A Software Behavior Trustworthiness Measurement Method based on Data Mining

This paper presents a congruence measurement method by partitions to apply software trustworthiness measures in dynamic behavior feature datasets. The datasets are generated at software running time. And the method compares the datasets with the static attribute feature datasets generated at software testing time. So this method can make recommendations for users in services selection time under the environment of SaaS. The measurement method is carried out in three stages: firstly, defining the concept of trust, software trustworthiness, static and dynamic feature datasets with fundamental calculating criteria; secondly, providing a group of formulas to illustrate congruence measurement approach for comparing the two types of feature datasets; lastly, giving an architecture supported by software trustworthiness measurement algorithm to evaluate conceptualized hierarchical software trustworthiness. © 2011, the authors.