data systems, including data visualization
  • CE6 - Design the Data Science process and apply scientific methodologies to obtain conclusions about populations and make decisions accordingly, from both structured and unstructured data and potentially stored in heterogeneous formats.
  • CE7 - Identify the limitations imposed by data quality in a data science problem and apply techniques to smooth their impact
  • CE8 - Extract information from structured and unstructured data by considering their multivariate nature.
  • CE9 - Apply appropriate methods for the analysis of non-traditional data formats, such as processes and graphs, within the scope of data science
  • CE10 - Identify machine learning and statistical modeling methods to use and apply them rigorously in order to solve a specific data science problem
  • CE11 - Analyze and extract knowledge from unstructured information using natural language processing techniques, text and image mining
  • CE12 - Apply data science in multidisciplinary projects to solve problems in new or poorly explored domains from a data science perspective that are economically viable, socially acceptable, and in accordance with current legislation
  • CE13 - Identify the main threats related to ethics and data privacy in a data science project (both in terms of data management and analysis) and develop and implement appropriate measures to mitigate these threats
  • CE14 - Execute, present and defend an original exercise carried out individually in front of an academic commission, consisting of an engineering project in the field of data science synthesizing the competences acquired in the studies

Technical Competences of each Specialization

Information systems specialization

  • CSI2 - To integrate solutions of Information and Communication Technologies, and business processes to satisfy the information needs of the organizations, allowing them to achieve their objectives effectively.
  • CSI3 - To determine the requirements of the information and communication systems of an organization, taking into account the aspects of security and compliance of the current normative and legislation.
  • CSI4 - To participate actively in the specification, design, implementation and maintenance of the information and communication systems.
  • CSI1 - To demonstrate comprehension and apply the principles and practices of the organization, in a way that they could link the technical and management communities of an organization, and participate actively in the user training.

Software engineering specialization

  • CES1 - To develop, maintain and evaluate software services and systems which satisfy all user requirements, which behave reliably and efficiently, with a reasonable development and maintenance and which satisfy the rules for quality applying the theories, principles, methods and practices of Software Engineering.
  • CES2 - To value the client needs and specify the software requirements to satisfy these needs, reconciling conflictive objectives through searching acceptable compromises, taking into account the limitations related to the cost, time, already developed systems and organizations.
  • CES3 - To identify and analyse problems; design, develop, implement, verify and document software solutions having an adequate knowledge about the current theories, models and techniques.

Information technology specialization

  • CTI1 - To define, plan and manage the installation of the ICT infrastructure of the organization.
  • CTI2 - To guarantee that the ICT systems of an organization operate adequately, are secure and adequately installed, documented, personalized, maintained, updated and substituted, and the people of the organization receive a correct ICT support.
  • CTI3 - To design solutions which integrate hardware, software and communication technologies (and capacity to develop specific solutions of systems software) for distributed systems and ubiquitous computation devices.
  • CTI4 - To use methodologies centred on the user and the organization to develop, evaluate and manage applications and systems based on the information technologies which ensure the accessibility, ergonomics and usability of the systems.

Computer engineering specialization

  • CEC1 - To design and build digital systems, including computers, systems based on microprocessors and communications systems.
  • CEC2 - To analyse and evaluate computer architectures including parallel and distributed platforms, and develop and optimize software for these platforms.
  • CEC3 - To develop and analyse hardware and software for embedded and/or very low consumption systems.
  • CEC4 - To design, deploy, administrate and manage computer networks, and manage the guarantee and security of computer systems.

Computer science specialization

  • CCO1 - To have an in-depth knowledge about the fundamental principles and computations models and be able to apply them to interpret, select, value, model and create new concepts, theories, uses and technological developments, related to informatics.
  • CCO2 - To develop effectively and efficiently the adequate algorithms and software to solve complex computation problems.
  • CCO3 - To develop computer solutions that, taking into account the execution environment and the computer architecture where they are executed, achieve the best performance.

