Undergraduate Course: Functional Programming and Specification (Level 9) (INFR09033)
|School||School of Informatics
||College||College of Science and Engineering
||Availability||Available to all students
|Credit level (Normal year taken)||SCQF Level 9 (Year 3 Undergraduate)
|Home subject area||Informatics
||Other subject area||None
||Taught in Gaelic?||No
|Course description||The course has two aims. The first is to provide an introduction to programming in Standard ML including the use of the facilities it offers for structuring programs into modules. Part of this is a review of material from the Functional Programming component of Inf1A, using Standard ML rather than Haskell, but more advanced material is also included. The second aim is to provide an introduction to formal methods for specification and development of programs, using the Extended ML specification framework as a vehicle. Simple proofs of properties of functions are interwoven with the first part of the course to link it with the second part.
Entry Requirements (not applicable to Visiting Students)
|| Students MUST have passed:
Informatics 2A - Processing Formal and Natural Languages (INFR08008) AND
Informatics 2B - Algorithms, Data Structures, Learning (INFR08009)
||Other requirements|| Successful completion of Year 2 of an Informatics Single or Combined Degree, or equivalent by permission of the School. Students must have a good background in some programming language together with a familiarity with basic notation from logic (logical connectives, quantifiers, etc.) and proofs using equational reasoning and induction.
MSc students should take the level 10 version of the course (INFR10043).
|Additional Costs|| None
Information for Visiting Students
|Displayed in Visiting Students Prospectus?||Yes
Course Delivery Information
|Not being delivered|
Summary of Intended Learning Outcomes
|1 - Students will be able to design a representation of an informally-described data structure in ML as a datatype, and translate an informal description of an algorithm into an ML function, making appropriate use of higher-order functions and other characteristic features of the functional programming paradigm.
2 - Students will be able to make effective use of the module facilities in ML to organize programs of about 1000 lines into appropriate units.
3 - Students will be able to use the notation of EML to formulate properties of first-order total ML functions, and to prove such properties using induction and methods of equational reasoning.
|Written Examination 75|
Assessed Assignments 25
Oral Presentations 0
Three written assignments, weighted equally: one on ML programming; one on the ML module system; one on specification and proof.
If delivered in semester 1, this course will have an option for semester 1 only visiting undergraduate students, providing assessment prior to the end of the calendar year.
||Functional programming in Standard ML: The functional paradigm. Polymorphic types, static typing and type inference. Recursion and induction. List processing. Higher-order functions. Eager and lazy evaluation. Imperative features. Signatures, structures, functors. Module hierarchy, sharing and data abstraction.
Specification and formal program development in Extended ML: Specification of ML functions and modules. Proving that a program is correct with respect to a specification of its intended behaviour. Refinement of specifications. Formal development of ML programs from EML specifications by modular decomposition and stepwise refinement.
Relevant QAA Computing Curriculum Sections: Comparative Programming Languages, Programming Fundamentals, Software Engineering
||* ***L. Paulson. ML for the Working Programmer, second edition. Cambridge University Press, 1996.
* **R. Harper. Programming in Standard ML. Carnegie Mellon University. Soon to be a book. Available on-line.
* ***D. Sannella. Formal program development in Extended ML for the working programmer.
* **S. Gilmore. Programming in Standard ML'97: A tutorial introduction. Edinburgh report ECS-LFCS-97-364, 1997
* *J. Ullman. Elements of ML Programming, second edition. Prentice Hall, 1997.
Timetabled Laboratories 0
Non-timetabled assessed assignments 25
Private Study/Other 47
|Course organiser||Dr Nigel Goddard
Tel: (0131 6)51 3091
|Course secretary||Miss Tamise Totterdell
Tel: 0131 650 9970