Training and Research

Credits

4

Language

English

Class attendance

Free Choice

Location

VERONA

Learning objectives

Software testing is a cornerstone activity in software development, conducted to identify defects by checking the program execution across several testing scenarios. Considering that manually writing test cases for all the important scenarios might be quite time consuming and expensive, several research approaches have been proposed to automate the generation of test cases that (i) assess many features of the software under development and (ii) are likely to reveal defects.
This PhD course will cover the foundational techniques proposed in literature to automatically write test cases, including those based on symbolic execution, concrete-symbolic execution and evolutionary algorithms. Subsequently, more recent approaches will be covered, that have been elaborated and proposed to automatically write test cases for diverse application domains, such as for web application, Android apps, blockchain smart-contracts and REST APIs.
The course will also include practical hands-on activities, where participants are supposed to develop a small project to implement one of the presented approaches to automatically write test cases for a domain of their interest. The exam consists in presenting this project at the end of the course.

Prerequisites and basic notions

Basic knowledge of programming, especially in Java

Program

The course program includes the following topics:
- Foundations and terminology of software testing
- Automated generation of test cases: Concrete symbolic execution, Search based, Genetic algorithms
- Automated generation of test cases for different domains: Web application, Smartphone apps, Blockchain smart contracts, REST APIs.
- Tools to support automated generation of test cases

Didactic methods

Frontal lectures, practical laboratory and discussions.

Learning assessment procedures

Project at the end of the course.

Students with disabilities or specific learning disorders (SLD), who intend to request the adaptation of the exam, must follow the instructions given HERE

Assessment

Clarity, quality and completeness of the project.

Criteria for the composition of the final grade

Project evaluation.

PhD school courses/classes - 2024/2025

Please note: Additional information will be added during the year. Currently missing information is labelled as “TBD” (i.e. To Be Determined).

1. PhD students must obtain a specified number of CFUs each year by attending teaching activities offered by the PhD School.
First and second year students must obtain 8 CFUs. Teaching activities ex DM 226/2021 provide 5 CFUs; free choice activities provide 3 CFUs.
Third year students must obtain 4 CFUs. Teaching activities ex DM 226/2021 provide 2 CFUs; free choice activities provide 2 CFUs.
More information regarding CFUs is found in the Handbook for PhD Students: https://www.univr.it/phd-vademecum

2. Registering for the courses is not required unless explicitly indicated; please consult the course information to verify whether registration is required or not. When registration is actually required, instructions will be sent well in advance. No confirmation e-mail will be sent after signing up. Please do not enquiry: if you entered the requested information, then registration was silently successful.

3. When Zoom links are not explicitly indicated, courses are delivered in presence only.

4. All information we have is published here. Please do not enquiry for missing information or Zoom links: if the information you need is not there, then it means that we don't have it yet. As soon as we get new information, we will promptly publish it on this page.

Summary of training activities

Teaching Activities ex DM 226/2021: Linguistic Activities

Teaching Activities ex DM 226/2021: Research management and Enhancement

Teaching Activities ex DM 226/2021: Statistics and Computer Sciences

Teaching Activities: Free choice

Course lessons
PhD Schools lessons

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Guidelines for PhD students

Below you will find the files that contain the Guidelines for PhD students and rules for the acquisition of ECTS credits (in Italian: "CFU") for the Academic Year 2023/2024.

Documents

Title Info File
File pdf Dottorandi: linee guida generali (2024/2025) pdf, it, 104 KB, 29/10/24
File pdf PhD students: general guidelines (2024/2025) pdf, en, 107 KB, 29/10/24