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 tools1 and research prototypes.

/pdf/the-worst-case-execution-time-problem-overview-of-methods-2kdq3gxkoy.pdf

The worst-case execution-time problem—overview of methods and survey of tools

In this paper, we propose an approach to estimate the worst-case response time (WCRT) of each task in a preemptive multitasking single-processor real-time system utilizing an L1 cache. The approach combines intertask cache-eviction analysis and intratask cache-access analysis to estimate the number of cache lines that can possibly be evicted by the preempting task and also be accessed again by the preempted task after preemptions (thus requiring the preempted task to reload the cache line(s)). This cache-reload delay caused by preempting task(s) is then incorporated into WCRT analysis. Three sets of applications with up to six concurrent tasks running are used to test our approach. The experimental results show that our approach can tighten the WCRT estimate by up to 32p (1.4X) over prior state-of-the-art.

Timing analysis for preemptive multitasking real-time systems with caches

In this paper, we propose an approach to estimate the worst case response time (WCRT) of tasks in a preemptive multi-tasking single-processor real-time system with a set associative cache. The approach focuses on analyzing the cache reload overhead caused by preemptions. We combine inter-task cache eviction behavior analysis and path analysis of the preempted task to reduce, in our analysis, the estimate of the number of cache lines that can possibly be evicted by the preempting task (thus requiring a reload by the preempted task). A mobile robot application which contains three tasks is used to test our approach. The experimental results show that our approach can tighten the WCRT estimate by up to 73% over prior state-of-the-art.

Timing analysis for preemptive multi-tasking real-time systems with caches

This paper explores the issues to be addressed to provide
safe worst-case execution time (WCET) estimation methods
based on measurements. We suggest to use structural testing
for the exhaustive exploration of paths in a program.
Since test data generation is in general too complex to be
used in practice for most real-size programs, we propose
to generate test data for program segments only, using program
clustering. Moreover, to be able to combine execution
time of program segments and to obtain the WCET of the
whole program, we advocate the use of compiler techniques
to reduce (ideally eliminate) the timing variability of program
segments and to make the time of program segments
independent from one another.

/pdf/safe-measurement-based-wcet-estimation-40co2hvicl.pdf

Safe measurement-based WCET estimation

Data caches significantly reduce the average memory access time and are necessary for an efficient design. Due to its direct dependency on input data is difficult to predict the worst case timing behavior, which is crucial for a reliable system. While simulation is too time-consuming, current worst case execution time approaches focus on instruction caches only. Current approaches to data cache analysis restrict cache behavior to predictable data accesses or classify input dependent memory accesses as non-cache able. In this paper we propose a worst case timing analysis for direct mapped data caches that classifies memory accesses as predictable or unpredictable. For unpredictable memory accesses, a novel analysis framework is proposed that tightly bounds the impact on the existing cache contents as well as cache behavior of unpredictable memory accesses themselves. For predictable memory accesses, we use a local cache simulation and dataflow techniques. Furthermore, we describe an implementation of the analysis framework. Several experiments demonstrate its applicability. The approach targets real-time software verification but is also useful for design space exploration.

Worst case timing analysis of input dependent data cache behavior

Verification of program running time is essential in system design with real-time constraints. Simulation with incomplete test patterns or simple instruction counting are not appropriate for complex architectures. Software running times of embedded systems are process state and input data dependent. Formal analysis of such dependencies leads to software running time intervals rather than single values. These intervals depend on program properties, execution paths, and states of processes, as well as on the target architecture. An approach to analysis of process behavior using running time intervals is presented. It improves our previous work by exploiting program segments with single paths and by taking the execution context into account. The example of an asynchronous transfer mode (ATM) cell handler demonstrates significant improvements in analysis precision. Experimental results show the superiority of the presented approach over well-established approaches.

Path clustering in software timing analysis

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

F. Wolf

Author Tools

Chat about Author

Papers

Path clustering in software timing analysis