Configuration-dependent Fault Localization

11/18/2019
by   Son Nguyen, et al.
0

In a buggy configurable system, configuration-dependent bugs cause the failures in only certain configurations due to unexpected interactions among features. Manually localizing configuration-dependent faults in configurable systems could be highly time-consuming due to their complexity. However, the cause of configuration-dependent bugs is not considered by existing automated fault localization techniques, which are designed to localize bugs in non-configurable code. Thus, their capacity for efficient configuration-dependent localization is limited. In this work, we propose CoFL, a novel approach to localize configuration-dependent bugs by identifying and analyzing suspicious feature interactions that potentially cause the failures in buggy configurable systems. We evaluated the efficiency of CoFL in fault localization of artificial configuration-dependent faults in a highly-configurable system. We found that CoFL significantly improves the baseline spectrum-based approaches. With CoFL, on average, the correctness in ranking the buggy statements increases more than 7 times, and the search space is significantly narrowed down, about 15 times.

READ FULL TEXT

Please sign up or login with your details

Forgot password? Click here to reset

Sign in with Google

×

Use your Google Account to sign in to DeepAI

×

Consider DeepAI Pro