REU Site: TaMaLe - Testing and Machine Learning for Context-Driven Systems: Research Experience for Undergraduates (open access)

REU Site: TaMaLe - Testing and Machine Learning for Context-Driven Systems: Research Experience for Undergraduates

Data management plan for the grant, "REU Site: TaMaLe - Testing and Machine Learning for Context-Driven Systems: Research Experience for Undergraduates." TaMaLe (Testing and Machine Learning for Context-Driven Systems), a renewal Research Experience for Undergraduates (REU) Site at University of North Texas, engages 10 undergraduate students for 10 weeks with problems in the context-driven system domain. The students explore research problems to improve the reliability and security of context-driven systems. Context-driven systems, such as mobile apps, face constant streams of input from both users and context changes in their environments. Users interact with apps through touch and speech interfaces. These systems also respond to context events that occur in their environments such as changes to network connection, battery level, screen orientation, and more. The combined explosion of possible user events and context event sequences pose new challenges that require cost effective testing solutions. Students and mentors in this REU program work in small teams to develop and empirically evaluate new software testing techniques for context-driven systems using strategies such as reinforcement learning and combinatorial-based techniques.
Date: 2022-03-01/2025-02-28
Creator: Bryce, Renee & Tunc, Cihan
System: The UNT Digital Library
IUCRC Phase I University of North Texas: Center for Electric, Connected and Autonomous Technologies for Mobility (eCAT) (open access)

IUCRC Phase I University of North Texas: Center for Electric, Connected and Autonomous Technologies for Mobility (eCAT)

Data management plan for the grant "IUCRC Phase I University of North Texas: Center for Electric, Connected and Autonomous Technologies for Mobility (eCAT)."
Date: 2023-03-15/2028-02-29
Creator: Fu, Song
System: The UNT Digital Library
Research Experiences for Undergraduates Site: Interdisciplinary Research Experience on Accelerated Deep Learning through A Hardware-Software Collaborative Approach (open access)

Research Experiences for Undergraduates Site: Interdisciplinary Research Experience on Accelerated Deep Learning through A Hardware-Software Collaborative Approach

Data management plan for the grant, "REU Site: Interdisciplinary Research Experience on Accelerated Deep Learning through A Hardware-Software Collaborative Approach." This Research Experiences for Undergraduates (REU) Site Program at the University of North Texas will enhance the knowledge and research skills of a diverse cohort of undergraduate students through empowering, innovative, and interdisciplinary research experiences in developing Deep Learning applications and systems. The program aims to 1) expose undergraduate students to real-world and cutting-edge research focused on accelerated deep learning through combined hardware and software development; 2) encourage more undergraduate students to continue their academic careers and seek graduate degrees in computer science, computer engineering, and related disciplines; 3) develop research skills and improve communication and collaborative skills in undergraduate students.
Date: 2021-03-01/2024-02-29
Creator: Zhao, Hui & Albert, Mark
System: The UNT Digital Library