
\noindent
BACKGROUND:
Recent research has shown the value of social metrics for defect prediction. 
Yet many repositories lack the information required for a  social analysis.
\\
AIM:
Can we infer how developers interact around their code using only static code
measures? Are static code measures useful in predicting defects?
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METHOD:
Using only static code measures,
we  determine what classes are  most  ``active'' 
%(\ie, have high perceived or experienced value attributed by the developer)
(\ie, the classes where the developers spend much time interacting with each other's
design and implementation decisions)
in \NSystems open-source Java systems that lack details about individual developers. 
We assess the merit of these activity-centric measures in the context of  ``inspection optimization'' -- a technique that
allows for reading the fewest lines of code in order to find the most defects.
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RESULTS:
For the task of inspection optimization these activity measures
perform as well as (usually, within 4\%) a theoretical upper bound
on the performance of any set of measures.  
\\ CONCLUSION: 
Activity is an excellent predictor for defects.
