Non-intrusive on-the-fly data race detection using execution replay

This paper presents a practical solution for detecting data races in parallel programs. The solution consists of a combination of execution replay (RecPlay) with automatic on-the-fly data race detection. This combination enables us to perform the data race detection on an unaltered execution (almost no probe effect). Furthermore, the usage of multilevel bitmaps and snooped matrix clocks limits the amount of memory used. As the record phase of RecPlay is highly efficient, there is no need to switch it off, hereby eliminating the possibility of Heisenbugs because tracing can be left on all the time.Comment: In M. Ducasse (ed), proceedings of the Fourth International Workshop on Automated Debugging (AAdebug 2000), August 2000, Munich. cs.SE/001003

Execution replay and debugging

As most parallel and distributed programs are internally non-deterministic -- consecutive runs with the same input might result in a different program flow -- vanilla cyclic debugging techniques as such are useless. In order to use cyclic debugging tools, we need a tool that records information about an execution so that it can be replayed for debugging. Because recording information interferes with the execution, we must limit the amount of information and keep the processing of the information fast. This paper contains a survey of existing execution replay techniques and tools.Comment: In M. Ducasse (ed), proceedings of the Fourth International Workshop on Automated Debugging (AADebug 2000), August 2000, Munich. cs.SE/001003

Holistic debugging - enabling instruction set simulation for software quality assurance

We present holistic debugging, a novel method for observing execution of complex and distributed software. It builds on an instruction set simulator, which provides reproducible experiments and non-intrusive probing of state in a distributed system. Instruction set simulators, however, only provide low-level information, so a holistic debugger contains a translation framework that maps this information to higher abstraction level observation tools, such as source code debuggers. We have created Nornir, a proof-of-concept holistic debugger, built on the simulator Simics. For each observed process in the simulated system, Nornir creates an abstraction translation stack, with virtual machine translators that map machine-level storage contents (e.g. physical memory, registers) provided by Simics, to application-level data (e.g. virtual memory contents) by parsing the data structures of operating systems and virtual machines. Nornir includes a modified version of the GNU debugger (GDB), which supports non-intrusive symbolic debugging of distributed applications. Nornir's main interface is a debugger shepherd, a programmable interface that controls multiple debuggers, and allows users to coherently inspect the entire state of heterogeneous, distributed applications. It provides a robust observation platform for construction of new observation tools

Multi-level Visualization of Concurrent and Distributed Computation in Erlang

This paper describes a prototype visualization system for concurrent and distributed applications programmed using Erlang, providing two levels of granularity of view. Both visualizations are animated to show the dynamics of aspects of the computation. At the low level, we show the concurrent behaviour of the Erlang schedulers on a single instance of the Erlang virtual machine, which we call an Erlang node. Typically there will be one scheduler per core on a multicore system. Each scheduler maintains a run queue of processes to execute, and we visualize the migration of Erlang concurrent processes from one run queue to another as work is redistributed to fully exploit the hardware. The schedulers are shown as a graph with a circular layout. Next to each scheduler we draw a variable length bar indicating the current size of the run queue for the scheduler. At the high level, we visualize the distributed aspects of the system, showing interactions between Erlang nodes as a dynamic graph drawn with a force model. Speci?cally we show message passing between nodes as edges and lay out nodes according to their current connections. In addition, we also show the grouping of nodes into “s_groups” using an Euler diagram drawn with circles