Efficient and scalable omniscient debugging for model transformations

Corley, Jonathan; Eddy, B. P.; Syriani, Eugene; Gray, Jeff

doi:10.1007/s11219-015-9304-4

Cited by 10 publications

(14 citation statements)

References 33 publications

(36 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A particular case of debugging is omniscient debugging (back-in-time or reversible debuggers) proposed by several studies in the context of model interpretation. Omniscient debugging replays the execution of systems using the recorded traces, and provides step-by-step execution in both forward and backward modes, and variable view (e.g., [13,21]). Corley et al [20,22] explore this approach to the debugging of model transformations in AToMPM [79].…”

Section: Model-level Debugging Via Interpretationmentioning

confidence: 99%

“…Omniscient debugging replays the execution of systems using the recorded traces, and provides step-by-step execution in both forward and backward modes, and variable view (e.g., [13,21]). Corley et al [20,22] explore this approach to the debugging of model transformations in AToMPM [79]. Their implementation records each change at the end of a transformation step, and provides support to step back to the previous states.…”

Section: Model-level Debugging Via Interpretationmentioning

confidence: 99%

See 1 more Smart Citation

Live modeling in the context of state machine models and code generation

et al. 2020

View full text Add to dashboard Cite

Live modeling has been recognized as an important technique to edit behavioral models while being executed and helps in better understanding the impact of a design choice. In the context of Model-driven Development (MDD) models can be executed by interpretation or by the translation of models into existing programming languages, often by code generation. This work is concerned with the support of live modeling in the context of state machine models when they are executed by code generation. To this end, we propose an approach that is completely independent of any live programming support offered by the target language. This independence is achieved with the help of a model transformation which equips the model with support for features which are required for live modeling. A subsequent code generation then produces a self-reflective program that allows changes to the model elements at runtime (through synchronization of design and runtime models). We have applied the approach in the context of UML-RT and created a prototype (Live-UMLRT) that provides a full set of services for live modeling of UML-RT state machines such as re-execution, adding/removing states and transitions, and adding/removing action code. We have evaluated the prototype on several use-cases. The evaluation shows that (1) generation of a self-reflective and model instrumentation can be carried out with reasonable performance, and (2) our approach can apply model changes to the running execution faster than the standard approach that depends on the live programming support of the target language.

show abstract

Section: Model-level Debugging Via Interpretationmentioning

confidence: 99%

Section: Model-level Debugging Via Interpretationmentioning

confidence: 99%

Live modeling in the context of state machine models and code generation

et al. 2020

View full text Add to dashboard Cite

show abstract

“…Despite omniscient debugging's advantages, there are severe performance limitations. First, omniscient debugging is plagued with memory issues (Bousse, Corley, Combemale, Gray, and Baudry 2015, Pothier, Tanter, and Piquer 2007, Corley, Eddy, Syriani, and Gray 2017. Storing the complete simulation trace eventually leads to memory exhaustion, as trace size only increases.…”

Section: Problems With Omniscient Debuggingmentioning

confidence: 99%

“…Omniscient debugging techniques have been explored in the context of modelling languages. Corley et al have implemented omniscient debugging for model transformations and analysed its efficiency Gray 2014, Corley, Eddy, Syriani, andGray 2017). Since model transformations are nondeterministic, their implementation logs each change at the end of a transformation step.…”

Section: Related Workmentioning

confidence: 99%

Time- and Space-Conscious Omniscient Debugging of Parallel DEVS

2017

TMS/DEVS Symposium on Theory of Modeling &Amp; Simulation (TMS/DEVS 2017)

View full text Add to dashboard Cite

Current Parallel DEVS simulation tools provide a wide set of debugging features. Omniscient debugging, or debugging backwards in time, is only rarely implemented, presumably due to its high resource consumption. Outside of DEVS simulation, omniscient debugging implementations are often lossy: some parts of the model or code are ignored, or they consider only a time window of most recent events. In this paper, we consider efficient and lossless omniscient debugging, particularly in the context of Parallel DEVS. We take inspiration from optimistic synchronization protocols, which can roll back simulation. We investigate how this technique can be tailored to omniscient debugging of Parallel DEVS models. Our algorithm limits simulation overhead and memory consumption, while remaining lossless. We compare the traditional approach with our approach. Our approach significantly decreases time and space overhead, at the cost of slightly slower debugging operations.

show abstract

“…The impact with regards to performance and scalability associated with incorporating the omniscient features has been reported in a previous work [11], the raw data has been made available online 1 . The prototype and a step-wise debugger implemented in AToMPM were both used to run a Petri-net simulator over various size models and the performance metrics were recorded.…”

Section: Quantifying the Impact Of Omniscient Debuggingmentioning

confidence: 99%

Towards Efficient and Scalabale Omniscient Debugging for Model Transformations

Corley

Eddy

Gray

2014

Proceedings of the 14th Workshop on Domain-Specific Modeling

Self Cite

View full text Add to dashboard Cite

Model transformations (MTs) are central artifacts in modeldriven engineering (MDE) that define core operations on models. Like other software artifacts, MTs may possess defects (bugs). Some MDE tools provide support for debugging. In this paper, we describe an omniscient debugging technique. Our technique enhances stepwise execution support for MTs by providing the ability to traverse, in either direction, the execution history of a live debugging session. We also introduce a proof of concept prototype applying the described technique and a preliminary study of the scalability, in terms of memory consumption, and performance, in terms of time to execute.

show abstract

Efficient and scalable omniscient debugging for model transformations

Cited by 10 publications

References 33 publications

Live modeling in the context of state machine models and code generation

Live modeling in the context of state machine models and code generation

Time- and Space-Conscious Omniscient Debugging of Parallel DEVS

Towards Efficient and Scalabale Omniscient Debugging for Model Transformations

Contact Info

Product

Resources

About