Efficient Testing of Multivariable Systems

Software systems, and automotive software in particular, are becoming increasingly configurable to fulfill customer needs. New methods such as product line engineering facilitate the development and enhance the efficiency of such systems. In modern, versatile systems, the number of theoretically possible variants easily exceeds the number of actually built products. This produces two challenges for quality assurance and especially testing. First, the costs of conventional test methods increase substantially with every tested variant. And secondly, it is no longer feasible to build every possible variant for the purpose of testing. Hence, efficient criteria for selecting variants for testing are necessary. In this contribution, we propose a new test design method that enables systematic sampling of variants from test cases. We present six optimization criteria to enable control of test effort and test quality by sampling variants with different characteristics. This approach is inherently different to conventional design methods, where firstly variants are selected for testing and then test cases are designed for each variant. Finally, we demonstrate and discuss the feasibility of our approach and compare the results to established test methods for multivariable systems.

• Record URL:
  https://doi.org/10.4271/2017-01-1676
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/01487191
• Supplemental Notes:
  • Abstract reprinted with permission of SAE International.
• Authors:
  • Lackner, Hartmut
• Conference:
  • WCX™ 17: SAE World Congress Experience
  • Location: Detroit Michigan, United States
  • Date: 2017-4-4 to 2017-4-6
• Publication Date: 2017-3-28

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Serial:
  • SAE Technical Paper
  • Publisher: Society of Automotive Engineers (SAE)
  • ISSN: 0148-7191
  • EISSN: 2688-3627
  • Serial URL: http://papers.sae.org/

Subject/Index Terms

• TRT Terms: Automotive engineering; Optimization; Product development; Quality assurance; Software; Test procedures; Vehicle tests
• Subject Areas: Design; Highways; Vehicles and Equipment;

Filing Info

• Accession Number: 01730988
• Record Type: Publication
• Source Agency: SAE International
• Report/Paper Numbers: 2017-01-1676
• Files: TRIS, SAE
• Created Date: Mar 30 2017 10:48AM