Software Metrics

The goal of this research is to provide the software industry with methods/tools for effective and efficient use of metrics – to support big data analyses, software analytics and machine learning.

The Software Metrics project started in August 2006 as a joint project between University of Gothenburg and a number of industry partners.

Read more about the project at software-center.se

The project addresses the following research problems:

  • How to maximize the value of measurement programs?
  • How to use machine learning and deep learning to identify hidden patterns in measurement data (e.g. in mining software repositories, defect trend analysis, test optimization and requirement analysis)?
  • How to visualize large data sets
  • How to transfer modern measurement practices to companies?
     

The group has the expertise in:

  • Machine learning and big data analyses
  • Software analytics
  • Development of measurement systems and visualization of quantitative data
  • Identification, development and assessment of Key Performance Indicators (KPIs) for product and organizational performance
  • Measuring and predicting quality of software designs
  • Quantifying and visualization
    • Documentation quality
    • Communication
    • Requirements complexity
    • Software reliability
  • Optimization of the number of indicators needed to monitor products and organizations

 

Books:

Automotive Software Architectures (springer.com)

Software Development Measurement Programs (springer.com)


Contact persons: Miroslaw Staron, Jan Bosch



Published: Tue 25 Feb 2014. Modified: Fri 19 Oct 2018