scholarly journals Time for Reactive System Modeling

2018 ◽  
Author(s):  
Insa Marie-Ann Fuhrmann

Reactive systems interact with their environment by reading inputs and computing and feeding back outputs in reactive cycles that are also called ticks. Often they are safety critical systems and are increasingly modeled with highlevel modeling tools. The concepts of the corresponding modeling languages are typically aimed to facilitate formal reasoning about program constructiveness to guarantee deterministic output and are explicitly abstracted from execution time aspects. Nevertheless, the worst-case execution time of a tick can be a crucial value, as it decides the frequency in which the system can interact with its surroundings. An excessive tick Worst Case Execution Time (WCET) can lead to lost inputs or tardy reaction to critical events. Thus, the modeler has to make sure that the timing behaviour of the system under development meets the specifications. This thesis proposes a general approach to interactive timing analysis, which enables the feedback of detailed timing values directly in the model representation to support timing aware modeling. The concept is based on a generic timing interface that enables the exchangeability of the modeling as well as the timing analysis tool for the flexible implementation of varying tool chains. This aims at enhancing the comparability of tools and facilitates the sharing of benchmark model suites. The introduced approach is applicable not only to dataflow-based systems, but also to state-based systems. The latter is enabled by a concept for communicating analysis requests and responses for arbitrary code parts instead of a restriction to function granularity. The proposed timing analysis approach includes visual highlighting and modeling pragmatics features to guide the user to WCET hotspots for timing related model revisions. The approach is practically evaluated with an open-source Eclipse-based example implementation for the modeling language SCCharts, which includes a user study.

Energies ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1747
Author(s):  
Simona Ramanauskaite ◽  
Asta Slotkiene ◽  
Kornelija Tunaityte ◽  
Ivan Suzdalev ◽  
Andrius Stankevicius ◽  
...  

Worst-case execution time (WCET) is an important metric in real-time systems that helps in energy usage modeling and predefined execution time requirement evaluation. While basic timing analysis relies on execution path identification and its length evaluation, multi-thread code with critical section usage brings additional complications and requires analysis of resource-waiting time estimation. In this paper, we solve a problem of worst-case execution time overestimation reduction in situations when multiple threads are executing loops with the same critical section usage in each iteration. The experiment showed the worst-case execution time does not take into account the proportion between computational and critical sections; therefore, we proposed a new worst-case execution time calculation model to reduce the overestimation. The proposed model results prove to reduce the overestimation on average by half in comparison to the theoretical model. Therefore, this leads to more accurate execution time and energy consumption estimation.


2005 ◽  
Vol 12A (5) ◽  
pp. 365-374
Author(s):  
Hyeon-Hui Park ◽  
Myeong-Su Choi ◽  
Seung-Min Yang ◽  
Yong-Hoon Choi ◽  
Hyung-Taek Lim

2021 ◽  
Vol 20 (6) ◽  
pp. 1-36
Author(s):  
Márton Búr ◽  
Kristóf Marussy ◽  
Brett H. Meyer ◽  
Dániel Varró

Runtime monitoring plays a key role in the assurance of modern intelligent cyber-physical systems, which are frequently data-intensive and safety-critical. While graph queries can serve as an expressive yet formally precise specification language to capture the safety properties of interest, there are no timeliness guarantees for such auto-generated runtime monitoring programs, which prevents their use in a real-time setting. While worst-case execution time (WCET) bounds derived by existing static WCET estimation techniques are safe, they may not be tight as they are unable to exploit domain-specific (semantic) information about the input models. This article presents a semantic-aware WCET analysis method for data-driven monitoring programs derived from graph queries. The method incorporates results obtained from low-level timing analysis into the objective function of a modern graph solver. This allows the systematic generation of input graph models up to a specified size (referred to as witness models ) for which the monitor is expected to take the most time to complete. Hence, the estimated execution time of the monitors on these graphs can be considered as safe and tight WCET. Additionally, we perform a set of experiments with query-based programs running on a real-time platform over a set of generated models to investigate the relationship between execution times and their estimates, and we compare WCET estimates produced by our approach with results from two well-known timing analyzers, aiT and OTAWA.


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