Accelerating worst case execution time analysis of timed automata models with cyclic behaviour

Al-Bataineh, Omar I.; Reynolds, Mark; French, Tim

doi:10.1007/s00165-015-0340-4

Cited by 8 publications

(6 citation statements)

References 28 publications

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“…Two approaches that come close to our technique are that of AlBataineh et al [1] and Henry et al [14]. Al-Bataineh et al use a precise acceleration of timed-automata models (with cyclic behavior) for WCET computation.…”

Section: Related Workmentioning

confidence: 73%

TIC: a scalable model checking based approach to WCET estimation

Metta

Becker

Bokil

et al. 2016

Proceedings of the 17th ACM SIGPLAN/SIGBED Conference on Languages, Compilers, Tools, and Theory for Embedded Systems

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The application of Model Checking to compute WCET has not been explored as much as Integer Linear Programming (ILP), primarily because model checkers fail to scale for complex programs. These programs have loops with large or unknown bounds, leading to a state space explosion that model checkers cannot handle. To overcome this, we have developed a technique, TIC, that employs slicing, loop acceleration and over-approximation on timeannotated source code, enabling Model Checking to scale better for WCET computation. Further, our approach is parametric, so that the user can make a trade-off between the tightness of WCET estimate and the analysis time.We conducted experiments on the Mälardalen benchmarks to evaluate the effect of various abstractions on the WCET estimate and analysis time. Additionally, we compared our estimates to those made by an ILP-based analyzer and found that ours were tighter for more than 30% of the examples and equal for the rest.

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Section: Related Workmentioning

confidence: 73%

TIC: a scalable model checking based approach to WCET estimation

Metta

Becker

Bokil

et al. 2016

Proceedings of the 17th ACM SIGPLAN/SIGBED Conference on Languages, Compilers, Tools, and Theory for Embedded Systems

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“…While in these abstractions could be used in some situations, in general they are either too restrictive because they do not work for a large class of programs, or they fail to address the scalability issue arising in the context of using a model checker to compute the WCET. Al-Bataineh et al [1] use a precise acceleration of timed-automata models (with cyclic behavior) for WCET computation, to scale up their IPET technique. However, these ideas are not readily applicable to loop acceleration in C programs in the absence of suitable abstractions.…”

Section: Related Workmentioning

confidence: 99%

“…The techniques being applied today for analyzing the timing behavior, such as Integer Linear Programming (ILP) and Abstract Interpretation (AI), or a combination thereof [59], work very well for analyzing complex programs, but they exhibit several weaknesses: (1) User annotations, such as loop bounds, have to be provided [59,55], but are hard to obtain, influence the tightness and may even refute the soundness of the WCET estimate. Providing too large bounds leads to a large overestimation, and too small bounds may yield an unsafe estimate.…”

Section: Introductionmentioning

confidence: 99%

Scalable and precise estimation and debugging of the worst-case execution time for analysis-friendly processors: a comeback of model checking

Becker¹,

Metta²,

Venkatesh³

et al. 2018

Int J Softw Tools Technol Transfer

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Estimating the Worst-Case Execution Time (WCET) of an application is an essential task in the context of developing real-time or safety-critical software, but it is also a complex and error-prone process. Conventional approaches require at least some manual inputs from the user, such as loop bounds and infeasible path information, which are hard to obtain and can lead to unsafe results if they are incorrect. This is aggravated by the lack of a comprehensive explanation of the WCET estimate, i.e., a specific trace showing how WCET was reached. It is therefore hard to spot incorrect inputs and hard to improve the worst-case timing of the application. Meanwhile, modern processors have reached a complexity that refutes analysis and puts more and more burden on the practitioner. In this article we show how all of these issues can be significantly mitigated or even solved, if we use processors that are amenable to WCET analysis. We define and identify such processors, and then we propose an automated tool set which estimates a precise WCET without unsafe manual inputs, and also reconstructs a maximum-detail view of the WCET path that can be examined in a debugger environment. Our approach is based on Model Checking, which however is known to scale badly with growing application size. We address this issue by shifting the analysis to source code level, where source code transformations can be applied that retain the timing behavior, but reduce the complexity. Our experiments show that fast and precise estimates can be achieved with Model Checking, that its scalability can even exceed current approaches, and that new opportunities arise in the context of "timing debugging".

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“…(Probability update rules after acceleration). Let P = (L, ℓ 0 , L f , X , Act, inv, E, L) be a PTA and (e 0 , e 1 , ..., e m−1 ) ∈ E π be the sequence of edges of a reachable cycle π in P. Then after accelerating the execution of π the probability weights of some edges in P will be updated as follows 1. Let E out be the set of edges in the set out(src(e i )) \ e i , where e i ∈ E π .…”

Section: Accelerating Execution Of Probabilistic Timed Cyclesmentioning

confidence: 99%

“…However, for probabilistic timed systems the problem may be much harder, as the solution needs to handle both timed transitions and probability distributions. Moreover, the abstractions, optimisations, and accelerations developed for the verification of WCET of TAs [1,2] cannot be used to verify expected WCET of PTAs, as cycles in PTAs exhibit both timing and probabilistic behavior.…”

Section: Introductionmentioning

confidence: 99%

Computing Maximal Expected Termination Time of Probabilistic Timed Automata

Al-Bataineh,

Fisher,

Rosenblum

2017

Preprint

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The paper addresses the problem of computing maximal expected time to termination of probabilistic timed automata (PTA) models, under the condition that the system will, eventually, terminate. This problem can exhibit high computational complexity, in particular when the automaton under analysis contains cycles that may be repeated very often (due to very high probabilities, e.g. p = 0.999). Such cycles can degrade the performance of typical model checking algorithms, as the likelihood of repeating the cycle converges to zero arbitrarily slowly. We introduce an acceleration technique that can be applied to improve the execution of such cycles by collapsing their iterations. The acceleration process of a cyclic PTA consists of several formal steps necessary to handle the cumulative timing and probability information that result from successive executions of a cycle. The advantages of acceleration are twofold. First, it helps to reduce the computational complexity of the problem without adversely affecting the outcome of the analysis. Second, it can bring the "worst case execution time" problem of PTAs within the bounds of feasibility for model checking techniques. To our knowledge, this is the first work that addresses the problem of accelerating execution of cycles that exhibit both timing and probabilistic behavior.

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Accelerating worst case execution time analysis of timed automata models with cyclic behaviour

Cited by 8 publications

References 28 publications

TIC: a scalable model checking based approach to WCET estimation

TIC: a scalable model checking based approach to WCET estimation

Scalable and precise estimation and debugging of the worst-case execution time for analysis-friendly processors: a comeback of model checking

Computing Maximal Expected Termination Time of Probabilistic Timed Automata

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