It is well established that ICT systems play a core role in our society, supporting our business and daily life activities. As systems evolve to cope with the increasing demands from the society they support, more and more important it becomes having effective methodologies to evaluate and control their quality.
One of the approaches proposed to track quality evolution is the use of software product metrics. These metrics enable a direct quantification of characteristics of the software artifacts such as source code, test code or schema definitions. In particular statically derived metrics (e.g. size, complexity metrics) can be used as early as the first artifacts are created or modified hence allowing faster response in case of potential problems are identified.
There are still many research challenges to address in metrics research for ICT systems with respect to both metrics definition and usage addressed in this Thematic Track.
Spreadsheets are growing in usage and criticality of functions they support and hence it is important to defined appropriate metrics to evaluate their quality evolution. In “A Quality Model for Spreadsheets”, Cunha et al propose a set of metrics to automatically evaluate spreadsheets based on the ISO/IEC 9126 international standard for the evaluation of software quality. The authors analyze a large set of spreadsheets to calibrate thresholds to be able to calculate a rating for each metric.
Systems are growing in size (generating a very large set of measurements) requiring means to identify only the important measurements that should be act upon. In “Automatic Event Detection for Software Product Quality Monitoring”, Bijlsma et al propose a methodology that automatically analyzes the difference of measurements over time to pinpoint changes worth to investigate. The authors applied this method to a large set of industrial systems reporting on the number of events detected.
Both works of Cunha et al and Bijlsma et al contribute to the body of knowledge of Quality Evolution in ICT by propose novel methodologies to evaluate and track software quality.