  Test effectiveness refers to the capability of a test suite in exposing
faults in software.
  It is crucial to be aware of factors that influence this capability.
  We aim at inferring the causal relationship between the two factors (i.e.,
Cover/Exec) and the capability of a test suite to expose and discover faults in
software. Cover refers to the number of distinct test cases covering the
statement and Exec equals the number of times a test suite executes a
statement. We analyzed 459166 software faults from {12} Java programs. Bayesian
statistics along with the back-door criterion was exploited for the purpose of
causal inference. Furthermore, we examined the common pitfall measuring
association, the mixture of causal and noncausal relationships, instead of
causal association. The results show that Cover is of more causal association
as against \textit{Exec}, and the causal association and noncausal one for
those variables are statistically different. Software developers could exploit
the results to design and write more effective test cases, which lead to
discovering more bugs hidden in software.
