More Web Proxy on the site http://driver.im/

article

Automatic library migration for the generation of hardware-in-the-loop models

Authors:

Joern Ploennigs,

Klaus KabitzschAuthors Info & Claims

Science of Computer Programming, Volume 77, Issue 2

Pages 83 - 95

https://doi.org/10.1016/j.scico.2010.06.005

Published: 01 February 2012 Publication History

Abstract

Embedded systems are widely used in several applications nowadays. As they integrate hard- and software elements, their functionality and reliability are often tested by hardware-in-the-loop methods, in which the system under test runs in a simulated environment. Due to the rising complexity of the embedded functions, performance limitations and practicability reasons, the simulations are often specialized to test specific aspects of the embedded system and develop a high diversity by themselves. This diversity is difficult to manage for a user and results in erroneously selected test components and compatibility problems in the test configuration. This paper presents a generative programming approach that handles the diversity of test libraries. Compatibility issues are explicitly evaluated by a new interface concept. Furthermore, a novel model analyzer facilitates the efficient application in practice by migrating existing libraries. The approach is evaluated for an example from the automotive domain using MATLAB/Simulink.

References

[1]

Kendall, I. and Jones, R., An investigation into the use of hardware-in-the-loop simulation testing for automotive electronic control systems. Control Engineering Practice. v7 i11. 1343-1356.

[2]

Reorda, M.S. and Violante, M., Hardware-in-the-loop-based dependability analysis of automotive systems. In: 12th IEEE Int. Symposium on On-Line Testing, IEEE Computer Society, Washington, DC, USA. pp. 229-234.

Digital Library

[3]

K.-C. Lee, J.-W. Jeon, D.-H. Hwang, S.-H. Lee, Y.-J. Kim, Development of antilock braking controller using hardware in-the-loop simulation and field test, in: 30th Annual Conf. of IEEE, vol. 3, 2004, pp. 2137-2141.

[4]

Biggerstaff, T.J., The library scaling problem and the limits of concrete component reuse. In: 3rd Int. Conf. of Software Reuse, IEEE. pp. 102-109.

[5]

McMurran, R., Rao, A. and Jones, P., Model based validation techniques for complex control systems. In: Hybrid Vehicle Conference, IET The Institution of Engineering and Technology. pp. 201-212.

[6]

S.R. Dalal, A. Jain, N. Karunanithi, J.M. Leaton, C.M. Lott, G.C. Patton, B.M. Horowitz, Model-based testing in practice in: 21st Int. Conf. on Software Engineering, Los Angeles, CA, USA, 1999, pp. 285-294.

[7]

Utting, M. and Legeard, B., Practical Model-Based Testing: A Tools Approach. 2006. Morgan Kaufmann Publishers Inc.

[8]

Czarnecki, K. and Eisenecker, U.W., Generative Programming: Methods, Tools and Applications. 2000. Addison-Wesley.

[9]

Draheim, D., Lutteroth, C. and Weber, G., Generative programming for C#. SIGPLAN Notices. v40 i8. 29-33.

[10]

Fähndrich, M., Carbin, M. and Larus, J.R., Reflective program generation with patterns. In: 5th Int. Conf. on Generative Programming and Component Engineering, ACM Press, New York, NY, USA. pp. 275-284.

[11]

Schlee, M. and Vanderdonckt, J., Generative programming of graphical user interfaces. In: Working Conf. on Advanced Visual Interfaces, ACM Press, New York, NY, USA. pp. 403-406.

[12]

Czarnecki, K., Bednasch, T., Unger, P. and Eisenecker, U.W., Generative programming for embedded software: an industrial experience report. In: 1st ACM SIGPLAN/SIGSOFT Conf. on Generative Programming and Component Engineering, Springer-Verlag. pp. 156-172.

[13]

C. Dziobek, J. Loew, W. Przystas, J. Weiland, Functional variants handling in Simulink models, in: MathWorks Virtual Automotive Conference, Stuttgart, 2008.

[14]

U. Ryssel, J. Ploennigs, K. Kabitzsch, Generative function block design and composition, in: 6th IEEE Workshop on Factory Communication Systems, Torino, Italy, 2006, pp. 253-262.

[15]

U. Ryssel, J. Ploennigs, K. Kabitzsch, M. Folie, Generative design of hardware-in-the-loop models, in: 1st Workshop on Automatic Program Generation for Embedded Systems, Salzburg, Austria, 2007.

[16]

Czarnecki, K., Eisenecker, U.W., Glück, R., Vandevoorde, D. and Veldhuizen, T.L., Generative programming and active libraries. In: Selected Papers from the International Seminar on Generic Programming, Springer-Verlag, London, UK. pp. 25-39.

