Director: Mirco Tribastone
The growing pervasiveness and centrality of software systems in all aspects of life requires the development of new methodologies for their analysis, design and validation in order to meet the increasingly stringent quality criteria required for their effective operation. Quality issues have arisen, for example, in numerous events of publication of sensitive data of companies and institutions, or the public outcry following recent events of crashes of public administration platforms developed for various forms of economic support in response to the Covid emergency.
The track in Software Quality (SQ) focuses on software as the main object of study around which to develop skills to improve its quality along the complete life cycle, from requirements analysis to validation and testing, considering both functional properties, i.e. program correctness, and the extra-functional ones such as usability, accessibility, reliability, performance and security.
The educational objective of the SQ track is to train researchers able to analyze, manage and anticipate software quality issues relevant to the digital transformation processes of society, including the following: digital identity, secure authentication and data privacy; database design for interoperable cloud-based information systems; strengthening the cybersecurity perimeter of critical infrastructure; explainable artificial intelligence systems to clarify the motivations behind automated decisions; methodologies to increase energy efficiency for software; and methodologies for auditing software technologies and systems to certify their quality.
The SQ track develops expertise in computer science in formal methods, programming languages, software engineering, cybersecurity, cloud computing, machine learning, and artificial intelligence. In addition, the SQ track will draw, in an interdisciplinary fashion, from adjacent fields such as control engineering (for the development of methods for optimal software self-adaptation to unanticipated external stimuli), numerical analysis (for the development of efficient techniques for analyzing performance models of software systems), operations research, and statistical physics (development of predictive models).
The course program is developed consistently with the educational objective. Specifically, courses will cover aspects related to software engineering (requirements engineering, methodologies of development and audit of software projects), mathematical methods for correctness (formal methods, program verification), modeling and simulation (machine learning, stochastic processes, performance evaluation, reliability, optimization) and computer security.
PhD students belonging to the SQ track will be involved in the joint training project in "Software Quality" with the PhD program in Computer Science of the Gran Sasso Science Institute (GSSI) of L'Aquila. This project stimulates the mobility of faculty and students between the two locations, the possibility of joint thesis co-supervision, and the activation of joint laboratories for the experimentation of techniques and methodologies for software quality.
Input and Output Profiles
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 software quality. The SQ track prepares for both further academic careers and transfer of acquired skills to the public and private sectors.
For more information regarding the track's activities and research staff, please see https://sysma.imtlucca.it/.