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Topics Covered | Turnaround Time | Price (USD) |
---|---|---|
Syntax and Semantics | 24 hours | $50 |
Pattern Matching | 48 hours | $40 |
Data Types and Modules | 72 hours | $35 |
Recursive Functions | 24 hours | $55 |
Higher-Order Functions | 48 hours | $45 |
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- Standard ML Assignment Help
- Perks of Obtaining Help with Standard ML Assignment from Experts
- Efficient Fibonacci Calculation with Memoization in Standard ML
- Top Reasons to Use Our Standard ML Assignment Help Service
- Step-by-Step Guide to Submit Assignment to Standard ML Assignment Experts
- Zero-Plagiarism Assurance from Our Standard ML Assignment Helpers
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Efficient Fibonacci Calculation with Memoization in Standard ML
(* Memoization to store previously computed Fibonacci numbers *)
fun make_fib_table () =
let
(* Create a table to store Fibonacci numbers *)
val table = Array.tabulate (100, fn i => if i = 0 orelse i = 1 then i else 0)
fun fib n =
if n < 0 orelse n >= Array.length table then
raise Fail "Index out of bounds"
else
let
(* Check if the value is already computed *)
val _ = if Array.sub (table, n) = 0 andalso n > 1 then
Array.update (table, n, fib (n - 1) + fib (n - 2))
else ()
in
Array.sub (table, n)
end
in
fib
end
(* Fibonacci number calculator with memoization *)
val fib = (make_fib_table ())
(* Example usage *)
val result_10 = fib 10
Explanation:
- Recursive Function with Memoization: The fib function is a classic example of how to use recursion for calculating Fibonacci numbers. Memoization (storing previously computed results) optimizes the recursive solution, demonstrating an essential technique for improving performance in recursive algorithms. This teaches students about the trade-offs between time complexity and space complexity.
- Pattern Matching and Functional Programming: The use of pattern matching and functional constructs like Array.tabulate and Array.update showcases Standard ML’s functional programming features. This helps students become familiar with idiomatic ways to manage state and mutable data in a functional programming paradigm.
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