P103 065

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Published on October 4, 2007

Author: Jancis

Source: authorstream.com

A Taxonomy of Execution Replay Systems:  A Taxonomy of Execution Replay Systems Frank Cornelis Andy Georges Mark Christiaens Michiel Ronsse Tom Ghesquiere Koen De Bosschere Dept. ELIS Ghent University The Debugging Problem:  The Debugging Problem The debugging process is hard to automate Current tools are inadequate for debugging large scale, interactive, multi-threaded, and event-driven applications Hard to find bugs: Synchronization errors Memory leaks Data races Dangling pointers Inadequate Tools:  Inadequate Tools Most common debugging technique: cyclic debugging Problem: there is no guarantee that the same behavior is observed during subsequent runs as many applications are non-deterministic Ideal situation: reverse execution… Solution: Execution Replay:  Solution: Execution Replay Execution 1 Execution 2 Trace file record replay Requirements:  Requirements Record must have low intrusion Replay must be accurate Record phase must be space efficient Replay phase must be time efficient Slide6:  Tornado RecPlay JaRec jRapture Interrupt Replay Scheduling Replay Compressed differences Instant Replay Input Replay Output Replay RSA DejaVu Igor Recap Outline:  Outline Introduction Content-based vs. ordering-based Dealing with input Dealing with timing Dealing with other processors Conclusion Content-based:  Content-based Record input for every instruction … add r1,1 → r1 load 8(r1) → r2 store r2 → 12(r1) … r1 = 10 r1 = 11 r2 = 401 r1=11 + Instruction can be executed in isolation – Huge trace files Ordering-based:  Ordering-based Record control flow of program from a given initial state C1; C2 + Smaller trace files – Reexecution required Sources of non-determinism:  Sources of non-determinism Input (e.g. a database, time, pixel coordinates) Timing (e.g. interrupts, scheduler actions) Interaction with other processors (processor, DMA, coprocessor) Outline:  Outline Introduction Content-based vs. ordering-based Dealing with input Dealing with timing Dealing with other processors Conclusion Input instructions:  Input instructions application kernel IO-instructions System calls content-based ordering-based  content-based Tornado jRapture Outline:  Outline Introduction Content-based vs. ordering-based Dealing with input Dealing with timing Dealing with other processors Conclusion Dealing with timing:  Dealing with timing Interrupts Input/output (timing aspect; not input aspect) Scheduling application other code ordering-based How to determine the ordering:  How to determine the ordering PC is not enough Need extra counter: SIC1 Instructions executed No of backward jumps 1 Software Instruction Counter Interrupt replay Repeatable scheduling DejaVu Outline:  Outline Introduction Content-based vs. ordering-based Dealing with input Dealing with timing Dealing with other processors Conclusion Dealing with other processors:  Dealing with other processors Multi-threading (multiple threads in one address space) Multi-processing (multiple processes sharing a common block of memory) A coprocessor (video, DMA, …) Code 1 Code 2 data c1 c2 c1 c2 Many systems:  Many systems RecPlay Ordering-based up to the first data race JaRec Ordering-based up to the first data race IGOR Content-based: checkpointing Recap Content-based: reverse execution Instant Replay Ordering-based: version numbers Netzers’s approach Ordering-based: also replays data races Overview:  Overview Conclusion:  Conclusion No execution replay system deals with all forms of non-determinism The more accurate the system gets, the more resources it needs (time, space), and hence becomes less useful There is a need for stable and platform-independent tools to further support debugging

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