  In this study, we assess the efficacy of employing the ChatGPT language model
to generate solutions for coding exercises within an undergraduate Java
programming course. ChatGPT, a large-scale, deep learning-driven natural
language processing model, is capable of producing programming code based on
textual input. Our evaluation involves analyzing ChatGPT-generated solutions
for 80 diverse programming exercises and comparing them to the correct
solutions. Our findings indicate that ChatGPT accurately generates Java
programming solutions, which are characterized by high readability and
well-structured organization. Additionally, the model can produce alternative,
memory-efficient solutions. However, as a natural language processing model,
ChatGPT struggles with coding exercises containing non-textual descriptions or
class files, leading to invalid solutions. In conclusion, ChatGPT holds
potential as a valuable tool for students seeking to overcome programming
challenges and explore alternative approaches to solving coding problems. By
understanding its limitations, educators can design coding exercises that
minimize the potential for misuse as a cheating aid while maintaining their
validity as assessment tools.
