The program dependence graph and its use in optimization
ACM Transactions on Programming Languages and Systems (TOPLAS)
LLVM: A Compilation Framework for Lifelong Program Analysis & Transformation
Proceedings of the international symposium on Code generation and optimization: feedback-directed and runtime optimization
Scalable statistical bug isolation
Proceedings of the 2005 ACM SIGPLAN conference on Programming language design and implementation
Empirical Software Engineering
Cooperative bug isolation
Statistical Debugging: A Hypothesis Testing-Based Approach
IEEE Transactions on Software Engineering
Statistical debugging using compound boolean predicates
Proceedings of the 2007 international symposium on Software testing and analysis
The probabilistic program dependence graph and its application to fault diagnosis
ISSTA '08 Proceedings of the 2008 international symposium on Software testing and analysis
Discovering and Exploiting Program Phases
IEEE Micro
HOLMES: Effective statistical debugging via efficient path profiling
ICSE '09 Proceedings of the 31st International Conference on Software Engineering
Probabilistic Graphical Models: Principles and Techniques - Adaptive Computation and Machine Learning
Proceedings of the 32nd ACM/IEEE International Conference on Software Engineering - Volume 1
CodeSurfer/x86—A platform for analyzing x86 executables
CC'05 Proceedings of the 14th international conference on Compiler Construction
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Statistical bug isolation techniques attempt to capture a correlation of various program features (like predicates and profiled paths) for debugging. These techniques collect profile data for multiple executions, both with successful and faulty runs, and propose using various statistical tests to capture this correlation. In this paper, we explore the utility of program phases, a concept which is primarily used by computer architects to speed up architectural simulations, for statistical bug isolation. Program phases represent sets of execution intervals in a program's execution where the rates of architectural statistics like branch mispredictions, CPU/Memory usage and cache misses remain almost the same. We found multiple scenarios where coupling program phases with predicates achieves higher accuracy to bug localization than when predicates are used alone. We demonstrate the use of program phases for bug isolation by presenting experimental results and concrete case studies on medium-size programs, showing an improved ranking of the program points that are critical to debugging over when program phases are not used.