traduccion couse outlines johanna ponce

UNIVERSIDAD DE ORIENTE COURSE OUTLINE

CAMPUS: ANZOATEGUI SCHOOL: ENGINEERING AND APPLIED SCIENCES

COURSE: PROGRAMMING I

PROGRAM: SYSTEM ENGINEERING

HOURS\WK CREDITS SEMESTER CODE PREREQUISITIES

3 LECTURE 3 LAB 4 III 722314 081824

SUMMARY OF PREVIOUS KNOWLEDGE: Basic math, derivatives, integrals, facility to resolve problems applying logic.

GENERL OVERVIEW: The goal of this course is provide basic knowledge related with the computer structure and organization. Hardware and software concepts. Explain the structure and components of a program. Develop algorithms to resolve problems and code in a high level programing language as C Language.

CONTENT: (Units and topics) UNIT I: Computer organization. CPU organization. Memory organization. Input Output interfaces. Buses. UNIT II: Operatives systems. Operative systems concepts. Commands and syntax. UNIT III: Introduction to programming. Processing algorithms. Pseudo code. Flow Diagrams. UNIT IV: Introduction to high level programming language. C Language. Basic program structure in C Language. Syntax rules. Data Types. Variables and Constants. Input and Output functions. UNIT V: Operators and operands. Arithmetic operators. Assignment operator. Logic operator. Precedence. UNIT VI: Simple and complex control sentences. UNIT VII: Complex data types. Single dimensional and multidimensional Arrays. UNIT VIII: Storage Classes. UNIT IX: Pointers. UNIT X: Procedures and functions. UNIT XI: Structure and Unions. UNIT XII: File Management.

REFERENCE: 1. Cabrera, Rene. Programming I Guide: C Language. Universidad de Oriente. 2. Ritchie, Dennis – Kernigham. Programming Language in C. Prentice Hall. 1991. Mexico. 3. Deitel, H – Deitel, P. C/C++: How to Program. Prentice Hall. 1994. Mexico

UNIVERSIDAD DE ORIENTE CAMPUS ANZOATEGUI

COURSE OUTLINE

COURSE TITLE: OBJECT ORIENTED PROGRAMMING WORKSHOP

SCHOOL ENGINEERING AND APPLIED SCIENCES

DEPARTMENT SYSTEMS AND COMPUTING

CODE 072-2111

PREREQUISITIES 072-1162

CREDITS 1 CREDIT

SEMESTER III

HOURS\WK 3

TOTAL SEMESTER HOURS VALIDATION

LECTURE HOURS 0

LAB HOURS 3

ORIGINATED BY

SUMMARY OF PREVIOUS KNOWLEDGE

Fundamentals of computer organization. Algorithms: Definition, design and implementation. Programming fundamentals: Overview of the basics of programming

and object oriented design principles.

MAIN OBJECTIVE

Develop software with a high level programming language and object oriented programing concepts.

COURSE DESCRIPTION

Work in an integrated development environment. Classes and objects. Input output standards. Control structure. Heritage. Uses of APIs. Object oriented design. Software

Engineering.

REFERENCE

1. Budd, T. 2001. Introduction to object Orientes Programming. 3rd Edition. Addison Wesley.

2. Koffman E. – Friedman F. 2000. Problem Solving, Abstraction, and Design in C++; Visuak C++ Edition. Addison Weslwy.

3. Gamma, E – Helm, R. – Johnson, R – Vlissides, J. 1995. Design Patterns, Addison Wesley.

4. Stroustrup, B. 1993. The C++ Programming Language. 2nd Edition. Addison Wesley.


COURSE OUTLINE

COURSE TITLE: OBJECTS AND DATA ABSTRACTION WORKSHOP



CODE 072-2131

PREREQUISITIES 072-2103, 0722111

CREDITS 1 CREDIT

SEMESTER IV

HOURS\WK 3


LECTURE HOURS 0

LAB HOURS 3

ORIGINATED BY

SUMMARY OF PREVIOUS KNOWLEDGE

Introduction to the object oriented programming. Use of object oriented programming language. Algorithms. Solving problems strategies.

