Deadline analysis of interrupt-driven software

Brylow, Dennis; Palsberg, Jens

doi:10.1109/tse.2004.64

Cited by 18 publications

(9 citation statements)

References 31 publications

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“…There has also been some research on using program analysis techniques for interrupt‐driven software . For example, Schlich et al use model checking of assembly code software for microcontrollers; however, this approach does not check temporal properties of the software.…”

Section: Related Workmentioning

confidence: 99%

A hybrid approach to testing for nonfunctional faults in embedded systems using genetic algorithms

Srisa-an

Cohen

et al. 2018

Software Testing Verif & Rel

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Embedded systems are challenging to program correctly, because they use an interrupt-driven programming paradigm and run in resource-constrained environments. This leads to various classes of nonfunctional faults that can be detected only by customized verification techniques.These nonfunctional faults are specifically related to usage of resources such as time and memory. For example, the presence of interrupts can induce delays in interrupt servicing and in system execution time. Such delays can occur when multiple interrupt service routines and interrupts of different priorities compete for resources on a given CPU. As another example, stack overflows are caused when the combination of active methods and interrupt invocations on the stack grows too large, and these can lead to data loss and other significant device failures. To detect these types of nonfunctional faults, developers need to estimate worst-case resource usage. Most existing approaches for calculating such estimates are based on static analysis; however, these have a tendency to overapproximate the resources needed. Dynamic techniques such as random testing, in contrast, often underapproximate resource usage. In this article, we present SIMESPRESSO, a framework that uses a combination of static analysis and a test case generation algorithm to estimate worst-case resource usage. There are three different worst-case resource usage scenarios that we consider: (1) worst-case execution times,(2) worst-case interrupt latencies, and (3) worst-case stack usage. SIMESPRESSO first uses static analysis to identify program paths and interrupt interleavings that potentially lead to worst-case scenarios. It then uses a genetic algorithm to generate test cases that guide program execution down these paths, using these particular interrupt interleavings. We performed an empirical study to evaluate the effectiveness of SIMESPRESSO; our results show that SIMESPRESSO is more effective than static analysis approaches and improves significantly over the state of the art dynamic technique, random test case generation. We also find that when we use only the genetic algorithm, omitting the static analysis, SIMESPRESSO performs almost as effectively, but takes significantly longer to complete its task.

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Section: Related Workmentioning

confidence: 99%

A hybrid approach to testing for nonfunctional faults in embedded systems using genetic algorithms

Srisa-an

Cohen

et al. 2018

Software Testing Verif & Rel

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“…Analysis of interrupt-driven programs. In the literature, there are a few work on analyzing and verifying IDPs [3,4,20,21]. Brylow et al [3] propose a static analysis method for interrupt-driven Z86-based software.…”

Section: Related Workmentioning

confidence: 99%

Numerical static analysis of interrupt-driven programs via sequentialization

Wu¹,

Chen²,

Miné

et al. 2015

2015 International Conference on Embedded Software (EMSOFT)

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Embedded software often involves intensive numerical computations and thus can contain a number of numerical runtime errors. The technique of numerical static analysis is of practical importance for checking the correctness of embedded software. However, most of the existing approaches of numerical static analysis consider sequential programs, while interrupts are a commonly used technique that introduces concurrency in embedded systems. To this end, a numerical static analysis approach is desired for embedded software with interrupts. In this paper, we propose a sound numerical static analysis approach specifically for interrupt-driven programs based on sequentialization techniques. A key benefit of using sequentialization is the ability to leverage the power of the state-of-the-art analysis and verification techniques for sequential programs to analyze interrupt-driven programs. To be more clear, we first propose a sequentialization algorithm to sequentialize interrupt-driven programs into non-deterministic sequential programs according to the semantics of interrupts. On this basis, we leverage the power of numerical abstract interpretation to analyze numerical properties of the sequentialized programs. Moreover, to improve the analysis precision, we design specific abstract domains to analyze sequentialized interrupt-driven programs by considering their specific features. Finally, we present encouraging experimental results obtained by our prototype implementation.

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“…Researchers attempted to apply different formal methods to interrupts. Palsberg et al [17], [18], [19], [20] performed a series of studies on interrupt-driven Z86-based software. They proposed a typed interrupt calculus, and developed a tool to analyze interrupt latencies, stack sizes, deadlines, and verify fundamental properties.…”

Section: Related Workmentioning

confidence: 99%

Probabilistic Denotational Semantics for an Interrupt Modelling Language

Huang

Zhao

Qin

et al. 2015

2015 20th International Conference on Engineering of Complex Computer Systems (ICECCS)

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Interrupts play an important role in real time and embedded systems. It is purposely designed to handle unexpected and emergent issues. However, the randomicity of interrupts brings some potential safety problems, i.e., too frequently interrupt handling would cause the interrupted program to miss its deadline. It is therefore difficult to precisely predict and formally reason about a program's behavior in the presence of interrupts. In this paper, we move one step forward by proposing a probabilistic denotational model for an interrupt modeling language that is capable of describing programs with nested interrupts, to characterise the formal semantics of such programs from a quantitative perspective under Hoare and He's UTP framework. On top of the denotational model, we also present a set of algebraic laws involving distinct features. Our model sets up a semantic foundation for the analysis and reasoning about programs with nested interrupts for embedded systems.

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Deadline analysis of interrupt-driven software

Cited by 18 publications

References 31 publications

A hybrid approach to testing for nonfunctional faults in embedded systems using genetic algorithms

A hybrid approach to testing for nonfunctional faults in embedded systems using genetic algorithms

Numerical static analysis of interrupt-driven programs via sequentialization

Probabilistic Denotational Semantics for an Interrupt Modelling Language

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