Software Quality
Overview
The growing pervasiveness and centrality of software systems in all aspects of life require the development of new methodologies for their analysis, design, and validation to meet the increasingly stringent quality criteria for their effective operation.
The Software Quality track focuses on the software's whole life cycle, from requirements analysis to validation and testing. The main aspects of concern are program correctness, usability, accessibility, reliability, performance, and security.
The educational objective of the Software Quality track is to train researchers able to analyze, manage and anticipate software quality issues relevant to the digital transformation processes of society, including
auditing and certification for software quality
digital identity, secure authentication and data privacy
design of interoperable cloud-based information systems
cost and energy efficiency of software systems
explainable artificial intelligence
systems for critical infrastructures.
Track Structure
The overall structure of the Ph.D. program is illustrated here.
The Software Quality track develops expertise in computer science in formal methods, programming languages, software engineering, cybersecurity, cloud computing, machine learning, and artificial intelligence. In addition, we offer classes for soft skills, research funding in academia, and technology transfer.
Ph.D. courses for the Software Quality track
Advanced Methods for Complex Systems
Applications of Stochastic Processes
Basics of Technological, Social, and Legal Aspects of Cybersecurity
Concurrent Programming
Foundations of Probability and Statistical Inference
From Shell to Cloud
Fundamentals of Academic Entrepreneurship
Funding Opportunities and Management of Intellectual Property
Introduction to Formal Methods
Introduction to Machine Learning
Introduction to Network Science
Markov Processes
Modelling and Verification of Reactive Systems
Numerical Optimization
Publication Strategies and Scientific Dissemination
Python for Data Science
Principles of Programming with Python
Reduced Order Models and Applications
Reinforcement Learning
Research Topics in Software Quality
Software Verification
Software Security
Stochastic Processes
Vulnerability Assessment and Penetration Testing
Depending on the specific needs of their research projects, students can also take specialised courses available for the other tracks of the Ph.D. program. See here for a full list.
Selection Criteria
Applicants will preferably be graduates in computer science or related disciplines and candidates with backgrounds in the mathematical, physical, and statistical sciences with applied interests in computer science.
Further Information and Contact
The Software Quality track by IMT's SySMA research unit members. You can visit SySMA's website for more information, including ongoing research projects, publications, and collaborations.
Ph.D. candidates in the Software Quality track will also have the opportunity to interact with colleagues from the National Ph.D. program in Cybersecurity, also run in collaboration with members of the SySMA unit.
If you have any questions, please contact sysma@imtlucca.it.