1. Machine learning and scientific computing need a lot of cycles; machines such as GPUs are complex to code. How do we automatically generate efficient code for these machines effectively. (Parallelism and Locality)
2. Can we use program analysis to automatically detect security bugs in programs? (Pointer analysis)
3. How do we automatically manage memory efficiently so users do not have to manage it themselves? (Garbage collection)
4. How do we make high-level programming languages efficient by optimizing the code? (Data-flow analysis)
5. The highest programming language is obviously natural language. Can we program our virtual assistant to perform compound tasks in natural language? We use machine learning techniques to map natural language into formal languages. Note: no prior knowledge in machine learning is needed. (Neural networks, Satisfiability Modulo Theories)

Note: The above shows that the theory, techniques and algorithms in a compiler are applicable to a wide range of problems in software design and development. The goal of this course is to provide students with the theory and techniques in program analysis and optimization.