Computer Programming with Laboratory
Scientific Disciplinary Sector (SSD)
INF/01 - INFORMATICS
Primo semestre, Secondo semestre
This course proposes providing the fundamentals skills in order to analyze and resolve problems by means of developing programs. The general objectives of this module are - the knowledge of the principles of programming and of programming languages, - the mastery of fundamental techniques for analyzing problems and developing their algorithmic solutions, - the introduction to the methods for the evaluation of correctness and efficiency of algorithms. In the laboratory, we will practice the above principles by means of a programming activity.
- Problems and Solutions.
- Models of Computations: abstract machine, compiler and interpreter.
- Programming languages: formal languages, compiler, interpreter.
- Laboratory: introduction to linux and to the developing environment.
PART I - Problems, algorithms and programs.
- Imperative programming
- Elementary of programming: basic instructions and development of simple programs; variables, expressions and assignment.
- Data types. The general concept of data type: characterisation and data representation. Abstract Data Types.
- Primitive data types: characterisation, use and related problems.
- Structured data types: array, record, file, pointer, string and other data structures.
- Program structure. Fundamental instructions. Sub-programs: structure, parameters and visibility. Recursion.
- Object Oriented Programming.
- Basics of objects: classes, objects, attributes, constructors, modifiers.
- Advanced data structures: representation of sequences, vector and matrices; inductive and dynamic data structures; introduction to lists, trees and graphs.
PART II - Analysis of Algorithms
- Correctness: termination, logic properties; methods for the correctness verification.
- Efficiency of algorithms.
- Introduction to the complexity. Performance of algorithms. Evaluation of efficiency. Computational costs.
- Asymptotic estimation of the complexity in time and space. The worst and medium case.
- Amortised analysis.
- Study of fundamental examples.
- Sequences: static and dynamic implementation and algorithms.
- Research and Sorting Algorithms: basic search, binary search, insertion and selection sort, merge sort, quick sort.
- Matrices and Vectors: implementation, operations and algorithms.
- Dynamic sequences: abstract definition and implementation; basic operations.
- Trees. Abstract definition and implementation. Basic operation. Binary research trees.
- Introduction to algorithms on graphs.
The practical activities use the laboratory and consist of learning the programming language in the laboratory and solving problems by applying the principles developed in class.
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The final exam consists of an oral exam: in order to be admitted to the final exam, the student must pass a preliminary written test.
The written test can be partially replaced by ongoing tests and activities.
The assessment methods could change according to the evolution of the general health situation and the academic rules.