Scalable and Optimized Hybrid Verification of Embedded Software

The verification of embedded software has become an important subject over the last years. However, neither standalone verification approaches, like simulation-based/formal verification, nor state-of-the-art semiformal verification approaches are able to verify large and complex embedded software wi...

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Bibliographic Details
Published inJournal of electronic testing Vol. 31; no. 2; pp. 151 - 166
Main Authors Behrend, Jörg, Lettnin, Djones, Grünhage, Alexander, Ruf, Jürgen, Kropf, Thomas, Rosenstiel, Wolfgang
Format Journal Article
LanguageEnglish
Published New York Springer US 01.04.2015
Springer Nature B.V
Subjects
Algorithms
CAE) and Design
Circuits and Systems
Computer programs
Computer simulation
Computer-Aided Engineering (CAD
Crashworthiness
Electrical Engineering
Embedded computer systems
Engineering
Mathematical models
Program verification (computers)
Software quality
Source code
Semiformal
Hybrid
Verification
Software
Embedded
Online AccessGet full text
ISSN0923-8174
1573-0727
DOI10.1007/s10836-015-5518-4

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Summary:The verification of embedded software has become an important subject over the last years. However, neither standalone verification approaches, like simulation-based/formal verification, nor state-of-the-art semiformal verification approaches are able to verify large and complex embedded software with or without hardware dependencies. This work presents a scalable hybrid verification approach for the verification of embedded software using a semiformal algorithm optimized with static parameter assignment (SPA). These algorithms and methodologies like SPA and counterexample guided simulation are used to combine simulation-based and formal verification in a new way. SPA offers a method to interact between dynamic and static verification approaches based on an automated ranking determination of possible function parameters according to the impact on the model size. Furthermore, SPA inserts initialization code for specific function parameters into the source code under test and supports model building and optimization algorithms to reduce the state space. We have successfully applied this optimized hybrid verification methodology to embedded software applications: Motorola’s Powerstone Benchmark suite and a complex automotive industrial embedded software. The results show that our approach scales better than standalone software model checkers to reach deep state spaces.
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ISSN:0923-8174
1573-0727
DOI:10.1007/s10836-015-5518-4