Obstacles in Worst-Case Execution Time Analysis

Conference Proceedings of the 2000 IEEE International Performance, Computing, and Communications Conference (Cat. No.00CH37086), 2000

(WCET) of a real-time program depends greatly on the technique used to generate paths. A method that is not able to distinguish between executable-and dead-paths could result in overestimation of the WCET. This paper addresses the issues of determining automatically the feasible paths. The algorithm targets the assembly code representation of a super-scalar processor program so that its hardware features can be accounted for during WCET estimation. The method attempts to identi& constant values in a real-time program to reduce the amount of user provided information using the concept of partially-known variables.

ACM Transactions on Embedded Computing Systems, 2008

The determination of upper bounds on execution times, commonly called Worst-Case Execution Times (WCETs), is a necessary step in the development and validation process for hard real-time systems. This problem is hard if the underlying processor architecture has components such as caches, pipelines, branch prediction, and other speculative components. This article describes different approaches to this problem and surveys several commercially available tools and research prototypes.

International Journal on Software Tools for Technology Transfer, 2009

The first international Worst Case Execution Time (WCET) Tool Challenge in 2006 used benchmark programs to evaluate academic and commercial WCET tools. It aimed to study the state-of-the-art in WCET analysis. The WCET Tool Challenge comprised two parallel evaluation approaches: an internal evaluation by the respective tool developers and an external test by a neutral person of an independent institute. The latter was conducted by the author of this paper. Focusing on the external test, we describe the rules, benchmarks, participants and discuss the obtained results.

Deutschsprachige WCET-Tagung

IEEE Transactions on Industrial Informatics, 2000

For hard real-time systems, static code analysis is needed to derive a safe bound on the worst-case execution time (WCET). Virtually all prior work has focused on the accuracy of WCET analysis without regard to the speed of analysis. The resulting algorithms are often too slow to be integrated into the development cycle, requiring WCET analysis to be postponed until a final verification phase.

Analyzers (SSQSA) is a set of software tools for static analysis that is incorporated in the framework developed to target the common aim-consistent software quality analysis. The main characteristic of all integrated tools is the independency of the input computer language. Language independency is achieved by enriched Concrete Syntax Tree (eCST) that is used as an intermediate representation of the source code. This characteristic gives the tools more generality comparing to the other similar static analyzers. The aim of this paper is to describe an early idea for introducing support for static timing analysis and Worst Case Execution Time (WCET) calculation at code level in SSQSA framework.

IFIP International Federation for Information Processing, 2004

Software - Practice and Experience, 2010

In this paper, we propose a solution for a worst-case execution time (WCET) analyzable Java system: a combination of a time predictable Java processor and a tool that performs WCET analysis at Java bytecode level. We present a Java processor, called JOP, designed for time-predictable execution of real-time tasks. The execution time of bytecodes, the instructions of the Java virtual machine, is known cycle accurately for JOP. Therefore, JOP simplifies the low-level WCET analysis. A method cache, which fills whole Java methods into the cache, simplifies cache analysis.

HAL (Le Centre pour la Communication Scientifique Directe), 2016

To ensure that a program will respect all its timing constraints we must be able to compute a safe estimation of its worst case execution time (WCET). However with the increasing sophistication of the processors, computing a precise estimation of the WCET becomes very difficult. In this paper, we propose a novel formal method to compute a precise estimation of the WCET that can be easily parameterized by the hardware architecture. Assuming that there exists an executable timed model of the hardware, we first use symbolic execution to precisely infer the execution time for a given instruction flow. Then we merge the states relying on the loss of precision we are ready to accept.

Abstract—We construct a fully automatic static WCET analysis suitable for real-time embedded systems applications by augmenting a high-level static analysis technique (originally aimed at heap-space) with a machine-level worst-case execution time tool. We evaluate this approach by studying two typical and realistic real-time control applications, using a readily available commercial microcontroller. Keywords-WCET; analysis; static; type system;

2006 27th IEEE International Real-Time Systems Symposium (RTSS'06), 2006

Static Worst-Case Execution Time (WCET) analysis is a technique to derive upper bounds for the execution times of programs. Such bounds are crucial when designing and verifying real-time systems. A key component for statically deriving safe and tight WCET bounds is information on the possible program flow through the program. Such flow information can be provided manually by user annotations, or automatically by a flow analysis. To make WCET analysis as simple and safe as possible, it should preferably be automatically derived, with no or very limited user interaction.

Embedded and Real-Time …, 2011

The goal of measurement-based WCET estimation (MBWE) is to derive an estimate of the worst-case execution time (WCET) of a given piece of software on a particular target platform by executing the software on the target hardware and analyzing the obtained time-stamped execution traces.

2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence), 2008

Most software engineering methods require some form of model populated with appropriate information. Realtime systems are no exception. A significant issue is that the information needed is not always freely available and derived it using manual methods is costly in terms of time and money. Previous work showed how machine learning information derived during software testing can be used to derive loop bounds as part of the Worst-Case Execution Time analysis problem. In this paper we build on this work by investigating the issue of branch prediction.

Proc. 5th International Workshop on Worst-Case …, 2005