# Arrays and Termination

To write efficient code, it is important to select appropriate data structures. Linked lists have their place: in some applications, the ability to share the tails of lists is very important. However, most use cases for a variable-length sequential collection of data are better served by arrays, which have both less memory overhead and better locality.

Arrays, however, have two drawbacks relative to lists:

1. Arrays are accessed through indexing, rather than by pattern matching, which imposes proof obligations in order to maintain safety.
2. A loop that processes an entire array from left to right is a tail-recursive function, but it does not have an argument that decreases on each call.

Making effective use of arrays requires knowing how to prove to Lean that an array index is in bounds, and how to prove that an array index that approaches the size of the array also causes the program to terminate. Both of these are expressed using an inequality proposition, rather than propositional equality.

## Inequality

Because different types have different notions of ordering, inequality is governed by two type classes, called LE and LT. The table in the section on standard type classes describes how these classes relate to the syntax:

ExpressionDesugaringClass Name
x < yLT.lt x yLT
x ≤ yLE.le x yLE
x > yLT.lt y xLT
x ≥ yLE.le y xLE

In other words, a type may customize the meaning of the < and ≤ operators, while > and ≥ derive their meanings from < and ≤. The classes LT and LE have methods that return propositions rather than Bools:

class LE (α : Type u) where
le : α → α → Prop

class LT (α : Type u) where
lt : α → α → Prop


The instance of LE for Nat delegates to Nat.le:

instance : LE Nat where
le := Nat.le


Defining Nat.le requires a feature of Lean that has not yet been presented: it is an inductively-defined relation.

### Inductively-Defined Propositions, Predicates, and Relations

Nat.le is an inductively-defined relation. Just as inductive can be used to create new datatypes, it can also be used to create new propositions. When a proposition takes an argument, it is referred to as a predicate that may be true for some, but not all, potential arguments. Propositions that take multiple arguments are called relations.

Each constructor of an inductively defined proposition is a way to prove it. In other words, the declaration of the proposition describes the different forms of evidence that it is true. A proposition with no arguments that has a single constructor can be quite easy to prove:

inductive EasyToProve : Prop where
| heresTheProof : EasyToProve


The proof consists of using its constructor:

theorem fairlyEasy : EasyToProve := by
constructor


In fact, the proposition True, which should always be easy to prove, is defined just like EasyToProve:

inductive True : Prop where
| intro : True


Inductively-defined propositions that don't take arguments are not nearly as interesting as inductively-defined datatypes. This is because data is interesting in its own right—the natural number 3 is different from the number 35, and someone who has ordered 3 pizzas will be upset if 35 arrive at their door 30 minutes later. The constructors of a proposition describe ways in which the proposition can be true, but once a proposition has been proved, there is no need to know which underlying constructors were used. This is why most interesting inductively-defined types in the Prop universe take arguments.

The inductively-defined predicate IsThree states that its argument is three:

inductive IsThree : Nat → Prop where
| isThree : IsThree 3


The mechanism used here is just like indexed families such as HasCol, except the resulting type is a proposition that can be proved rather than data that can be used.

Using this predicate, it is possible to prove that three is indeed three:

theorem three_is_three : IsThree 3 := by
constructor


Similarly, IsFive is a predicate that states that its argument is 5:

inductive IsFive : Nat → Prop where
| isFive : IsFive 5


If a number is three, then the result of adding two to it should be five. This can be expressed as a theorem statement:

theorem three_plus_two_five : IsThree n → IsFive (n + 2) := by
skip


The resulting goal has a function type:

unsolved goals
n : Nat
⊢ IsThree n → IsFive (n + 2)


Thus, the intro tactic can be used to convert the argument into an assumption:

theorem three_plus_two_five : IsThree n → IsFive (n + 2) := by
intro three

unsolved goals
n : Nat
three : IsThree n
⊢ IsFive (n + 2)


Given the assumption that n is three, it should be possible to use the constructor of IsFive to complete the proof:

theorem three_plus_two_five : IsThree n → IsFive (n + 2) := by
intro three
constructor


However, this results in an error:

tactic 'constructor' failed, no applicable constructor found
n : Nat
three : IsThree n
⊢ IsFive (n + 2)