Digital Library

[17]

Diedrich, C., Russo, F., Winkel, L. and Blevins, T., Function block applications in control systems based on IEC 61804. ISA Transactions. v43 i1. 123-131.

[18]

World Wide Web Consortium (W3C), Extensible Markup Language (XML), http://www.w3.org/XML/ (visited 2009).

[19]

Svahnberg, M. and Mattsson, M., Conditions and restrictions for product line generation migration. In: 4th Int. Workshop on Software Product-Family Engineering, Springer-Verlag, London, UK. pp. 143-154.

[20]

Yoshimura, K., Ganesan, D. and Muthig, D., Defining a strategy to introduce a software product line using existing embedded systems. In: 6th ACM & IEEE Int. Conf. on Embedded Software, ACM Press, New York, NY, USA. pp. 63-72.

[21]

Liu, J., Batory, D. and Lengauer, C., Feature oriented refactoring of legacy applications. In: 28th Int. Conf. on Software Engineering, ACM, New York, NY, USA. pp. 112-121.

[22]

Trujillo, S., Batory, D. and Diaz, O., Feature refactoring a multi-representation program into a product line. In: 5th Int. Conf. on Generative Programming and Component Engineering, ACM, New York, NY, USA. pp. 191-200.

[23]

Kästner, C., Apel, S. and Kuhlemann, M., A model of refactoring physically and virtually separated features. In: 8th Int. Conf. on Generative Programming and Component Engineering, ACM, New York, NY, USA. pp. 157-166.

[24]

S. Wenzel, U. Kelter, Model-driven design pattern detection using difference calculation, in: 1st Int. Workshop on Pattern Detection for Reverse Engineering, Co-located with 13th Working Conf. on Reverse Engineering, 2006.

[25]

M. Schmidt, SiDiff: Generische, auf Ähnlichkeiten basierende Berechnung von Modelldifferenzen, in: SE GI-Tagung Software Engineering: VVUM¿Vergleich und Versionierung von UML-Modellen, 2007, position paper.

[26]

Kelter, U., Wehren, J. and Niere, J., A generic difference algorithm for UML models. In: Liggesmeyer, P., Pohl, K., Goedicke, M. (Eds.), LNI, GI, vol.64. pp. 105-116.

[27]

Melnik, S., Garcia-Molina, H. and Rahm, E., Similarity flooding: a versatile graph matching algorithm and its application to schema matching. In: 18th Int. Conf. on Data Engineering, IEEE Computer Society. pp. 117-128.

[28]

G. Varro, K. Friedl, D. Varro, Adaptive graph pattern matching for model transformations using model-sensitive search plans, in: Int. Workshop on Graph and Model Transformation, 2005, pp. 191-205.

[29]

Nayak, R. and Iryadi, W., XML schema clustering with semantic and hierarchical similarity measures. Knowledge-Based Systems. v20 i4. 336-349.

[30]

Chen, Y.-P.P., Promparmote, S. and Maire, F., Mdsm: microarray database schema matching using the hungarian method. Information Sciences. v176 i19. 2771-2790.

[31]

Doshi, P., Kolli, R. and Thomas, C., Inexact matching of ontology graphs using expectation¿maximization. Web Semantics: Science, Services and Agents on the World Wide Web. v7 i2. 90-106.

[32]

Wang, H., Akinci, B., Garrett Jr., J.H., Nyberg, E. and Reed, K.A., Semi-automated model matching using version difference. Advanced Engineering Informatics. v23 i1. 1-11.

[33]

Levenshtein, V.I., Binary codes capable of correcting deletions, insertions and reversals. Soviet Physics Doklady. v10. 707-710.

[34]

Floyd, R.W., Algorithm 97: shortest path. Communications of the ACM. v5 i6. 345

[35]

Jain, A.K., Murty, M.N. and Flynn, P.J., Data clustering: a review. ACM Computing Surveys. v31 i3. 264-323.

Cited By

Schultheiß ABittner PBoll AGrunske LThüm TKehrer T(2022)RaQuN: a generic and scalable n-way model matching algorithmSoftware and Systems Modeling (SoSyM)10.1007/s10270-022-01062-522:5(1495-1517)Online publication date: 21-Nov-2022
https://dl.acm.org/doi/10.1007/s10270-022-01062-5
Schultheiß ABittner PKehrer TThüm TLopez-Herrejon R(2020)On the use of product-line variants as experimental subjects for clone-and-own researchProceedings of the 24th ACM Conference on Systems and Software Product Line: Volume A - Volume A10.1145/3382025.3414972(1-6)Online publication date: 19-Oct-2020
https://dl.acm.org/doi/10.1145/3382025.3414972
Meixner KRabiser RBiffl S(2020)Feature identification for engineering model variants in cyber-physical production systems engineeringProceedings of the 14th International Working Conference on Variability Modelling of Software-Intensive Systems10.1145/3377024.3377043(1-5)Online publication date: 5-Feb-2020
https://dl.acm.org/doi/10.1145/3377024.3377043
Show More Cited By

