Title: Software Metrics Artifacts to make Web Quality Measurable
Slides available here
Abstract: Mining open source repositories introduces an effective approach to put in practice empirical software engineering in a variety of technologies. Kernel development (Linux) first and then Internet (Chromium) and more recently cloud orchestration (Kubernetes) and machine learning (TensorFlow) are fundamental pieces not just for open source ecosystem but also for the industry leading software innovation. Empirical software engineering sustains a better understanding of these projects, reducing even more the barriers for adoption. In this work we focus on empirical quality assessment developing software metrics artifacts to make web components quality measurable. After reviewing the state of the art and main frameworks for software measurement, we will present our proposal for the empirical evaluation of quality metrics for web components, data collection, measurement and prediction, discussing main benefits and some drawback of the selected approach, which will be aim in future works.
Bio: Andres-Leonardo Martinez-Ortiz is member of the Google Engineering team, leading Google Cloud Ecosystem program in Europe. He drives the success of Google's developer products and the Open Web by creating a thriving ecosystem of developers. He meets with experts and partners in large companies, startups, universities and enterprises, promoting Open standards and Google technologies. He is also member of IEEE, ACM, Linux Foundation and Computer Society. @davilagrau