VIRTUAL TEST ENVIRONMENT FOR SELF-OPTIMIZING SYSTEMS

被引:0
|
作者
Stoecklein, Joerg [1 ]
Baldin, Daniel [2 ]
Mueller, Wolfgang [3 ]
Xie, Tao [3 ]
机构
[1] Univ Paderborn, Dept Prod Engn, Heinz Nixdorf Inst, D-33102 Paderborn, Germany
[2] Univ Paderborn, Design Distributed Embedded Syst, Heinz Nixdorf Inst, D-33102 Paderborn, Germany
[3] Univ Paderborn, C LAB, D-33102 Paderborn, Germany
关键词
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In our paper we present a virtual test environment for self-optimizing systems based on mutant based testing to validate user tasks of a real-time operating system. This allows the efficient validation of the code coverage of the test cases and therefore helps to detect errors in order to improving the reliability of the system software. Technically we are able to run and test the software on both systems. By writing application software and setting up the virtual test environment properly, we define our test cases. To validate the code coverage for our test cases, we use the approach of mutant based testing. By running this mutated code on our virtual prototype in the virtual test environment, we are able to efficiently validate the code coverage and are able to detect bugs in the application code or detect dead code that is not executed. Finding non-executing code leads to redefinition of our test cases by either changing the test environment or the application code in the case of dead code. We implemented the virtual test environment on top of the third party low cost VR system Unity 3D, which is frequently used in entertainment and education. We demonstrate our concepts by the example of our BeBot robot vehicles. The implementation is based on our self-optimizing real-time operating system ORCOS and we used the tool CERTITUDE(TM) for generating the mutations in our application code. Our BeBot virtual prototype in our virtual test environment implements the same low-level interface to the underlying hardware as the real BeBot. This allows a redirection of commands in ORCOS to either the real or the virtual BeBot in order to provide a VR based platform for early software development as well as ensures comparable conditions under both environments. Our example applies a virtual BeBot that drives through a labyrinth utilizing its IR sensors for navigation. The mutant based testing checks if all situations implemented by the software to navigate through the labyrinth are covered by our tests.
引用
收藏
页数:8
相关论文
共 50 条
  • [1] Virtual prototyping of self-optimizing mechatronic systems
    Gausemeier, J
    Müller, W
    Paelke, V
    Bauch, J
    Shen, Q
    Radkowski, R
    [J]. Design 2004: Proceedings of the 8th International Design Conference, Vols 1-3, 2004, : 219 - 224
  • [2] VIRTUAL AND AUGMENTED REALITY FOR SYSTEMATIC TESTING OF SELF-OPTIMIZING SYSTEMS
    Gausemeier, J.
    Rammig, F.
    Radkowski, R.
    Krupp, A.
    Mueller, W.
    [J]. 11TH INTERNATIONAL DESIGN CONFERENCE (DESIGN 2010), VOL 1-3, 2010, : 1305 - 1314
  • [3] Self-optimizing machining systems
    Moehring, H-C
    Wiederkehr, P.
    Erkorkmaz, K.
    Kakinuma, Y.
    [J]. CIRP ANNALS-MANUFACTURING TECHNOLOGY, 2020, 69 (02) : 740 - 763
  • [4] Self-optimizing production systems
    Permin, Eike
    Bertelsmeier, Felix
    Blum, Matthias
    Buetzler, Jennifer
    Haag, Sebastian
    Kuz, Sinem
    Oezdemir, Denis
    Stemmler, Sebastian
    Thombansen, Ulrich
    Schmitt, Robert
    Brecher, Christian
    Schlick, Christopher
    Abel, Dirk
    Poprawe, Reinhart
    Loosen, Peter
    Schulz, Wolfgang
    Schuh, Guenther
    [J]. RESEARCH AND INNOVATION IN MANUFACTURING: KEY ENABLING TECHNOLOGIES FOR THE FACTORIES OF THE FUTURE - PROCEEDINGS OF THE 48TH CIRP CONFERENCE ON MANUFACTURING SYSTEMS, 2016, 41 : 417 - 422
  • [5] Self-optimizing assembly of laser systems
    Loosen, Peter
    Schmitt, Robert
    Brecher, Christian
    Mueller, Rainer
    Funck, Max
    Gatej, Alexander
    Morasch, Valentin
    Pavim, Alberto
    Pyschny, Nicolas
    [J]. PRODUCTION ENGINEERING-RESEARCH AND DEVELOPMENT, 2011, 5 (04): : 443 - 451
  • [6] Basics of virtual machine migration on heterogeneous architectures for self-optimizing mechatronic systems
    Groesbrink, Stefan
    [J]. PRODUCTION ENGINEERING-RESEARCH AND DEVELOPMENT, 2013, 7 (01): : 69 - 79
  • [7] An autonomous model for self-optimizing virtual machine selection by learning automata in cloud environment
    Najafizadegan, Negin
    Nazemi, Eslam
    Khajehvand, Vahid
    [J]. SOFTWARE-PRACTICE & EXPERIENCE, 2021, 51 (06): : 1352 - 1386
  • [8] USING DSM FOR THE MODULARIZATION OF SELF-OPTIMIZING SYSTEMS
    Gausemeier, Juergen
    Kahl, Sascha
    Steffen, Daniel
    [J]. PROCEEDINGS OF THE 9TH INTERNATIONAL DSM CONFERENCE, 2007, : 235 - +
  • [9] Towards a design methodology for self-optimizing systems
    Gausemeier, E
    Frank, U
    Schmidt, A
    Steffen, D
    [J]. ADVANCES IN DESIGN, 2006, : 61 - +
  • [10] Special Issue on Self-Optimizing Machining Systems
    Kakinuma, Yasuhiro
    Kono, Daisuke
    [J]. INTERNATIONAL JOURNAL OF AUTOMATION TECHNOLOGY, 2022, 16 (02) : 125 - 125