February 23, 2018  - CINI ITEM National Lab - Centri Comuni  Complesso Universitario Montesantangelo

h: 10.00 - 12.00

Ing. Marco CASTELLUCCIO

Mozilla, London, UK

Improving software quality through machine learning and data mining

How we are using machine learning and data mining techniques at Mozilla to improve software quality and engineering practices: automatic understanding of groups of crash reports with contrast set learning; improving clustering of crash reports using Natural Language Processing techniques; empirical studies of software processes at Mozilla (analyzing the processes around uplifts / backports, the review processes, how bugs caused by third-party software affect the products and how they are managed); automatically detecting web-compatibility issues (with virtually infinite test oracles) using Convolutional Neural Networks; studying and improving processes around flaky tests management (e.g. using code coverage information). Future directions.