| KEYWORD |
DAUIN - GR-16 - SOFTWARE ENGINEERING GROUP - SOFTENG
AI-based solutions for web site automated monitoring & regression testing
Reference persons RICCARDO COPPOLA
Research Groups DAUIN - GR-16 - SOFTWARE ENGINEERING GROUP - SOFTENG
Thesis type INDUSTRY
Description Thesis work at Concept Quality Reply
Context:
In the context of highly innovative and technically inspiring projects, we want to build a solution capable to run monitoring & non regression testing over a web site, in
a completely automated fashion, leveraging AI & Computer Vision techniques. The solution is meant to automatically analyze a web site through web crawlers
indexing all content / pages, and to automatically monitor and check through Computer Vision / AI techniques for variations w ith respect to a given baseline, in order
to point out possible deviations (e.g. temporary unavailability, sw regressions after a new deploy, etc.), excluding false positives (e.g. dynamic content).
Description:
The candidate will take part of a dedicated team drafting innovation on AI / ML topics (internal community of practice), ther efore having constant support and
possibility for confrontation with other colleagues. The candidate should contribute to solution architecture, to the scouting of existing tools and techniques available
in the market that can fit to the designed solution, to implementation and validation of a proof-of-concept, to piloting on existing web sites in order to set the basis for
an MVP (Minimum Viable Product). According to the innovative nature of the project, the project will be run with an Agile met hodology in order to keep close control
of task planning/progress and at the same time be able to direct it in the most efficient way
Phases:
• Drafting of baseline solution architecture
• Scouting of existing tools and techniques available in the market that can fit to the designed solution
• Implementation and validation of a first POC (proof-of-concept)
• Piloting on existing web sites in order to assess POC quality, robustness, etc.
• MVP (Minimum Viable Product)
Pre-requisites:
• Demonstrated interest in AI / Computer Vision / Low-Code fields (university projects, extracurricular activities..)
• Interest in Quality Assurance techniques and test automation (university projects, extracurricular activities..)
• Self-directed learning skills
Skills acquired:
• AI, Computer Vision, Web Crawlers, QA Monitoring & Regression testing techniques, Agile delivery approach
Deadline 03/09/2025
PROPONI LA TUA CANDIDATURA