Map

Converts one array into another.

• e.g., (map (lambda (x) (* x x)) lst)
• Notice: If the transformation has no side effects, this can be easily parallelized. This is one key motivation for pure functional programming.
• Do some of the In-Class problems.
• Do the “bound” in-class problem.
• Show how to use closures to write a general “bound” function

Fold/Reduce

“Reduce” is a common pattern wherein you

1. Iterate over a list
2. At each iteration, you use the current item to modify a “partial” answer. (Consider sum and max as examples.)

• This function goes by many different names across programming languages:
  • Javascript: Reduce
  • Ruby: Inject
  • Kava: Fold
• The “partial” result goes by many names:
  • “Partial”
  • “Accumulator”
  • “Memo”
• To use fold in kawa you must import a library: (require 'list-lib)
  • API for this library: https://srfi.schemers.org/srfi-1/srfi-1.html
• In Kawa the parameters to fold are in this order:
  1. lambda
  2. initial value
  3. list
• The parameters to the lambda are in this order
  1. item
  2. partial

• These orders change from language to language!

• Sum values in an array

(require 'list-lib)
(display 
    (fold (lambda (item partial) (+ item partial)) 0 '(1 2 3 4 5 6)))
(newline)

• Have students implement Max.
  • Notice the challenge of choosing the first value.
• Show reduce

(display
    (reduce (lambda (item partial) (if (> item partial) item partial)) 99999999 lst)
)
(newline)

• count_positive using fold

• Implement map using fold.