A study of techniques for interpreting and compiling programming languages, implementing them in a typed functional programming language (e.g., OCaml, Haskell). The module will outline a whole compiler from source to machine code, but will focus in depth on key algorithms and techniques. Possible in-depth topics include:
• writing interpreters,
• Hindley-Milner type inference,
• register allocation,
• garbage collection,
• abstract interpretation,
• static single assignment form.
The implemented language will be based on a simple imperative (e.g., Pascal-like) language with some extensions to address advanced topics in data layout (e.g., closures, objects, pattern matching). The course will be organized around a simple, but complete, example compiler that the student will have to understand and modify.
Total contact hours: 35 hours
Private study hours: 115 hours
Total study hours: 150 hours
Main assessment methods
Coursework: 30 hours (60%)
2 hour unseen written exam (40%)
Reassessment methods
Like for like.
Aho, A., Lam, M., Sethi, R., and Ullman, J. (2007). Compilers: Principles, Techniques, and Tools 2nd ed., Prentice Hall.
Appel, A.W. (2004) Modern compiler implementation in ML, Cambridge University Press
Cooper, K., and Torczan, L. (2011). Engineering a compiler, Morgan Kaufmann.
Minsky, Y., Madhavapeddy, A., and Hickey, J (2013). Real world OCaml, O'Reilly Media.
See the library reading list for this module (Canterbury)
The intended subject specific learning outcomes.
On successfully completing the module students will be able to:
1 Understand how a computer program in a high-level, imperative language is translated into machine code;
2 Understand how a program is executed, including run-time system support;
3 Understand a variety of techniques that a compiler uses to improve the efficiency of its generated code;
4 Understand how to represent programs as data in a typed functional language
5 Implement basic compiler optimisation techniques;
6 Evaluate a program's performance; and
7 Work with and modify an existing code base.
The intended generic learning outcomes.
On successfully completing the module students will be able to:
1 Be able to clearly communicate the results of performance experiments;
2 Be able to manage their own learning and development, through self-directed study and working on continuous assessment.
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