MAIN OBJECTIVE

Design software using abstracts data structure based on the fundamentals of object oriented programming languages.

COURSE DESCRIPTION

Practice 1: Dynamic memory allocation. Practice 2: Abstract classes. Practice 3: Polymorphism. Practice 4: Overloading. Practice 5: Templates. Practice 6: Recursivity. Practice 7: Data abstraction and modularity. Practice 8: Fundamentals algorithms. Practice 9: Software testing. Practice 10: Software Engineering

REFERENCE

1. CARRANO F. PRICHARD J. Data Abstraction and Problem Solving with C++: Walls and Mirrors. 3rd Edition. Addison Wesley. 2001

2. SEDGEWICK R. Algorithms in C++. Addison Wesley. 2001. 3. MAIN M and SAVIKTCH W. Data Structures ans Others Objects Using C++. 2nd Edition.

Addison Wesley. 2000. 4. MEYER B. Buildig object oriented software. 2nd Edition. Prentice Hall. 1998.

UNIVERSIDAD DE ORIENTE

CAMPUS ANZOATEGUI COURSE OUTLINE

COURSE TITLE: OBJECTS AND DATA ABSTRACTION



CODE 072-2123


CREDITS 3 CREDIT

SEMESTER IV

HOURS\WK 4

TOTAL SEMESTER HOURS VALIDATION 2004

LECTURE HOURS 2

LAB HOURS 2

ORIGINATED BY

SUMMARY OF PREVIOUS KNOWLEDGE Introduction to the object oriented programming. Use of object oriented

programming language. Algorithms. Solving problems strategies.

MAIN OBJECTIVE Develop software using abstracts data structure based on the fundamentals of object

oriented programming languages.

COURSE DESCRIPTION - Review of programming fundamentals concepts and object-oriented design. Review

of the general aspects of the algorithms design. - Polymorphism: Abstract classes. Polymorphism uses. Polymorphism advantages. - Design and implementation algorithms classic techniques based on the object-

oriented design. - Abstraction and data encapsulation through fundamentals data structures:

Introduction to data structure fundamentals and its relation with the algorithms design.

- Introduction to basic algorithms analysis. - Algorithms design techniques to develop IT projects. - Recursivity: Design techniques base on recursivity. Recursivity uses. Introduction to

Trees and graphs. - Software Engineering: Develop a mid size software using the algorithms efficiently.

REFERENCE

1. CARRANO F AND PRICHARD J. Data Abstraction ans problem solving with C++: Walls and Mirors. 3rd Edition. Addison Wesley. 2001.

2. SEDGEWICK R. Algorithms in C++. Addison Wesley. 2001. 3. MAIN M and SAVIKTCH W. Data Structures ans Others Objects Using C++. 2nd Edition.

Addison Wesley. 2000. 4. MEYER B. Buildig object oriented software. 2nd Edition. Prentice Hall. 1998.


COURSE OUTLINE

COURSE TITLE: PROGRAMMING LANGUAGES WORKSHOP



CODE 072-3381

PREREQUISITIES N\A

CREDITS 1 CREDIT

SEMESTER VI

HOURS\WK 3


LECTURE HOURS 0

LAB HOURS 3

ORIGINATED BY

SUMMARY OF PREVIOUS KNOWLEDGE Handling of concepts and structures: Polymorphism, abstraction and encapsulation

trough fundamental data structure. Recusivity. Introduction to trees and graphs models.

MAIN OBJECTIVE Develop software using programming languages applying deferment paradigms to

implement solutions to fundamental problems.