Academic

  • CEA1 - Capability to understand the basic principles of the Multiagent Systems operation main techniques , and to know how to use them in the environment of an intelligent service or system.
  • CEA2 - Capability to understand the basic operation principles of Planning and Approximate Reasoning main techniques, and to know how to use in the environment of an intelligent system or service.
  • CEA3 - Capability to understand the basic operation principles of Machine Learning main techniques, and to know how to use on the environment of an intelligent system or service.
  • CEA4 - Capability to understand the basic operation principles of Computational Intelligence main techniques, and to know how to use in the environment of an intelligent system or service.
  • CEA5 - Capability to understand the basic operation principles of Natural Language Processing main techniques, and to know how to use in the environment of an intelligent system or service.
  • CEA6 - Capability to understand the basic operation principles of Computational Vision main techniques, and to know how to use in the environment of an intelligent system or service.
  • CEA7 - Capability to understand the problems, and the solutions to problems in the professional practice of Artificial Intelligence application in business and industry environment.
  • CEA8 - Capability to research in new techniques, methodologies, architectures, services or systems in the area of ??Artificial Intelligence.
  • CEA9 - Capability to understand Multiagent Systems advanced techniques, and to know how to design, implement and apply these techniques in the development of intelligent applications, services or systems.
  • CEA10 - Capability to understand advanced techniques of Human-Computer Interaction, and to know how to design, implement and apply these techniques in the development of intelligent applications, services or systems.
  • CEA11 - Capability to understand the advanced techniques of Computational Intelligence, and to know how to design, implement and apply these techniques in the development of intelligent applications, services or systems.
  • CEA12 - Capability to understand the advanced techniques of Knowledge Engineering, Machine Learning and Decision Support Systems, and to know how to design, implement and apply these techniques in the development of intelligent applications, services or systems.
  • CEA13 - Capability to understand advanced techniques of Modeling , Reasoning and Problem Solving, and to know how to design, implement and apply these techniques in the development of intelligent applications, services or systems.
  • CEA14 - Capability to understand the advanced techniques of Vision, Perception and Robotics, and to know how to design, implement and apply these techniques in the development of intelligent applications, services or systems.

Professional

  • CEP1 - Capability to solve the analysis of information needs from different organizations, identifying the uncertainty and variability sources.
  • CEP2 - Capability to solve the decision making problems from different organizations, integrating intelligent tools.
  • CEP3 - Capacity for applying Artificial Intelligence techniques in technological and industrial environments to improve quality and productivity.
  • CEP4 - Capability to design, write and report about computer science projects in the specific area of ??Artificial Intelligence.
  • CEP5 - Capability to design new tools and new techniques of Artificial Intelligence in professional practice.
  • CEP6 - Capability to assimilate and integrate the changing economic, social and technological environment to the objectives and procedures of informatic work in intelligent systems.
  • CEP7 - Capability to respect the legal rules and deontology in professional practice.
  • CEP8 - Capability to respect the surrounding environment and design and develop sustainable intelligent systems.

Direcció i gestió

  • CDG1 - Capability to integrate technologies, applications, services and systems of Informatics Engineering, in general and in broader and multicisciplinary contexts.
  • CDG2 - Capacity for strategic planning, development, direction, coordination, and technical and economic management in the areas of Informatics Engineering related to: systems, applications, services, networks, infrastructure or computer facilities and software development centers or factories, respecting the implementation of quality and environmental criteria in multidisciplinary working environments .
  • CDG3 - Capability to manage research, development and innovation projects in companies and technology centers, guaranteeing the safety of people and assets, the final quality of products and their homologation.

Especifics

  • CTE1 - Capability to model, design, define the architecture, implement, manage, operate, administrate and maintain applications, networks, systems, services and computer contents.
  • CTE2 - Capability to understand and know how to apply the operation and organization of Internet, technologies and protocols for next generation networks, component models, middleware and services.
  • CTE3 - Capability to secure, manage, audit and certify the quality of developments, processes, systems, services, applications and software products.
  • CTE4 - Capability to design, develop, manage and evaluate mechanisms of certification and safety guarantee in the management and access to information in a local or distributed processing.
  • CTE5 - Capability to analyze the information needs that arise in an environment and carry out all the stages in the process of building an information system.
  • CTE6 - Capability to design and evaluate operating systems and servers, and applications and systems based on distributed computing.
  • CTE7 - Capability to understand and to apply advanced knowledge of high performance computing and numerical or computational methods to engineering problems.
  • CTE8 - Capability to design and develop systems, applications and services in embedded and ubiquitous systems .
  • CTE9 - Capability to apply mathematical, statistical and artificial intelligence methods to model, design and develop applications, services, intelligent systems and knowledge-based systems.
  • CTE10 - Capability to use and develop methodologies, methods, techniques, special-purpose programs, rules and standards for computer graphics.
  • CTE11 - Capability to conceptualize, design, develop and evaluate human-computer interaction of products, systems, applications and informatic services.
  • CTE12 - Capability to create and exploit virtual environments, and to the create, manageme and distribute of multimedia content.

