The need for a theory of software complexity to serve as a rigorous, scientific foundation for software engineering has long been recognized. However, unfortunately, the complexity measures proposed thus far have only resulted in rough heuristics and rules of thumb. In this paper, we propose a new information theoretic measure of software complexity that, unlike previous measures, captures the volume of design information in software modules. By providing proof outlines for a number of theorems that collectively represent our current understanding and intuitions about software complexity, we demonstrate that this new, information-based formulation of software complexity is not only capable of explaining our current understanding of software complexity, but also is resilient to the factors that cause inaccuracies in previous measures.
|Title of host publication
|Proceedings - 4th SEMAT Workshop on General Theory of Software Engineering, GTSE 2015
|Institute of Electrical and Electronics Engineers Inc.
|Number of pages
|Published - Jul 27 2015
|4th SEMAT Workshop on General Theory of Software Engineering, GTSE 2015 - Florence, Italy
Duration: May 18 2015 → …
|4th SEMAT Workshop on General Theory of Software Engineering, GTSE 2015
|5/18/15 → …
- Design Decisions
- Information Volume
- Software Complexity
- Software Design
ASJC Scopus subject areas