COURSE DESCRIPTION - Object-oriented programming - Imperative programming - Functional programming - Logic Programming - Lexical analysis - Syntactic analysis

REFERENCE

1. WATT, D. Programming languages: Concepts and paradigms. Prentice Hall. 1993 2. ZELKOWITZ, M; Terrence W. Pratt. Programming Languages: Design and

Implementation. 4/e. USA. Prentice Hall. 2001 3. CALEB, C. Object-oriented Programming with C++ and Smalltalk. 1/e. Prentice Hall.

1998 4. KALIN, M. Object-oriented Programming in JAVA. 1/e. Prentice Hall. 2001 5. KRZYSZTOF, A. From Logic Programming to prolog. 1/e. Amsterdan. Prentice Hall.

1996. 6. GRAHAM, P. ANSI Common LISP. 1/e. Prentice Hall. 1996. 7. KLEIMAN, S; Devang Shah y Bart Smaalders. Programming with Threads. 1/e. Prentice

Hall. 1996



COURSE TITLE: PROGRAMMING LANGUAGES



CODE 072-3373

PREREQUISITIES N/A

CREDITS 3 CREDIT

SEMESTER VI

HOURS\WK 3


LECTURE HOURS 3

LAB HOURS 0

ORIGINATED BY


trough fundamental data structure. Recusivity. Introduction to trees and graphs models.

MAIN OBJECTIVE Apply different paradigms that guide the languages programming building and the

implementation aspect that have to be considered to elaborate software.

COURSE DESCRIPTION - Introduction to programming languages. - Virtual Machines - Object-oriented paradigm - Imperative Paradigm - Functional Paradigm - Functional Paradigm - Logical Paradigm - Introduction to languages translation

REFERENCE

1. WATT, D. Programming languages: Concepts and paradigms. Prentice Hall. 1993 2. ZELKOWITZ, M; Terrence W. Pratt. Programming Languages: Design and

Implementation. 4/e. USA. Prentice Hall. 2001 3. CALEB, C. Object-oriented Programming with C++ and Smalltalk. 1/e. Prentice Hall.

1998 4. KALIN, M. Object-oriented Programming in JAVA. 1/e. Prentice Hall. 2001 5. KRZYSZTOF, A. From Logic Programming to prolog. 1/e. Amsterdan. Prentice Hall.

1996. 6. GRAHAM, P. ANSI Common LISP. 1/e. Prentice Hall. 1996. 7. KLEIMAN, S; Devang Shah y Bart Smaalders. Programming with Threads. 1/e. Prentice

Hall. 1996


COURSE OUTLINE

COURSE TITLE: DATA STRUCTURES



CODE 072-3123


CREDITS 3 CREDIT

SEMESTER V

HOURS\WK 4


LECTURE HOURS 2

LAB HOURS 2

ORIGINATED BY

SUMMARY OF PREVIOUS KNOWLEDGE Handling concepts and structures: Polymorphism, Abstraction and data encapsulation

trough fundamental data structures. Recursivity.

MAIN OBJECTIVE Develop fundamental data structures to represent different types of information trough the description of data in memory, identifying advantages and disadvantages of its use in function to algorithms related to each of them using a object-oriented programming language.

COURSE DESCRIPTION - Data representation in memory. Management of persistent storage. - Fundamental data structures: Stacks, queues and priority queue. - Linked data structures: Linked lists. Doubly linked lists. - Hashing. - Graphs: Matrix representation of graphs. Representation trough adjacency list. Algorithms

for basics operations. - Trees: Binary trees. Binary search tree. AVL Trees. 2-3 Trees. B Trees. Algorithms for basic

operations. - Implementation strategies for graphs ad trees. Performance considerations for different data

structure.

