Abstract-Debugging often involves 1) finding the point of failure (the first statement that produces bad output) and 2) finding and fixing the actual bug. Print statements and debugger break points can help with step 1. Slicing the program back from values used at the point of failure can help with step 2. However, neither approach is ideal: Debuggers and print statements can be clumsy and timeconsuming and backward slices can be almost as large as the original program. This paper addresses both problems. We present callstack-sensitive slicing, which reduces slice sizes by leveraging the series of calls active when a program fails. We also show how slice intersections may further reduce slice sizes. We then describe a set of tools that identifies points of failure for programs that produce bad output. Finally, we apply our point-of-failure tools to a suite of buggy programs and evaluate callstack-sensitive slicing and slice intersection as applied to debugging. Callstack-sensitive slicing is very effective: On average, a callstack-sensitive slice is about 0.31 time the size of the corresponding full slice, down to just 0.06 time in the best case. Slice intersection is less impressive, on average, but may sometimes prove useful in practice. Index Terms-Static program slicing, callstack-sensitive analysis, points of failure, output tracing and attribution.
A recent approach based on dynamic 3 see "the Daikon Invariant Detector", http://groups.csail.mit.edu/pag/daikon/ slicing is proposed in REF , which through a callstack-sensitive slicing and slices intersection, reduces the slice sizes by leveraging the series of calls active when a program fails.
Better Debugging via Output Tracing and Callstack-Sensitive Slicing
IEEE Transactions on Software Engineering
IEEE Transactions on Software Engineering
Computer Science