DRACULA: Detector of Data Races in Signals Handlers
Takamitsu Tahara, Katsuhiko Gondow, Seiya Ohsuga · 2008
Data races can occur even in sequential programs due to asynchronous software interrupts (e.g., UNIX signals). In this paper, we propose and implement a new tool DRACULA that dynamically detects data races caused by UNIX signals. DRACULA has many positive characteristics like full-automation, no source code required, high scalability, and synchronization mechanism independence, which make DRACULA highly practical. Our preliminary evaluation of applying DRACULA on SPARC and IA32 platforms to Bash-3.0, consisting of around 89 KLOC in C code, produced promising results; the rates of false-positives are very low (2.6% and 7.0%) and DRACULA automatically reported 3 actual data races in Bash-3.0.