- Strategies for correct data structure selection based on the information that will be shown. REFERENCE

1. WEISS M. Data structure and Problem Solving Using C++. 2nd Edition. Addison Wesley. 1999 2. STANDISH, T. Data Structures, Algorithms & Software Principles in C. 1st Edition. Addison

Wesley. 1994 3. WOOD, D. New and Modern Introduction to Data Structures – Data Structures, Algorithms

and Performance. Addison Wesley. 1993. 4. CORMEN T,. LEUSERSON C. & RIVEST D. Introduction to Algorithms. MIT Press, Cambridge

1990

5. WIRTH, N. Algorithms + Data Structure = Programs, Castillo Editions. 1996


COURSE OUTLINE

COURSE TITLE: DATA STRUCTURE WORKSHOP



CODE 072-3131


CREDITS 1 CREDIT

SEMESTER V

HOURS\WK 3


LECTURE HOURS 0

LAB HOURS 3

ORIGINATED BY


trough fundamental data structure. Recusivity.

MAIN OBJECTIVE Software design using fundamental abstracts data structures based on object-

oriented programming.

COURSE DESCRIPTION

- Practice 1: Memory handling. - Practice 2:Abstract data type. - Practice 3: Stacks and queues. - Practice 4:Linked data structures. - Practice 5: Hashing. - Practice 6: Graphs. - Practice 7: Binary graphs. - Practice 8: AVL Tress. - Practice 9: 2-3 Tress. - Practice 10: B Trees.

REFERENCE

1. WEISS M. Data structure and Problem Solving Using C++. 2nd Edition. Addison Wesley. 1999

2. STANDISH, T. Data Structures, Algorithms & Software Principles in C. 1st Edition. Addison Wesley. 1994

3. WOOD, D. New and Modern Introduction to Data Structures – Data Structures, Algorithms and Performance. Addison Wesley. 1993.

4. WIRTH, N. Algorithms + Data Structure = Programs, Castillo Editions. 1996



COURSE TITLE: ALGORITHMS ANALYSIS AND DESIGN WORKSHOP



CODE 072-3161


CREDITS 1 CREDIT

SEMESTER VI

HOURS\WK 3


LECTURE HOURS 0

LAB HOURS 3

ORIGINATED BY

SUMMARY OF PREVIOUS KNOWLEDGE Data Structure Fundamentals. Linked data structure. Graphs. Trees. Implementation Strategies of graphs and tress.

MAIN OBJECTIVE Develop software; focus on solving complex computer problems trough different strategies to improve the solution efficiency.

COURSE DESCRIPTION - Practice 1: Greedy Method - Practice 2: Divide and Conquer - Practice 3: Backtracking - Practice 4: Branch and Bound - Practice 5: First search in amplitude - Practice 6: Depth first search - Practice 7: Algorithms to find the shortest path (Dijkstra’s algorithm, Floyd’s algorithm) - Practice 8: Transitive closure - Practice 9: Algorithms to find minimum spanning tree (Prim’s algorithm, Kruskal’s algorithm) - Practice 10: Topological sorting

- Practice 11: Cryptographic algorithms. REFERENCE

1. HOROWITZ E., SAHNIS S. AND RAJASEKARAN S. Computer algorithms/ C++. Computer Science Press. 1996

2. TEL, G. Topic in distributed Algorithms. Cambridge University. 1991 3. CORMEN T, LEUSERSON C & RIVEST D. Introduction to algorithms. MIT press. 1990 4. SEDGEWICK, R. Algorithms. Second Edition. Addison Wesley. 2001 5. BRASSARD, G & BRATLEY, P. Algorithms fundamentals. Prentice Hall. 1990 6. MEHLHORN, K. Data Structures and Algorithms. Vol 1-3. Springer-Verlag. 2000

7. AHO A, HOPCROFT J & ULLMAN J. The design and analysis of computer algorithms, Addison-Wesley. 1999



COURSE TITLE: DATABASE SYSTEMS



CODE 072-3713


CREDITS 3 CREDIT

SEMESTER VI

HOURS\WK 3


LECTURE HOURS 3

LAB HOURS 0

ORIGINATED BY

SUMMARY OF PREVIOUS KNOWLEDGE Handling of fundamental structures: Graphs, Trees. Strategies to choose the correct data structure depending on the information that will be shown

MAIN OBJECTIVE Administration and design of database systems, trough the database concepts, data dictionary and SQL language, database models techniques, organization, administration and control.