Computer graphics and virtual reality

  • CEE1.1 - Capability to understand and know how to apply current and future technologies for the design and evaluation of interactive graphic applications in three dimensions, either when priorizing image quality or when priorizing interactivity and speed, and to understand the associated commitments and the reasons that cause them.
  • CEE1.2 - Capability to understand and know how to apply current and future technologies for the evaluation, implementation and operation of virtual and / or increased reality environments, and 3D user interfaces based on devices for natural interaction.
  • CEE1.3 - Ability to integrate the technologies mentioned in CEE1.2 and CEE1.1 skills with other digital processing information technologies to build new applications as well as make significant contributions in multidisciplinary teams using computer graphics.

Computer networks and distributed systems

  • CEE2.1 - Capability to understand models, problems and algorithms related to distributed systems, and to design and evaluate algorithms and systems that process the distribution problems and provide distributed services.
  • CEE2.2 - Capability to understand models, problems and algorithms related to computer networks and to design and evaluate algorithms, protocols and systems that process the complexity of computer communications networks.
  • CEE2.3 - Capability to understand models, problems and mathematical tools to analyze, design and evaluate computer networks and distributed systems.

Advanced computing

  • CEE3.1 - Capability to identify computational barriers and to analyze the complexity of computational problems in different areas of science and technology as well as to represent high complexity problems in mathematical structures which can be treated effectively with algorithmic schemes.
  • CEE3.2 - Capability to use a wide and varied spectrum of algorithmic resources to solve high difficulty algorithmic problems.
  • CEE3.3 - Capability to understand the computational requirements of problems from non-informatics disciplines and to make significant contributions in multidisciplinary teams that use computing.

High performance computing

  • CEE4.1 - Capability to analyze, evaluate and design computers and to propose new techniques for improvement in its architecture.
  • CEE4.2 - Capability to analyze, evaluate, design and optimize software considering the architecture and to propose new optimization techniques.
  • CEE4.3 - Capability to analyze, evaluate, design and manage system software in supercomputing environments.

Service engineering

  • CEE5.1 - Capability to participate in improvement projects or to create service systems, providing in particular: a) innovation and research proposals based on new uses and developments of information technologies, b) application of the most appropriate software engineering and databases principles when developing information systems, c) definition, installation and management of infrastructure / platform necessary for the efficient running of service systems.
  • CEE5.2 - Capability to apply obtained knowledge in any kind of service systems, being familiar with some of them, and thorough knowledge of eCommerce systems and their extensions (eBusiness, eOrganization, eGovernment, etc.).
  • CEE5.3 - Capability to work in interdisciplinary engineering services teams and, provided the necessary domain experience, capability to work autonomously in specific service systems.

Specific

  • CEC1 - Ability to apply scientific methodologies in the study and analysis of phenomena and systems in any field of Information Technology as well as in the conception, design and implementation of innovative and original computing solutions.
  • CEC2 - Capacity for mathematical modelling, calculation and experimental design in engineering technology centres and business, particularly in research and innovation in all areas of Computer Science.
  • CEC3 - Ability to apply innovative solutions and make progress in the knowledge that exploit the new paradigms of Informatics, particularly in distributed environments.

Generic Technical Competences

Generic

  • CG1 - Identify and apply the most appropriate data management methods and processes to manage the data life cycle, considering both structured and unstructured data
  • CG2 - Identify and apply methods of data analysis, knowledge extraction and visualization for data collected in disparate formats
  • CG3 - Define, design and implement complex systems that cover all phases in data science projects
  • CG4 - Design and implement data science projects in specific domains and in an innovative way
  • CG5 - To be able to draw on fundamental knowledge and sound work methodologies acquired during the studies to adapt to the new technological scenarios of the future.
  • CG6 - Capacity for general management, technical management and research projects management, development and innovation in companies and technology centers in the area of Computer Science.
  • CG7 - Capacity for implementation, direction and management of computer manufacturing processes, with guarantee of safety for people and assets, the final quality of the products and their homologation.
  • CG8 - Capability to apply the acquired knowledge and to solve problems in new or unfamiliar environments inside broad and multidisciplinary contexts, being able to integrate this knowledge.
  • CG9 - Capacity to understand and apply ethical responsibility, law and professional deontology of the activity of the Informatics Engineering profession.
  • CG10 - Capacity to apply economics, human resources and projects management principles, as well as legislation, regulation and standardization of Informatics.

