Software Metrics Artifacts Making Web Quality Measurable

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 aimed at future works.