COURSE DESCRIPTION - Database Systems: History of database systems. Database systems components.

DBMS Functions. Database architecture. Data Independence. - Data Model: General Concepts. Conceptual Model. Object-Oriented Model. Relational

data model. - Relational Database: Convert a conceptual data model to a relational data model.

Entity and Referential Integrity. Relational algebra. Relational Calculus. - Database query Languages. General overview of database languages. Structure Query

Language (SQL). Query optimization. - Relational database design. Database Design. Functional dependency. Normal

Forms(Database Normalization). Multivalued dependencies. - Transactions processing. Transactions. Fail Recovery. Concurrency control.

REFERENCE 1. ELMASRI R. & NAVATHE S. Database Systems – Fundamental concepts. 3rd Edition.

Addison Wesley. 2001 2. DATE C. Introduction to database systems. 7th Edition. Prentice Hall. 2001 3. Hansen G & Hansen J. Administration and database design. 2nd Edition. Prentice Hall.

1997.



COURSE TITLE: DATABASE SYSTEMS WORKSHOP



CODE 072-3721


CREDITS 1 CREDIT

SEMESTER VI

HOURS\WK 3


LECTURE HOURS 0

LAB HOURS 3

ORIGINATED BY

SUMMARY OF PREVIOUS KNOWLEDGE Handling of fundamental structures: Graphs, Trees. Strategies to choose the correct data structure depending on the information that will be shown

MAIN OBJECTIVE Build database systems, using fundamental data structure based on the information managment trough different data models.

COURSE DESCRIPTION Practice 1: Work with Database Management System (DBMS). Practice 2: Data Definition. Practice 3: Data Manipulation. Practice 4: Query optimization. Practice 5: Views. Practice 6: Security management. Practice 7: Transactions processing. Practice 8: Backup and Recovery. Practice 9: Develop software interacting with database systems Practice 10: Database Replication.

REFERENCE 1. ELMASRI R. & NAVATHE S. Database Systems – Fundamental concepts. 3rd Edition.

Addison Wesley. 2001 2. DATE C. Introduction to database systems. 7th Edition. Prentice Hall. 2001 3. Hansen G & Hansen J. Administration and database design. 2nd Edition. Prentice Hall.

1997.


COURSE OUTLINE

COURSE TITLE: ALGORITHMS ANALYSIS AND DESIGN



CODE 072-3143


CREDITS 3 CREDIT

SEMESTER VI

HOURS\WK 3


LECTURE HOURS 3

LAB HOURS 0

ORIGINATED BY

SUMMARY OF PREVIOUS KNOWLEDGE Data Structure Fundamentals. Linked data structure. Graphs. Trees. Implementation Strategies of graphs and tress

MAIN OBJECTIVE Analyze and design algorithms, focus on math theory and practical efficiency considerations to develop optimal algorithms.

COURSE DESCRIPTION - Demonstration techniques. - Basic algorithms analysis: Asymptotic analysis using limits. Standard complex class.

Empirical measurement of performance. - Basics methodologies to design algorithms: Greedy Method. Divide and Conquer.

Backtracking. Branch and Bound. Heuristic method. - Graphs and trees algorithms: First search in amplitude. Depth first search. Algorithms

to find the shortest path (Dijkstra’s algorithm, Floyd’s algorithm). Transitive closure. Algorithms to find minimum spanning tree (Prim’s algorithm, Kruskal’s algorithm). Topological sorting.

- Distributed algorithms. - Introduction to automata theory. Finite-state machine. Turing machine. Context free

grammar. Non-computable functions. - Introduction to cryptography. Public and Private Key.

