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Advanced Programming
Scholar Year: 2019/2020 - 1S
| Code: |
INF32157 |
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Acronym: |
PA |
| Scientific Fields: |
Informática |
Courses
| Acronym |
N. of students |
Study plan |
Curricular year |
ECTS |
Contact time |
Total Time |
| INF |
156 |
|
2º |
6,0 |
75 |
162,0 |
Teaching language
Portuguese
Intended learning outcomes (Knowledges, skills and competencies to be developed by the students)
Students are expected to have a good knowledge of advanced programming techniques, including the implementation and use of Abstract Data Types (TADs), Software Patterns and Refactoring Techniques.
Syllabus
1 -Abstract Data Types (ADTs)
1.1 Introduction to implementation of ADTs in JAVA
1.2 Trees: ADT Binary Search Tree
1.3 GraphsADT Graph
2 - Software Patterns
2.1 Introduction to software patterns
2.2 Architectural Patterns
2.3 Creation Patterns
2.4 Structural Patterns
2.5 Behavioural Patterns
3 - Refactoring
3.1 Bad Smells
3.2 Refactoring Techniques
Software
Java runtime environments
NetBeans IDE
Demonstration of the syllabus coherence with the UC intended learning outcomes
Syllabus covers all the topics needed to enable students to master various advanced programming techniques, including the implementation and use of Abstract Data Types (ADTs), Software Patterns and Refactoring techniques.
Teaching methodologies
Classes Theoretical/Practical: presentation of the material with the help of slides presentation and, problem solving with execution of the solution in Integrated Development Environment.
Lab classes: solving exercises in a development environment and elaborating a software application (pratical work)
Demonstration of the teaching methodologies coherence with the curricular unit's intended learning outcomes
The use of methodologies that include exposition of knowledge, resolution of exercises and the elaboration of a software application gives the student the opportunity to acquire, apply and integrate knowledge about advanced programming techniques (implementation and use of Abstract Data Types) of Software Patterns and Refactoring techniques).
Assessment methodologies and evidences
The student may choose a continuous assessment or examination. In both cases you will have to carry out a practical work that will be defended in oral discussion.
1. If you wish to be evaluated by examination, you will also provide an exam the normal time or at the time of appeal, and to obtain approval you must have a grade of 9.5 or higher in any of the exam.
2. If you choose continuous assessment (in addition to the practical assignment), the student will make 5 class questions (5 multi-choice questions in each lesson card), 8 laboratories evaluated and a summative test. If you do not obtain approval in the continuous regime the student will have to take the normal period exam or appeal.
IMPORTANT NOTES:
1. The approval of the Laboratory component is a requirement to be approved in the discipline.
2. Regardless of whether the student opts for the examination evaluation or for continuous assessment, it is ABSOLUTELY MANDATORY to register in the evaluation tests within the established timeframes. Entries are made through the moodle platform.
Students who are not enrolled within the deadlines previously established will be forbidden access to the respective test.
MODE 1: Continuous Assessment (general)
Theoretical (50%)> = 9.5
- Average of the best 4 QA - 15%
- Supplementary Test - 35%> = 9.5
Practice (50%)> = 9.5
- Practical Work 35%
- Av Laboratorial 15%
MODE 2: Assessment by examination
Exam - 50% (> = 9.5)
Practical work -50% (> = 9.5)
MODE 3: Continuing Assessment (Student Worker)
Theoretical (50%)> = 9.5
- Average of 2 Questions Lessons (30 minutes duration) 15%
- Supplementary Test - 35%> = 9.5
Practice (50%)> = 9.5
- Practical Work 35%> = 9,5
- Av Laboratorial 15% - (4 works submitted in moodle - individually done and discussed in person)
NOTE: In the special season and at the time of recourse the students must take an exam and a practical work.
Attendance system
To access the continuous evaluation (General mode), attendance of 75% in the classes is required.
Assement and Attendance registers
| Description |
Type |
Time (hours) |
End Date |
| Attendance (estimated) |
Classes |
0 |
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| |
Total: |
0 |
Primary Bibliography
Martin Fowler, Kent Beck , John Brant , William Opdyke;Opdyke, don Roberts , 2002 , 2002. ISBN: Refactoring: Improving the Design of Existing Code |
Michael T. Goodrich, Roberto Tamassia;Data Structure and Algorithms in Java, John Wiley & Sons, 2011 |
Eric Freeman ,Elisabeth Robson, Bert Bates, Kathy Sierra;Head First Design Patterns,. ISBN: OREILLY |
António Adrego da Rocha;Estruturas de Dados e Algoritmos em Java, FCA. ISBN: 978-972-722-704-4 |
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