Abstract: Producing codes with high quality is one of the most important skills for students majoring in computer science. Performance is one of the key factors to measure the software quality. Many programmers, including students, often ignore the performance but mainly focus on code functionality in software development; such coding style potentially increases software maintenance costs. Cultivating good coding styles should happen in the college via various programming courses, such as data structures, programming languages, compilers, parallel computing, operating systems, and many others. However, it is challenging to help students intuitively understand the performance issues. To address these challenges, we develop several tools to help students understand program performance and integrate these tools into undergraduate teaching. These tools analyze programs written in different languages, such as C/C++, Java, and Python, pinpointing and visualizing performance inefficiencies due to poor data structures, suboptimal algorithms, inefficient compiler code generation. These insights help students deepen their knowledge of various CS courses and become qualified programmers.

Short Bio: Shuyin Jiao is a Llecturer in the Department of Computer Science at the College of William and Mary. She serves on the undergraduate curriculum committee in the department. Her primary focus is on undergraduate teaching to fulfill the department requirement. Besides teaching, she supervises undergraduate and master students doing research in the area of program analysis. She obtained her Ph.D. from the University of Houston in 2015 and joined the College of William and Mary in the same year. During her Ph.D. study, she was a recipient of KALSI Research Award, ABS Scholarship, and AMOCO Minority Scholarship