2015Unpublished venueRequires access

Static slack-based instrumentation of programs

Hany Kashif, Johnson J. Thomas, Hiren Patel, Sebastian Fischmeister

Open publisher page 3 citations

Abstract

Real-time embedded programs are time sensitive and, to trace such programs, the instrumentation mechanism must honor the programs' timing constraints. We present a time-aware instrumentation technique that injects program code with slack-based conditional instrumentation. The central idea is to execute instrumentation code only when its execution does not increase the worst-case execution time beyond a program's deadline. This occurs at run-time. Unlike previous efforts, this work allows instrumenting on the path that results in the worst-case execution time of the program. We propose a software, and a hardware method of allowing for slack-based conditional instrumentation. We evaluate and compare these two alternatives using a common benchmark suite for real-time systems. Our results show that, on average, the two proposed methods achieve 57% and 80% instrumentation coverage, respectively, compared to only a 3% coverage by previous work.

About this research paper

What this paper is about

Real-time embedded programs are time sensitive and, to trace such programs, the instrumentation mechanism must honor the programs' timing constraints. We present a time-aware instrumentation technique that injects program code with slack-based conditional instrumentation. The central idea is to execute instrumentation code only when its execution does not increase the worst-case execution time beyond a program's deadline. This occurs at run-time. Unlike previous efforts, this work allows instrumenting on the path that results in the worst-case execution time of the program. We propose a software, and a hardware method of allowing for slack-based conditional instrumentation. We evaluate and compare these two alternatives using a common benchmark suite for real-time systems. Our results show that, on average, the two proposed methods achieve 57% and 80% instrumentation coverage, respectively, compared to only a 3% coverage by previous work.

Why it matters

OpenAlex reports 3 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

Real-time embedded programs are time sensitive and, to trace such programs, the instrumentation mechanism must honor the programs' timing constraints. We present a time-aware instrumentation technique that injects program code with slack-based conditional instrumentation. The central idea is to execute instrumentation code only when its execution does not increase the worst-case execution time beyond a program's deadline. This occurs at run-time. Unlike previous efforts, this work allows instrumenting on the path that results in the worst-case execution time of the program. We propose a software, and a hardware method of allowing for slack-based conditional instrumentation. We evaluate and compare these two alternatives using a common benchmark suite for real-time systems. Our results show that, on average, the two proposed methods achieve 57% and 80% instrumentation coverage, respectively, compared to only a 3% coverage by previous work.

Key concepts: Instrumentation (computer programming), Computer science, Benchmark (surveying), Suite, Code (set theory), Software, TRACE (psycholinguistics), Embedded system

Related papers

Back to paper searchBrowse research topicsOriginal source
Static slack-based instrumentation of programs — Research Paper | ScholarLens