Skip to content

Integrated Systemic Research Software Intelligence

I define Integrated Systemic Research Software Intelligence (ISRSI) as a software engineering research paradigm that combines software engineering methods, machine learning and artificial intelligence to provide systemic insights into sets of software projects. It enables system-level software intelligence that supports governance, decision-making, strategical planning, etc., for research software ecosystems or organizations and their units.

To examine the term “Integrated Systemic Research Software Intelligence” more closely:

  • Integrated refers to the combination and integration of analyses of sets of software projects and processes within the given system on different aspects, e.g., software quality, security, readiness, compliance, maintainability, sustainability, impact, etc.
  • Systemic refers to the focus of intelligence-gathering on the level of systems, i.e., ecosystems or organizations and their units.
  • Research Software refers to the focus on research software as defined in [1], which, due to the specific preconditions of its development, maintenance and operation, benefits particularly from a systemic view.
  • Intelligence refers to the holism of the provided knowledge, i.e., the potential for abstraction and access to system properties beyond the sum of its parts.

ISRSI combines the following methods and paradigms in particular to create, prepare and consolidate datasets to make them accessible and usable.

  • Repository, data and metadata mining;
  • empirical and evidence-based software engineering;
  • automated software engineering;
  • software analytics;
  • machine learning;
  • artifical intelligence;
  • data science.

[1] M. Gruenpeter, D. S. Katz, A.-L. Lamprecht, T. Honeyman, D. Garijo, A. Struck, A. Niehues, P. A. Martinez, L. J. Castro, T. Rabemanantsoa, N. P. Chue Hong, C. Martinez-Ortiz, L. Sesink, M. Liffers, A. C. Fouilloux, C. Erdmann, S. Peroni, P. Martinez Lavanchy, I. Todorov, and M. Sinha, "Defining Research Software: a controversial discussion," 2021. doi: 10.5281/zenodo.5504016.