Abstract
The verification and validation of industrial automotive systems is increasingly challenging as they become larger and more complex. Recent automotive Electric Control Units (ECUs) have approximately one half to one million of lines of code, and a modern automobile can contain hundreds of controllers. Significant work-hours are needed to understand and manage systems of this level of complexity. One particular challenge is understanding the changes to the software across development phases and revisions. To this end, we present a code dependency analysis tool that enhances designer understanding. It combines abstract interpretation and graph based data analysis to generate visualized dependency graphs on demand to support designer’s understanding of the code. We demonstrate its value by presenting dependency graph visuals for an industrial application, and report results showing significant reduction of work-hours and enhancement of the ability to understand the software.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Haughey, B.: Design Review Based on Failure Modes (DRBFM) and Design Review Based on Test Results (DRBTR) Process Guidebook. SAE International, Warrendale (2012)
Cytron, R., et al.: An efficient method of computing static single assignment form. In: Proceedings of the 16th ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages, pp. 25–35. ACM (1989)
Weiser, M.: Program slicing. In: Proceedings of the 5th International Conference on Software Engineering. IEEE Press (1981)
Cousot, P., Cousot, R.: Abstract interpretation: a unified lattice model for static analysis of programs by construction or approximation of fixpoints. In: Proceedings of the 4th ACM SIGACT-SIGPLAN Symposium on Principles of Programming Languages, pp. 238–252. ACM (1977)
D’Silva, V., Kroening, D., Weissenbacher, G.: A survey of automated techniques for formal software verification. IEEE Trans. Comput.-Aided Des. Integr. Circ. Syst. 27(7), 1165–1178 (2008)
Aho, A.V.: Compilers: Principles, Techniques and Tools (for Anna University), 2/e. Pearson Education India, Bengaluru (2003)
Kroening, D., Tautschnig, M.: CBMC – C bounded model checker. In: Ábrahám, E., Havelund, K. (eds.) TACAS 2014. LNCS, vol. 8413, pp. 389–391. Springer, Heidelberg (2014). https://doi.org/10.1007/978-3-642-54862-8_26
Tesoriero, C.: Getting Started with OrientDB. Packt Publishing Ltd., Birmingham (2013)
Blazy, S., Bühler, D., Yakobowski, B.: Structuring abstract interpreters through state and value abstractions. In: Bouajjani, A., Monniaux, D. (eds.) VMCAI 2017. LNCS, vol. 10145, pp. 112–130. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-52234-0_7
Blanchet, B., et al.: A static analyzer for large safety-critical software. In: PLDI 2003, pp. 196–207 (2003)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Yamaguchi, T., Brain, M., Ryder, C., Imai, Y., Kawamura, Y. (2019). Application of Abstract Interpretation to the Automotive Electronic Control System. In: Enea, C., Piskac, R. (eds) Verification, Model Checking, and Abstract Interpretation. VMCAI 2019. Lecture Notes in Computer Science(), vol 11388. Springer, Cham. https://doi.org/10.1007/978-3-030-11245-5_20
Download citation
DOI: https://doi.org/10.1007/978-3-030-11245-5_20
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-11244-8
Online ISBN: 978-3-030-11245-5
eBook Packages: Computer ScienceComputer Science (R0)