Proceedings of the 29th annual ACM/IEEE international symposium on Microarchitecture
Exploiting hardware performance counters with flow and context sensitive profiling
Proceedings of the ACM SIGPLAN 1997 conference on Programming language design and implementation
Proceedings of the 14th ACM SIGPLAN conference on Object-oriented programming, systems, languages, and applications
A portable sampling-based profiler for Java virtual machines
Proceedings of the ACM 2000 conference on Java Grande
Interprocedural Path Profiling
CC '99 Proceedings of the 8th International Conference on Compiler Construction, Held as Part of the European Joint Conferences on the Theory and Practice of Software, ETAPS'99
Adaptive online context-sensitive inlining
Proceedings of the international symposium on Code generation and optimization: feedback-directed and runtime optimization
Fast, accurate call graph profiling
Software—Practice & Experience
Cloning-based context-sensitive pointer alias analysis using binary decision diagrams
Proceedings of the ACM SIGPLAN 2004 conference on Programming language design and implementation
Low-overhead memory leak detection using adaptive statistical profiling
ASPLOS XI Proceedings of the 11th international conference on Architectural support for programming languages and operating systems
Low-overhead call path profiling of unmodified, optimized code
Proceedings of the 19th annual international conference on Supercomputing
Accurate, efficient, and adaptive calling context profiling
Proceedings of the 2006 ACM SIGPLAN conference on Programming language design and implementation
Refinement-based context-sensitive points-to analysis for Java
Proceedings of the 2006 ACM SIGPLAN conference on Programming language design and implementation
The DaCapo benchmarks: java benchmarking development and analysis
Proceedings of the 21st annual ACM SIGPLAN conference on Object-oriented programming systems, languages, and applications
Using Valgrind to detect undefined value errors with bit-precision
ATEC '05 Proceedings of the annual conference on USENIX Annual Technical Conference
Valgrind: a framework for heavyweight dynamic binary instrumentation
Proceedings of the 2007 ACM SIGPLAN conference on Programming language design and implementation
Making context-sensitive points-to analysis with heap cloning practical for the real world
Proceedings of the 2007 ACM SIGPLAN conference on Programming language design and implementation
Proceedings of the 22nd annual ACM SIGPLAN conference on Object-oriented programming systems and applications
Tracking bad apples: reporting the origin of null and undefined value errors
Proceedings of the 22nd annual ACM SIGPLAN conference on Object-oriented programming systems and applications
Evaluating the benefits of context-sensitive points-to analysis using a BDD-based implementation
ACM Transactions on Software Engineering and Methodology (TOSEM)
FastTrack: efficient and precise dynamic race detection
Proceedings of the 2009 ACM SIGPLAN conference on Programming language design and implementation
LiteRace: effective sampling for lightweight data-race detection
Proceedings of the 2009 ACM SIGPLAN conference on Programming language design and implementation
How a Java VM can get more from a hardware performance monitor
Proceedings of the 24th ACM SIGPLAN conference on Object oriented programming systems languages and applications
Proceedings of the 24th ACM SIGPLAN conference on Object oriented programming systems languages and applications
PACER: proportional detection of data races
PLDI '10 Proceedings of the 2010 ACM SIGPLAN conference on Programming language design and implementation
Precise calling context encoding
Proceedings of the 32nd ACM/IEEE International Conference on Software Engineering - Volume 1
Dynamic tainting for deployed Java programs
Proceedings of the ACM international conference companion on Object oriented programming systems languages and applications companion
Complete and Platform-Independent Calling Context Profiling for the Java Virtual Machine
Electronic Notes in Theoretical Computer Science (ENTCS)
Proceedings of the 9th International Conference on Principles and Practice of Programming in Java
Proceedings of the 2012 International Symposium on Software Testing and Analysis
Execution privatization for scheduler-oblivious concurrent programs
Proceedings of the ACM international conference on Object oriented programming systems languages and applications
WuKong: automatically detecting and localizing bugs that manifest at large system scales
Proceedings of the 22nd international symposium on High-performance parallel and distributed computing
Trace construction using enhanced performance monitoring
Proceedings of the ACM International Conference on Computing Frontiers
Proceedings of the 2013 ACM SIGPLAN international conference on Object oriented programming systems languages & applications
DeltaPath: Precise and Scalable Calling Context Encoding
Proceedings of Annual IEEE/ACM International Symposium on Code Generation and Optimization
Dynamic and Adaptive Calling Context Encoding
Proceedings of Annual IEEE/ACM International Symposium on Code Generation and Optimization
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Calling context--the set of active methods on the stack--is critical for understanding the dynamic behavior of large programs. Dynamic program analysis tools, however, are almost exclusively context insensitive because of the prohibitive cost of representing calling contexts at run time. Deployable dynamic analyses, in particular, have been limited to reporting only static program locations. This paper presents Breadcrumbs, an efficient technique for recording and reporting dynamic calling contexts. It builds on an existing technique for computing a compact (one word) encoding of each calling context that client analyses can use in place of a program location. The key feature of our system is a search algorithm that can reconstruct a calling context from its encoding using only a static call graph and a small amount of dynamic information collected at cold (infrequently executed) callsites. Breadcrumbs requires no offline training or program modifications, and handles all language features, including dynamic class loading. We use Breadcrumbs to add context sensitivity to two dynamic analyses: a data-race detector and an analysis for diagnosing null pointer exceptions. On average, it adds 10% to 20% runtime overhead, depending on a tunable parameter that controls how much dynamic information is collected. Collecting less information lowers the overhead, but can result in a search space explosion. In some cases this causes reconstruction to fail, but in most cases Breadcrumbs produces non-trivial calling contexts that have the potential to significantly improve both the precision of the analyses and the quality of the bug reports.