REFERENCE 1. HOROWITZ E., SAHNIS S. AND RAJASEKARAN S. Computer algorithms/ C++. Computer

Science Press. 1996 2. CORMEN T, LEUSERSON C & RIVEST D. Introduction to algorithms. MIT press. 1990 3. SEDGEWICK, R. Algorithms. Second Edition. Addison Wesley. 2001 4. BRASSARD, G & BRATLEY, P. Algorithms fundamentals. Prentice Hall. 1990 5. MEHLHORN, K. Data Structures and Algorithms. Vol 1-3. Springer-Verlag. 2000 6. AHO A, HOPCROFT J & ULLMAN J. The design and analysis of computer algorithms,

Addison-Wesley. 1999


COURSE OUTLINE

COURSE TITLE: SOFTWARE DEVELOPMENT



CODE 72-4712


CREDITS 2 CREDIT

SEMESTER VII

HOURS\WK 3


LECTURE HOURS 2

LAB HOURS 1

ORIGINATED BY

SUMMARY OF PREVIOUS KNOWLEDGE Functional and conceptual management of database system. Relational database design. Transaction processing

MAIN OBJECTIVE Design and analyze software systems, in order to be able to develop software systems from a logical point of view trough practical group experiences.

COURSE DESCRIPTION - Software Engineering. Concept. Classification. Software engineering myths. Phases.

Software Architecture. - Process oriented systems. Design and structure analysis. Data flow diagrams.

Processes description. Data Dictionary. Modular Systems. The process of software design: Concepts and fundamental principles of design.

- Introduction to object-oriented methodology and its representation. - Basic concepts related to the unified process of software development. - Inception Phase of unified process of software development. Importance. Use case

modeling. - Elaboration Phase: Use case model. Analysis Model. Design Model. - Construction Phase: Components modeling. Representation: Components diagrams.

Implementation: UI and database design. Transition Phase: Testing. -

REFERENCE 1. SOMMERVILLE I. Software Engineering. 6th Edition. Addison Wesley. 2001 2. PRESSMAN R. Software Engineering – A practitioner’s approach. 5th Edition. McGraw Hill. Mexico 2002 3. JACOBSON, GRADY & RUMBAUGH. Unifies Process of software development.


COURSE OUTLINE

COURSE TITLE: VISUAL PROGRAMMING



CODE 072-4883


CREDITS 3

SEMESTER VIII

HOURS\WK 3


LECTURE HOURS 3

LAB HOURS 0

ORIGINATED BY

SUMMARY OF PREVIOUS KNOWLEDGE Graphics systems. Fundamental techniques of graphics handling.

MAIN OBJECTIVE Develop software, using visual tools to design and implement object-oriented programs.

COURSE DESCRIPTION - Introduction: Fundamental aspect of visual programming. Develop user interfaces.

Controls uses. Code development. - Variables and constant: Create and uses of variables and constant. Variables scope. - Iteration structure. - Dialog boxes and error capture. - Database access, DDE and OLE. - Software design: OOED software planning. Coding, testing, depuration and

documentation. Build user interfaces. - Selection structure. - Files access.

REFERENCE 1. CORNELL P. Computer Graphics: An Object-Oriented Approach to the Art and

Science. Franklin, Breedle & Asoc. 1994 2. HEARN D. & BAKER M. Graphics for computers. Prentince Hall. 1994


COURSE OUTLINE

COURSE TITLE: ARITIFICIAL INTELLIGENCE



CODE 072-4363


CREDITS 3

SEMESTER VII

HOURS\WK 3


LECTURE HOURS 3

LAB HOURS 0

ORIGINATED BY

SUMMARY OF PREVIOUS KNOWLEDGE Basic algorithms analysis. Basic methodologies for algorithms design. Graphs and trees algorithms: Searching.

MAIN OBJECTIVE Design and implement intelligent systems in different areas: Natural languages processing, experts systems, robotic, based on basic fundamentals of artificial

intelligence.

