Graph-based analysis and prediction for software evolution
Proceedings of the 34th International Conference on Software Engineering
Measure method and metrics for network characteristics in service systems
ICPCA/SWS'12 Proceedings of the 2012 international conference on Pervasive Computing and the Networked World
| Hi-index | 0.00 |
How can we effectively measure the complexity of a modern complex software system has been a challenge for software engineers. Complex networks as a branch of Complexity Science are recently studied across many fields of science, and many large-scale software systems are proved to represent an important class of artificial complex networks. So, we introduce the relevant theories and methods of complex networks to analyze the topological/structural complexity of software systems, which is the key to measuring software complexity. Primarily, basic concepts, operational definitions, and measurement units of all parameters involved are presented respectively. Then, we propose a qualitative measure based on the structure entropy that measures the amount of uncertainty of the structural information, and on the linking weight that measures the influences of interactions or relationships between components of software systems on their overall topologies/structures. Eventually, some examples are used to demonstrate the feasibility and effectiveness of our method.