Objectives

  1. To design a class of data with a clear independence between specification and implementation. To justify why an object of the class can only be created, consulted or modified using the operations in the class specification.
    Related competences: CT5.4, CT5.3, CT1.1B, CT1.1A,
  2. To solve any exercise which requires the application of a simple algorithm to a vector of objects of a class of data in C++.
    Related competences: CT4.1, CT4.2, CT5.2, CT5.4, CT5.3,
  3. Given an implementation for a simple class of data, make improvements in its representation and its operations.
    Related competences: CT5.2, CT5.4, CT5.1, CT5.3, CT1.2B,
  4. To explain the main stages of modular design.
    Related competences: CT5.4, CT5.1, CT5.3, CT1.1B, CT1.1A,
  5. To identify in a textual statement of a problem data abstractions that may be represented by classes of data which could be used to solve the problem. To check whether any of the abstractions identified has been previously detected, in order to reuse the corresponding class of data.
    Related competences: CT5.2, CT5.4, CT5.1, CT5.3,
  6. To individually design a modular program in C++ from the data abstractions identified by analysing the statement of a problem. To modify or add some functionality to a given modular program written in C++.
    Related competences: CT3.6, CT4.1, CT4.2, CT5.2, CT5.4, CT5.3, CT1.2B, CT1.1A,
  7. To implement a modular program in C++ elegantly and in such a way that other programmers can understand what it does and modify it. To write documentation that facilitates the use of a modular program written in C++ by other programmers.
    Related competences: CT8.6, CT3.6, CT5.4, CT5.3,
  8. Prepare a C++ program which uses simple data types and C++ classes (some of the predefined and others defined by the student) to be executed. Thw student should be able to do this in two ways: 1) compiling and linking the program using the g++ command; and 2) writing a makefile file, and using it to compile and link the program.
    Related competences: CT1.1B, CT1.1A,
  9. To design in teams a modular program in C++ and/or a set of cases (i.e. a set of examples of correct input and corresponding output) to test the full functionality of the program. To debug this program systematically, so that small implementation errors are removed in a reasonable period of time.
    Related competences: CT8.6, G5.1, CT3.6, CT5.3,
  10. To know the data types typically used to represent and manage linear data structures and their specification. To design iterative and recursive algorithms for solving search and traversal problems on stacks, queues and lists, using the operations of the corresponding data type and iterators (when appropriated).
    Related competences: CT4.1, CT4.2, CT5.2, CT1.1A,
  11. To know data types used to represent and manage tree data structures and their specification. To design recursive algorithms for solving search and traversal problems about binary, n-ary and general trees, using the operations of the corresponding data type.
    Related competences: CT4.1, CT4.2, CT5.2, CT1.1A,
  12. To describe the main steps in the design of iterative algorithms. To justify the correctness of relatively simple iterative algorithms.
    Related competences: CT3.6, CT4.2, CT5.3, CT1.1A,
  13. To describe the main steps in the design of recursive algorithms. To justify the correctness of relatively simple recursive algorithms.
    Related competences: CT3.6, CT4.2, CT5.3, CT1.1A,
  14. To know what a generalization of a function is, and to be able to explain the difference between specification gneralisations and efficiency generalisations. To know the different types of specification generalizations and the different types of efiiciency generalisations.
    Related competences: CT4.2, CT5.3, CT1.1A,
  15. Given a simple recursive algorithm, to determine whether there is a straightforward way to obtain an equivalent iterative algorithm, and write it if there exists such a straightforward transformation.
    Related competences: CT4.2, CT5.3, CT1.1A,
  16. To distinguish whether the cost of a given iterative or recursive simple algorithm which works on vectors, stacks, queues, lists or trees is linear or if it is quadratic (assuming that the cost is of one of these two types).
    Related competences: CT4.1, CT4.2, CT5.2, CT1.1A,
  17. To determine if the efficiency of a given simple recursive algorithm can be improved and, if it is possible, to design a more efficient recursive algorithm that solves the same problem using efficiency generalizations.
    Related competences: CT4.1, CT4.2, CT5.2, CT1.1A,
  18. To determine if the efficiency of a given simple iterative algorithm can be improved and, if it is possible, to design a more efficient iterative algorithm that solves the same problem.
    Related competences: CT4.1, CT4.2, CT5.2, CT1.1A,
  19. To implement a data structure with specific requirements for its operations and/or the efficiency of such operations, using recursive data types (linked data structures).
    Related competences: CT4.1, CT4.2, CT5.2, CT5.4, CT1.1A,
  20. To design iterative and recursive algorithms for solving search and traversal problems in linked data structures by using directly their representation.
    Related competences: CT4.1, CT4.2, CT5.2, CT5.4, CT1.1A,
  21. To distinguish the roles of user, specifier and implementer of data classes. To know the main components of the specification of a class of data. To know the main components of the implementation of a class of data.
    Related competences: CT8.6, CT5.4, CT1.1B, CT1.1A,

