Biblio

Process-level races are endemic in modern  systems. These races are difficult  to debug  because they are  sensitive to execution   events  such  as  interrupts and scheduling.  Unless  a process interleaving   that can result in the race can be found, it cannot be reproduced  and cannot be corrected. In practice, however,  the number of interleavings  that can occur among processes  in practice  is large,  and the patterns of interleavings can be complex. Thus, approaches for reproducing process-level races  to date are  often ineffective.  In  this paper, we present RRF, a race reproduction  framework that can help software engineers reproduce reported process-level races, enabling  them to potentially  debug these races. RRF performs a hybrid analysis by leveraging  existing  static program analysis tools, dynamic kernel event  reporting tools,  and yield points  to provide  the observability and controllability  needed to reproduce races. We conducted an empirical study to evaluate RRF; our results show that RRF can be effective for reproducing races.