Neural Code Analysis
People
Course director
Description
The course is divided in two parts. First, the students learn how to mine software repositories to collect large amounts of structured and unstructured data that can be used to train deep learning models for the automation of software-related tasks. Second, the students will see concrete applications of AI in software engineering, and will experiment themself with the creation of AI-based tools automating software-related tasks. Solid basis in programming and software engineering are required.
Objectives
To acquire competences related to (i) the usage of AI in software engineering, knowing strengths and weaknesses of such techniques; (ii) the creation and assessment of novel AI-based tools automating software-related tasks.
Teaching mode
In presence
Learning methods
Students will apply the acquired expertise in the context of a project running during the second half of the semester and will give presentations in class about selected research articles relevant for to the course topics.
Examination information
The final grade is defined based on the assignments submitted by the student throughout the semester.
Education
- Master of Science in Software & Data Engineering, Lecture, 2nd year
