First cycle
degree courses
Second cycle
degree courses
Single cycle
degree courses
School of Science
Course unit
DATA STRUCTURES AND PROGRAMMING (Ult. numero di matricola dispari)
SCP7081518, A.A. 2018/19

Information concerning the students who enrolled in A.Y. 2018/19

Information on the course unit
Degree course First cycle degree in
SC2094, Degree course structure A.Y. 2014/15, A.Y. 2018/19
bring this page
with you
Number of ECTS credits allocated 6.0
Type of assessment Mark
Course unit English denomination DATA STRUCTURES AND PROGRAMMING
Website of the academic structure
Department of reference Department of Statistical Sciences
E-Learning website
Mandatory attendance No
Language of instruction Italian
Single Course unit The Course unit can be attended under the option Single Course unit attendance
Optional Course unit The Course unit can be chosen as Optional Course unit

Teacher in charge MASSIMO MELUCCI ING-INF/05
Other lecturers ANTONIO GIUNTA 000000000000

Course unit code Course unit name Teacher in charge Degree course code
SCP7081518 DATA STRUCTURES AND PROGRAMMING (Ult. numero di matricola dispari) MASSIMO MELUCCI SC2095

ECTS: details
Type Scientific-Disciplinary Sector Credits allocated
Basic courses ING-INF/05 Data Processing Systems 6.0

Course unit organization
Period Second semester
Year 1st Year
Teaching method frontal

Type of hours Credits Teaching
Hours of
Individual study
Laboratory 1.0 10 15.0 2
Lecture 5.0 32 93.0 No turn

Start of activities 25/02/2019
End of activities 14/06/2019
Show course schedule 2019/20 Reg.2014 course timetable

Examination board
Board From To Members of the board
4 Commissione a.a.2018/19 (matr.pari) 01/10/2018 30/09/2019 ZINGIRIAN NICOLA (Presidente)
GIUNTA ANTONIO (Membro Effettivo)
MELUCCI MASSIMO (Membro Effettivo)
3 Commissione a.a.2018/19 (matr.dispari) 01/10/2018 30/09/2019 MELUCCI MASSIMO (Presidente)
GIUNTA ANTONIO (Membro Effettivo)
ZINGIRIAN NICOLA (Membro Effettivo)

Prerequisites: The course foresees to have previously acquired the concepts presented in the course of Processing Systems I as well as the ability to analyze and synthesize simple programs in C language.
Target skills and knowledge: The main competence to be acquired is the ability to distinguish information from the way in which it is represented by data and to make data management algorithms effective through programming. The knowledge acquired is related to the way in which information is represented by the programmer through data structures and the way in which they are represented by the computer. We also acquire the ability to represent algorithms for managing data structures by writing programs in a programming language.
Examination methods: The exam will present specific information processing problems that will have to be solved through the data structures and the algorithms illustrated in class and by writing programs in a programming language. The elaborate will be the program in source form.
Assessment criteria: The correctness of the solution provided by the program written in a programming language will be evaluated.
Course unit contents: - The main data structures for the representation of information.
- The main algorithms for processing data structures.
- The encoding of algorithms and data structures by using a programming language.
Planned learning activities and teaching methods: The course in the classroom provides the theoretical explanation of the concepts through the traditional blackboard, their validation through special programs built on the spot with a visible terminal in video projection. In ASID some exercises will be performed that simulate the problems of examination.
Additional notes about suggested reading: Lecture notes by the teacher.
Textbooks (and optional supplementary readings)
  • Aho, Alfred V.; Ullman, Jeffrey D., Fondamenti di informaticaAlfred V. Aho, Jeffrey D. Ullman. Bologna: Zanichelli, 1994. Cerca nel catalogo
  • Ceri, Stefano; Mandrioli, Dino, Informaticaarte e mestiereStefano Ceri, Dino Mandrioli, Licia Sbattella. Milano: McGraw-Hill, 2004. Cerca nel catalogo

Innovative teaching methods: Teaching and learning strategies
  • Lecturing
  • Laboratory
  • Problem based learning
  • Case study
  • Working in group
  • Problem solving
  • Loading of files and pages (web pages, Moodle, ...)

Innovative teaching methods: Software or applications used
  • Moodle (files, quizzes, workshops, ...)