COURSE DESCRIPTION - Fundamental aspects of intelligent systems. Artificial intelligence history.

Philosophical aspects. Fundamental concepts. World modeling. Application of heuristic methods.

- Intelligent agents. Search and satisfaction of constraints. Solution space. Brute Force search. First search in amplitude and Depth first search.

- Reasoning and knowledge representation. Review of propositional logic. First order logic. Demonstration of theorems. Expert systems characteristics. Non-monotonic Inference. Probabilistic reasoning. Theorem of Bayes.

- Advance search: Genetics algorithm. Local search. - Machine Learning. Neural networks. Definitions and examples of machine learning.

Supervised learning. Decision tree learning. Neural network. Belief networks. Nearest Networks Algorithms. Learning theory. Unsupervised learning. Knowledge reinforcement.

REFERENCE 1. MIRA J., GONZALEZ J & FERNANDEZ S. Artificial intelligence resolve problems.

1st Edition. Addison Wesley. 1998 2. RUSSEL S., BERKLEY & NORVIG P. Artificial intelligence. A modern approach. 1st

Edition. Prentice Hall. 1996 3. RICH, E & KNIGHT, K. Artificial Intelligence. 2nd Edition. McGraw Hill. 1994. 4. WINSTON, P. Artificial Intelligence. 3rd Edition. Addison Wesley. 1992


COURSE OUTLINE

COURSE TITLE: ARTIFICIAL INTELLIGENCE WORKSHOP



CODE 072-4371

PREREQUISITIES 072-3161, 072-3381

CREDITS 1

SEMESTER VII

HOURS\WK 3


LECTURE HOURS 0

LAB HOURS 3

ORIGINATED BY

SUMMARY OF PREVIOUS KNOWLEDGE Basic algorithms analysis. Basic methodologies for algorithms design. Graphs and trees algorithms: Searching.

MAIN OBJECTIVE Analyze, design an implement intelligent systems in different areas: Natural languages processing, experts systems, robotic, based on basic fundamentals of artificial intelligence.

COURSE DESCRIPTION - Practice 1: Searching and satisfaction of constraints. Brute Force search. First search

in amplitude and Depth first search. - Practice 2: Reasoning and knowledge representation. Expert system architecture. - Practice 3: Advance search: Genetics algorithm. Local search. - Practice 4: Game problems. Algorithms and solutions. - Practice 5: Machine Learning and neural networks: Learning machines examples.

Supervised learning. - Practice 6: Decision tree learning. Neural network. Belief networks. - Practice 7: Pattern recognition algorithms.

REFERENCE 1. MIRA J., GONZALEZ J & FERNANDEZ S. Artificial intelligence resolve problems.

1st Edition. Addison Wesley. 1998 2. RUSSEL S., BERKLEY & NORVIG P. Artificial intelligence. A modern approach. 1st

Edition. Prentice Hall. 1996 3. RICH, E & KNIGHT, K. Artificial Intelligence. 2nd Edition. McGraw Hill. 1994. WINSTON, P. Artificial Intelligence. 3rd Edition. Addison Wesley. 1992


COURSE OUTLINE

COURSE TITLE: ADVANCE SOFTWARE DEVELOPMENT



CODE 072-4742


CREDITS 2

SEMESTER VIII

HOURS\WK 3


LECTURE HOURS 2

LAB HOURS 1

ORIGINATED BY

SUMMARY OF PREVIOUS KNOWLEDGE Software design process: Process-oriented systems design. Data-oriented systems design. Object-oriented system design.

MAIN OBJECTIVE Implement software development techniques to build interactive web applications, focus on object-oriented libraries to generate graphical user interfaces. Event-oriented programming and fundamentals of human-computer interaction.

COURSE DESCRIPTION - Client\ Server E-commerce software engineering. Concepts. Distributed systems design.