Contents

  1. Linear data structures
    Stacks, queues, lists, maps and sets: specification and use (search and traversal operations). Iterators: definition and use.
  2. Tree data structures
    Binary trees.
  3. Iterative program correctness
    Loop invariants. Justification of the correctness of iterative algorithms.
  4. Recursive programming and correctness of recursive algorithms
    Inductive design of recursive algorithms. Justification of the correctness of recursive algorithms. Generalisation of a function . Specification immersions by weakening the postcondition and strengthening the precondition. Relationship between tail-recursive algorithms and iterative algorithms.
  5. Efficiency enhancements for recursive and iterative programs
    Detection of repeated calculations in recursive and iterative programs. Efficiency generalisations: new data (input parameters) and/or results (return values or output parameters) in recursive operations to improve efficiency. New local variables that use their previous values in iterative operations to improve efficiency.
  6. Modular design and object-oriented design
    Abstraction and the need for abstraction. Functional and data decomposition. Modules. Information hiding. Encapsulation. Modular design phases: difference between specification and implementation. Types of modules and their use. Libraries.

    Basic principles of object-oriented design: classes and objects; fields and methods.

    Implementing modular designs in C++. Separate compilation and linking. Debugging, testing and documentation of modular programs.
  7. Recursive data types
    Introduction to the use of recursive data types. Pointer type constructor and dynamic memory management. Implementation of linked data structures by means of recursive data types. Iterative and recursive algorithms for solving search and traversal problems in linked data structures by directly accessing the representation based on nodes and node pointers.

Activities

Activity Evaluation act


C++ review exercises.

Link to PRO1 contents.
  • Laboratory: Laboratory session week 1
Objectives: 2 8
Contents:
Theory
0h
Problems
0h
Laboratory
3h
Guided learning
0h
Autonomous learning
3h

Linear data structures.

Development of the corresponding topic and laboratory exercises.
  • Theory: Theory session week 3.
  • Laboratory: Laboratory session week 6 and first hour of laboratory session week 7
Objectives: 10
Contents:
Theory
2h
Problems
0h
Laboratory
6h
Guided learning
0h
Autonomous learning
9h

Recursive programming

Development of the corresponding topic.
  • Theory: Theory session week 6 and first hour of theory session week 7.
Objectives: 14 15 13
Contents:
Theory
3h
Problems
0h
Laboratory
0h
Guided learning
0h
Autonomous learning
3h

Tree data structures.

Development of the corresponding topic and laboratory exercises.
  • Theory: Theory session week 4.
  • Laboratory: Last two hours of laboratory session in week 7.
Objectives: 11
Contents:
Theory
2h
Problems
0h
Laboratory
9h
Guided learning
0h
Autonomous learning
16h

Iterative program correctness

Development of the corresponding topic.
  • Theory: Theory session week 5.
Objectives: 12
Contents:
Theory
2h
Problems
0h
Laboratory
0h
Guided learning
0h
Autonomous learning
2h

Efficiency enhancements for recursive and iterative programs.

Development of the corresponding topic.
  • Theory: Second hour of theory session week 7 and theory session week 8.
Objectives: 12 14 15 16 17 13 18
Contents:
Theory
3h
Problems
0h
Laboratory
9h
Guided learning
0h
Autonomous learning
12h

Introduction to modular design and object-oriented design.

Development of the corresponding topic.
  • Theory: Theory sessions weeks 1 and 2
Objectives: 21 1 2 4
Contents:
Theory
4h
Problems
0h
Laboratory
0h
Guided learning
0h
Autonomous learning
4h

Specification and use of classes of objects in C++.

Exercises from the corresponding topic.
  • Laboratory: Laboratory sessions weeks 2 and 3
Objectives: 21 1 2
Contents:
Theory
0h
Problems
0h
Laboratory
3h
Guided learning
0h
Autonomous learning
6h

Implementing classes of objects in C++.

