earticle

영어

Ensuring the reliability of structured fork-join parallel programs is difficult because the potential for subtle interactions between concurrent threads can cause concurrency bugs, such as data races, which are hard to detect, reproduce, and eliminate. The visualization for the executions of the programs may offer effective debugging environments with intuitively understanding. Unfortunately, visualization techniques for structured fork-join parallel programs still also difficult to represent and analyze the information of programs executions, because the information for analyzing thread executions and relevant events to data races are increased exponentially in proportion to maximum parallelism of the program. This paper presents a visualization tool that offers overall information for detecting data races by grouping and abstracting thread executions and accesses to shared variables. Moreover, the tool provides an effective approach to debug data races by indicating locations of the defects.