Security engineering. Software components of client server systems. - Web engineering (IWeb). The IWeb Process. UML extended representation for web software

development based on unified process. Management problems. - Event-oriented programming: Handle events methods. Events propagation. - Concurrence administration on events handling. Exceptions management. - Learning\ Teaching systems: Concepts. Methodology of Galvis. - Re-engineering software: Reverse engineering. Restructuration. Direct engineering. Re-

engineering economics. - Extreme programming (XP). Concepts. Construction phase with XP. - Introduction to human-computer interaction. Development and evaluation based on humans.

Human performance models. Characteristics of good design and good software designers. - Software testing based on humans: Determination of evaluation objectives. Evaluation

strategies. - Software development based on humans: Approaches, characteristics y generalities of

development process. Techniques and tools to generate prototypes. - New approaches for software development

REFERENCE 1. HARMELEN M. Object modeling and user interface design. Addison Wesley. 2001 2. SZYPERSK C. Component Software. Beyond Object-Oriented Programming. Addison

Wesley. 1998. 3. PRESSMAN R. Software Engineering – A practitioner’s approach. 5th edition. McGraw

Hill. 2002



COURSE TITLE: SOFTWARE DEVELOPMENT WORKSHOP



CODE 072-4751


CREDITS 1

SEMESTER VIII

HOURS\WK 3


LECTURE HOURS 0

LAB HOURS 3

ORIGINATED BY

SUMMARY OF PREVIOUS KNOWLEDGE Software design process: Process oriented systems design. Data-oriented systems design. Object-oriented system design.

MAIN OBJECTIVE Develop software based on practical foundations to analyze and design solutions based on software engineering and practical use of the methodology in real projects of software developing.

COURSE DESCRIPTION - Practice 1: Software tools to visualize, create, implement and document software - Practice 2: Project definition. Inception phase planning. Use case modeling.

Documentation. - Practice 3: Inception Phase: Analysis and design modeling. - Practice 4: Elaboration Phase: Use case model. Software architecture representation. - Practice 5: Elaboration Phase: Depuration. Analysis Model. Design Model. - Practice 6: Construction Phase: Components modeling. Implementation: UI Design. - Practice 7: Construction Phase: Implementation: Database Design. Phase testing. - Practice 8: Transition phase: Software Testing - Practice 9: Install software. Last revision. Presentation.

REFERENCE 1. HARMELEN M. Object Modeling and user interface design. Addison Wesley.

2001 2. SZYPERSK C. Component Software. Beyond Object-Oriented Programming.

Addison Wesley. 1998. 3. PRESSMAN R. Software Engineering – A practitioner’s approach. 5th edition.

McGraw Hill. 2002 4. McCONNELL S. Develop and management of IT projects. 1st Edition. McGraw

Hill. 1997 5. JACOBSON, GRADY & RUMBAUGH. Unifies Process of software development.


COURSE OUTLINE

COURSE TITLE: EVENT ORIENTED PROGRAMMING



CODE 072-5843

PREREQUISITIES 072-4743, 072-4751

CREDITS 3

SEMESTER IX

HOURS\WK 3


LECTURE HOURS 3

LAB HOURS 0

ORIGINATED BY

SUMMARY OF PREVIOUS KNOWLEDGE Event-oriented programming: Methods to handle events. Events propagation. Concurrence administration on events handling. Exceptions management. Software development based on the human. Software development techniques.

MAIN OBJECTIVE Analyze the paradigms of the event-oriented programming, using object-oriented programming languages that support the handle of events to develop applications.

COURSE DESCRIPTION - General event-oriented programming fundamentals. - Programming languages that support event oriented paradigms. - Events: Event oriented programming. Models to handle events. - Build user interfaces oriented to events. - Models to handle events in others programming languages.

REFERENCE 1. CAMPIONE & WALRATH. The Java Tutorial. 3rd Edition. Addison Wesley. 1998. 2. The instructor will give additional study material.

traduccion couse outlines johanna ponce

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