San Francisco, CA, United States of America

Mark Art

USPTO Granted Patents = 1 

Average Co-Inventor Count = 10.0

ph-index = 1


Company Filing History:


Years Active: 2024

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1 patent (USPTO):Explore Patents

Title: Mark Art - Innovator in Program Modeling

Introduction

Mark Art is a notable inventor based in San Francisco, CA. He has made significant contributions to the field of program modeling, particularly through his innovative patent. His work focuses on enhancing the efficiency and effectiveness of software testing.

Latest Patents

Mark Art holds a patent for an "Adaptively Generated Program Model." This invention presents a system and method to adaptively generate a program model. The process involves receiving source code of a program to be tested for code issues, along with a set of predefined patterns to be tested in the source code. Feature configuration data is generated by determining a set of features corresponding to the received set of predefined patterns. A set of program models is identified by selecting, for each feature in the set of features, a program model from among a plurality of program models that is optimized for the feature. A dynamic program model is built based on the identified set of program models, which is adapted to resolve each of the patterns included in the received set of predefined patterns. The source code is then tested for code issues by extracting from the dynamic program model instances of each of the set of predefined patterns. Mark Art has 1 patent to his name.

Career Highlights

Mark Art is currently employed at GitLab B.V., where he continues to develop innovative solutions in software engineering. His work has been instrumental in advancing the capabilities of program testing and modeling.

Collaborations

Mark collaborates with talented individuals such as Julian Thome and Isaac Dawson, contributing to a dynamic and innovative work environment.

Conclusion

Mark Art is a distinguished inventor whose work in program modeling has the potential to significantly improve software testing processes. His contributions are paving the way for more efficient programming practices in the tech industry.

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