BiCAM-based automated scoring system for digital logic circuit diagrams

Abstract

Abstract In online education, it is critical for the quality of education to evaluate and grade the assignments or examinations that students upload to the system. However, it is time-consuming to determine how well the circuit drawings prepared for the digital logic course, which is a fundamental course in computer engineering and similar disciplines, are not only correct but also compatible with the truth table. Content-addressable memory (CAM), also known as associative memory, is a data storage and retrieval unit. Typically, it is used instead of the conventional memories in fast-paced and time-sensitive applications such as address lookup in Internet routers, databases, and pattern recognition. CAMs implement the search process by comparing the content itself with a key instead of finding the address like the conventional memories. To see the effect of using binary content-addressable memory-based memory on the time spent scoring hand or digital-drawn logic circuits, it is compared with various data structures commonly used in logic simulation programs. I found a significant relationship (O(1)), indicating that the proposed architecture reduces the time complexity in the search process. This expression is the same as time complexity in hash tables.