17945829. OPTIMIZED TEST SELECTION simplified abstract (GM Cruise Holdings LLC)
Contents
- 1 OPTIMIZED TEST SELECTION
OPTIMIZED TEST SELECTION
Organization Name
Inventor(s)
Aravindha Ganesh Ramakrishnan of Santa Clara CA (US)
Ritchie Lee of Sunnyvale CA (US)
Ishan Singh of San Francisco CA (US)
Saurabh Gupta of San Carlos CA (US)
Brooke Colburn of Spokane WA (US)
OPTIMIZED TEST SELECTION - A simplified explanation of the abstract
This abstract first appeared for US patent application 17945829 titled 'OPTIMIZED TEST SELECTION
Simplified Explanation
The disclosed technology provides solutions for identifying autonomous vehicle (AV) tests that offer the desired level of test coverage for testing or validating the AV software stack.
- Steps for extracting a first set of features associated with a first set of test programs
- Tagging each respective test program with metadata tags
- Identifying a second set of features associated with an updated set of AV program code
- Determining if the tags match the features of the updated AV program code
- Executing the test programs based on the tags
Potential Applications
This technology can be applied in the automotive industry for testing and validating autonomous vehicle software, ensuring safety and reliability on the road.
Problems Solved
This technology addresses the challenge of efficiently identifying and executing relevant tests for autonomous vehicle software, improving the overall testing process and software quality.
Benefits
The benefits of this technology include increased test coverage, improved software reliability, and enhanced safety of autonomous vehicles on the road.
Potential Commercial Applications
Potential commercial applications of this technology include autonomous vehicle companies, software development firms, and automotive testing facilities.
Possible Prior Art
One possible prior art could be automated testing tools used in software development to improve test coverage and efficiency.
Unanswered Questions
How does this technology impact the overall development timeline of autonomous vehicles?
This technology can potentially streamline the testing process, leading to faster development cycles and quicker deployment of autonomous vehicles on the market.
What are the potential limitations or challenges of implementing this technology in real-world AV testing environments?
Challenges may include integrating this technology with existing testing frameworks, ensuring compatibility with different AV software stacks, and managing the scalability of testing processes.
Original Abstract Submitted
Aspects of the disclosed technology provide solutions for identifying autonomous vehicle (AV) tests that provide a desired level of test coverage for testing or validating the AV software stack. A process of the disclosed technology can include steps for extracting a first set of features associated with a first set of test programs, tagging each respective test program with metadata tags, and identifying a second set of features associated with an updated set of AV program code. In some aspects, the process may further include steps for determining if the one or more tags match one or more features of the second set of features associated with the updated AV program code, and executing the respective test programs based on the one or more tags. Systems and machine-readable media are also provided.
