Comp Sci / Sfwr Eng 3FP3, Term 2 2018/19
Term 2: Monday, Wednesday 11:30-12:20, Friday 13:30-14:20, KTH B132
Dr. J. Carette, ITB-168 , ext 26869, email: firstname.lastname@example.org.
Musa Al-hassy (alhassm)
The calendar description says:
Functional programming; lists and algebraic data types, pattern matching,
parametric polymorphism, higher-order functions, reasoning about programs; lazy
and strict evaluation; programming with monads; domain-specific languages.
textbookThe Craft of Functional Programming by Simon Thompson.
The course content will generally follow the textbook. There will be few ``lectures''
per se; most classes will consist of either live coding or in-class exercises.
Will be posted soon. But generally, all the material from 2DM3 and 2FA3 will be
assumed, as well as a certain 'programming maturity'.
- Students should know and understand:
- Logical Formalism
- Calculational Proofs in Propositional and Predicate Logic
- Induction, Recursion
- Discrete Structures: Sets, Functions, Relations
- Abstract data types
- Students should be able to
- Write programs in imperative and OO languages
- Debug programs
- Use the command line to call compilers and other tools
- Students should know and understand
- The basic types in functional languages
- What parametric polymorphism is
- The difference between lazy and strict evaluation
- Understand overloading (type classes)
- Students should be able to
- Use lists and other algebraic data types to solve problems
- Use pattern-matching on ADTs
- Give general types for their functions
- Use and create higher-order functions
- Reason about the correctness of their functions
- Write properties that their functions should satisfy
- Use randomized testing
- Use monads (and do notation) for encapsulating effects
- Build small DSLs and interpreters for them
Note that not all objectives will be measured for marks.
Some of the graduate attributes below will be measured (probably
most), in some fashion. These are measurements for the purposes
of understanding your overall state in terms of the attributes which
the CEAB deems important for engineers (and will be done whether you are
in CS or SE). Some will be measured
through assignments, presentations and deliverables (and worth marks),
while others will be done via other means not directly tied
to course marks.
2 Problem Analysis
- 1 A knowledge base for engineering
- 1.1 Competence in Mathematics
- 1.4 Competence in Specialized Engineering knowledge
- 2.1 Demonstrates an ability to identify reasonable assumptions including identification of uncertainties and imprecise information that could or should be made before a solution path is proposed
- 2.2 (Demonstrates an ability to identify reasonable assumptions (including identification of uncertainties and imprecise information) that could or should be made before a solution path is proposed
- 3.1 Recognizes and discusses applicable theory knowledge base
- 3.2 Selects appropriate model and methods and identifies assumptions and constraints
5 Use of engineering tools
- 4.2 Recognizes and follows engineering design principles including appropriate consideration of environmental, social and economic aspects as well as health and safety issues
- 4.3 Proposes solutions to open-ended problems
- 5.2 Demonstrates an ability to use modern/state of the art tools
Section to be completed.
The latest version of this outline and the most "up-to date"
information as well as hand-outs can be found on the course web page.
(Or go to my home page and then to the course page).
Avenue will be used for handing in assignments. Either Discord or Slack will be used
for further coordination (TBD).
The assignments will be worth 50%, two midterms (each 15%) and a
final worth 20%.
As usual, there will be (significant) bonus parts on the assignments.
Marking schemes will be strict: code that does not compile will be worth
very few marks (if any). You will be better off submiting a partial implementation
that compiles that one that is 'almost done' but doesn't typecheck.
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The following illustrates only three forms of academic dishonesty:
- Plagiarism, e.g. the submission of work that is not one’s own or for which other credit has been obtained.
- Improper collaboration in group work.
- Copying or using unauthorized aids in tests and examinations.
Individual assignments have to be solved by one person only,
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or using any books or information found on the web has to
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People who let other people copy are as guilty as the ones who copy.
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