Code profiling enables a user to know where in an application or function the execution time is spent. The Pharo ecosystem offers several code profilers. However, most of the publicly available profilers (MessageTally, Spy, GadgetProfiler) largely ignore the activity carried out by the virtual machine, thus incurring inaccuracy in the gathered information and missing important information, such as the Just-in-time compiler activity. This paper describes the motivations and the latest improvements carried out in VMProfiler, a code execution profiler hooked into the virtual machine, that performs its analysis by monitoring the virtual machine execution. These improvements address some limitations related to assessing the activity of native functions (resulting from a Just-in-time compiler operation): as of now, VMProfiler provides more detailed profiling reports, showing for native code functions in which bytecode range the execution time is spent.
With concurrency being integral to most software systems, developers combine high-level concurrency models in the same application to tackle each problem with appropriate abstractions. While languages and libraries offer a wide range of concurrency models, debugging support for applications that combine them has not yet gained much attention. Record & replay aids debugging by deterministically reproducing recorded bugs, but is typically designed for a single concurrency model only.This paper proposes a practical concurrency-model-agnostic record & replay approach for multi-paradigm concurrent programs, i. e. applications that combine concurrency models. Our approach traces high-level nondeterministic events by using a uniform model-agnostic trace format and infrastructure. This enables orderingbased record & replay support for a wide range of concurrency models, and thereby enables debugging of applications that combine them. In addition, it allows language implementors to add new concurrency models and reuse the model-agnostic record & replay support.We argue that a concurrency-model-agnostic record & replay is practical and enables advanced debugging support for a wide range of concurrency models. The evaluation shows that our approach is expressive and flexible enough to support record & replay of applications using threads & locks, communicating event loops, communicating sequential processes, software transactional memory and combinations of those concurrency models. For the actor model, we reach recording performance competitive with an optimized special-purpose record & replay solution. The average recording overhead on the Savina actor benchmark suite is 10 % (min. 0 %, max. 23 %). The performance for other concurrency models and combinations thereof is at a similar level.We believe our concurrency-model-agnostic approach helps developers of applications that mix and match concurrency models. We hope that this substrate inspires new tools and languages making building and maintaining of multi-paradigm concurrent applications simpler and safer.
ACM CCS 2012Computing methodologies → Concurrent programming languages; Software and its engineering → Software maintenance tools;
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