Recommendations

A large-scale empirical study on Java library migrations: prevalence, trends, and rationales
ESEC/FSE 2021: Proceedings of the 29th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering

With the rise of open-source software and package hosting platforms, reusing 3rd-party libraries has become a common practice. Due to various failures during software evolution, a project may remove a used library and replace it with another library, ...
Automatic generation of test models and properties from UML models with OCL constraints
OCL '12: Proceedings of the 12th Workshop on OCL and Textual Modelling

Model-Based Testing and Property-Based Testing are two testing methodologies that usually facilitate the automation of the generation of test cases, using either models or properties as basis to derive complete test suites. In doing so, they also ...
MUT: Human-in-the-Loop Unit Test Migration
ICSE '24: Proceedings of the IEEE/ACM 46th International Conference on Software Engineering

Test migration, which enables the reuse of test cases crafted with knowledge and creativity by testers across various platforms and programming languages, has exhibited effectiveness in mobile app testing. However, unit test migration at the source code ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image Science of Computer Programming

Science of Computer Programming Volume 77, Issue 2

February, 2012

48 pages

ISSN:0167-6423

Issue’s Table of Contents

Copyright © Elsevier B.V. © 2010.

Publisher

Elsevier North-Holland, Inc.

United States

Publication History

Published: 01 February 2012

Author Tags

Qualifiers

Article

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

17
Total Citations
View Citations
0
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 15 Jan 2025

Other Metrics

View Author Metrics

Citations

Cited By

Schultheiß ABittner PBoll AGrunske LThüm TKehrer T(2022)RaQuN: a generic and scalable n-way model matching algorithmSoftware and Systems Modeling (SoSyM)10.1007/s10270-022-01062-522:5(1495-1517)Online publication date: 21-Nov-2022
Schultheiß ABittner PKehrer TThüm TLopez-Herrejon R(2020)On the use of product-line variants as experimental subjects for clone-and-own researchProceedings of the 24th ACM Conference on Systems and Software Product Line: Volume A - Volume A10.1145/3382025.3414972(1-6)Online publication date: 19-Oct-2020
Meixner KRabiser RBiffl S(2020)Feature identification for engineering model variants in cyber-physical production systems engineeringProceedings of the 14th International Working Conference on Variability Modelling of Software-Intensive Systems10.1145/3377024.3377043(1-5)Online publication date: 5-Feb-2020
Reuling DKelter UBürdek JLochau M(2019)Automated N-way Program Merging for Facilitating Family-based Analyses of Variant-rich SoftwareACM Transactions on Software Engineering and Methodology10.1145/331378928:3(1-59)Online publication date: 18-Jul-2019
Schlie AWille DSchulze SCleophas LSchaefer I(2017)Detecting Variability in MATLAB/Simulink ModelsProceedings of the 21st International Systems and Software Product Line Conference - Volume A10.1145/3106195.3106225(215-224)Online publication date: 25-Sep-2017
Wille DRunge TSeidl CSchulze SSchaefer I(2017)Extractive software product line engineering using model-based delta module generationProceedings of the 11th International Workshop on Variability Modelling of Software-Intensive Systems10.1145/3023956.3023957(36-43)Online publication date: 1-Feb-2017
Wille DSchulze SSchaefer ISeidl CTeixeira L(2016)Variability mining of state chartsProceedings of the 7th International Workshop on Feature-Oriented Software Development10.1145/3001867.3001875(63-73)Online publication date: 30-Oct-2016
Kehrbusch PRichenhagen JRumpe BSchloßer ASchulze CMei H(2016)Interface-based similarity analysis of software components for the automotive industryProceedings of the 20th International Systems and Software Product Line Conference10.1145/2934466.2934468(99-108)Online publication date: 16-Sep-2016
Seidl CTeixeira L(2016)Proceedings of the 7th International Workshop on Feature-Oriented Software DevelopmentundefinedOnline publication date: 30-Oct-2016
Schaefer ISeidl CCleophas LWatson B(2015)SPLicing TABASCOProceedings of the 2015 Annual Research Conference on South African Institute of Computer Scientists and Information Technologists10.1145/2815782.2815799(1-10)Online publication date: 28-Sep-2015
Show More Cited By

View Options

View options

Media

Figures

Other

Tables

View Issue’s Table of Contents