Exercises from the corresponding topic.
  • Laboratory: Laboratory session week 4
Objectives: 21 1 3
Contents:
Theory
0h
Problems
0h
Laboratory
3h
Guided learning
0h
Autonomous learning
3h

Supervision of practical

Supervision of the design and implementation of the practical.
  • Laboratory: Laboratory session week 11.
Objectives: 3 5 6 7 8 10 11 16 17 21 1
Contents:
Theory
0h
Problems
0h
Laboratory
3h
Guided learning
0h
Autonomous learning
6h

Recursive data types.

Development of the corresponding topic.
  • Theory: Theory sessions weeks 10, 11, 12 and 13
  • Laboratory: Laboratory sessions weeks 13 and 14
Objectives: 16 17 19 20 1 3 18
Contents:
Theory
7.5h
Problems
0h
Laboratory
9h
Guided learning
0h
Autonomous learning
16h

Review of theory and exam problems.

Questions can be asked about the topics covered in theory classes.
  • Theory: Theory session week 14.
  • Autonomous learning: Solve past exam problems

Theory
2h
Problems
0h
Laboratory
0h
Guided learning
0h
Autonomous learning
2h

EX_SIMUL1

Mock exam for midterm exam 1
Objectives: 10 11 16 17 19 20 2 3 5 6 7 8 18
Week: 8 (Outside class hours)
Type: assigment
Theory
0h
Problems
0h
Laboratory
0h
Guided learning
2h
Autonomous learning
2h

EX_PAR1_TP

Mid-term theory/problems exam.
Objectives: 10 11 16 17 19 20 2 3 5 6 7 8 18
Week: 9 (Outside class hours)
Type: theory exam
Theory
2h
Problems
0h
Laboratory
0h
Guided learning
0h
Autonomous learning
5h

CODI_DOC_PRAC1

Delivery of the programming project code and documentation.
Objectives: 10 11 12 14 16 17 21 1 5 6 7 8 9 13 18
Week: 12 (Outside class hours)
Type: assigment
Theory
0h
Problems
0h
Laboratory
0h
Guided learning
0h
Autonomous learning
10h

EX_SIMUL2

Mock exam for midterm exam 2
Objectives: 10 11 16 17 19 20 2 3 5 6 7 8 18
Week: 13 (Outside class hours)
Type: assigment
Theory
0h
Problems
0h
Laboratory
0h
Guided learning
2.5h
Autonomous learning
2.5h

EX_PAR2_TP

Final theory/problems exam.
Objectives: 10 11 16 17 19 20 2 3 5 6 7 8 18
Week: 15 (Outside class hours)
Type: theory exam
Theory
2.5h
Problems
0h
Laboratory
0h
Guided learning
0h
Autonomous learning
6.5h

Teaching methodology

Topics will be explained in a practical way by using many examples.

Theory classes introduce knowledge, techniques and concepts that will be used in laboratory sessions. They also include the presentation and discussion of the solutions of a set of problems.

The two-hour theory classes and the three-hour laboratory sessions will take place weekly.

The programming project integrates knowledge and skills of the entire course, except maybe for the topic (recursive data types) which will be assessed in the final theory exam.

Evaluation methodology

The technical competence mark (NCTEC) is calculated as follows:

NCTEC = 0.3*EXAM1 + 0.3*EXAM2 + 0.25*PRAC + 0.15*DELIVERY

where

* EXAM1 and EXAM2 are the marks of the mid-term and final theory exams

* PRAC is the mark of the programming project; it may have an automatic part, derived from code testing, and a manual part.

* DELIVERY is the mark arising from the deliveries from students of solutions to exercises requested over the course.

Nevertheless, NCTEC will be NP if the weight of the assessment activities with an NP mark is greater than or equal to 70%.

The assessment of the generic competence Teamwork is obtained from some of the deliveries carried out along the course (DELIVERY) which will be done in teams.

Bibliography

Basic:

Complementary:

Web links

Previous capacities

Students are expected to have been trained in imperative programming techniques based on:
- basic instructions (assignment, alternative and iteration)
- actions and functions, parameter passing and recurrence
- vectors, tuples and sequences
- sequential search and traversal schemes
- basic algorithms (binary search, vector sorting, matrix arithmetics).

They are also expected to know how to use at least one imperative language, preferably C++, and they should have some
experience in implementing of C++ programs in the Linux environment.

Furthermore, they should be able to assimilate information from a statement, discuss the correctness of an algorithm and compare algorithmic solutions.