This error occurs because n + 2 is not definitionally equal to 5. In an ordinary function definition, dependent pattern matching on the assumption three could be used to refine n to 3. The tactic equivalent of dependent pattern matching is cases, which has a syntax similar to that of induction:

theorem three_plus_two_five : IsThree n → IsFive (n + 2) := by
intro three
cases three with
| isThree => skip


In the remaining case, n has been refined to 3:

unsolved goals
case isThree
⊢ IsFive (3 + 2)


Because 3 + 2 is definitionally equal to 5, the constructor is now applicable:

theorem three_plus_two_five : IsThree n → IsFive (n + 2) := by
intro three
cases three with
| isThree => constructor


The standard false proposition False has no constructors, making it impossible to provide direct evidence for. The only way to provide evidence for False is if an assumption is itself impossible, similarly to how nomatch can be used to mark code that the type system can see is unreachable. As described in the initial Interlude on proofs, the negation Not A is short for A → False. Not A can also be written ¬A.

It is not the case that four is three:

theorem four_is_not_three : ¬ IsThree 4 := by
skip


The initial proof goal contains Not:

unsolved goals
⊢ ¬IsThree 4


The fact that it's actually a function type can be exposed using simp:

theorem four_is_not_three : ¬ IsThree 4 := by
simp [Not]

unsolved goals
⊢ IsThree 4 → False


Because the goal is a function type, intro can be used to convert the argument into an assumption. There is no need to keep simp, as intro can unfold the definition of Not itself:

theorem four_is_not_three : ¬ IsThree 4 := by
intro h

unsolved goals
h : IsThree 4
⊢ False


In this proof, the cases tactic solves the goal immediately:

theorem four_is_not_three : ¬ IsThree 4 := by
intro h
cases h


Just as a pattern match on a Vect String 2 doesn't need to include a case for Vect.nil, a proof by cases over IsThree 4 doesn't need to include a case for isThree.

### Inequality of Natural Numbers

The definition of Nat.le has a parameter and an index:

inductive Nat.le (n : Nat) : Nat → Prop
| refl : Nat.le n n
| step : Nat.le n m → Nat.le n (m + 1)


The parameter n is the number that should be smaller, while the index is the number that should be greater than or equal to n. The refl constructor is used when both numbers are equal, while the step constructor is used when the index is greater than n.

From the perspective of evidence, a proof that $$n \leq k$$ consists of finding some number $$d$$ such that $$n + d = m$$. In Lean, the proof then consists of a Nat.le.refl constructor wrapped by $$d$$ instances of Nat.le.step. Each step constructor adds one to its index argument, so $$d$$ step constructors adds $$d$$ to the larger number. For example, evidence that four is less than or equal to seven consists of three steps around a refl:

theorem four_le_seven : 4 ≤ 7 :=
open Nat.le in
step (step (step refl))


The strict less-than relation is defined by adding one to the number on the left:

def Nat.lt (n m : Nat) : Prop :=
Nat.le (n + 1) m

instance : LT Nat where
lt := Nat.lt


Evidence that four is strictly less than seven consists of two step's around a refl:

theorem four_lt_seven : 4 < 7 :=
open Nat.le in
step (step refl)


This is because 4 < 7 is equivalent to 5 ≤ 7.

## Proving Termination

The function Array.map transforms an array with a function, returning a new array that contains the result of applying the function to each element of the input array. Writing it as a tail-recursive function follows the usual pattern of delegating to a function that passes the output array in an accumulator. The accumulator is initialized with an empty array. The accumulator-passing helper function also takes an argument that tracks the current index into the array, which starts at 0:

def Array.map (f : α → β) (arr : Array α) : Array β :=
arrayMapHelper f arr Array.empty 0


The helper should, at each iteration, check whether the index is still in bounds. If so, it should loop again with the transformed element added to the end of the accumulator and the index incremented by 1. If not, then it should terminate and return the accumulator. An initial implementation of this code fails because Lean is unable to prove that the array index is valid:

def arrayMapHelper (f : α → β) (arr : Array α) (soFar : Array β) (i : Nat) : Array β :=
if i < arr.size then
arrayMapHelper f arr (soFar.push (f arr[i])) (i + 1)
else soFar

failed to prove index is valid, possible solutions:
- Use have-expressions to prove the index is valid
- Use a[i]! notation instead, runtime check is perfomed, and 'Panic' error message is produced if index is not valid
- Use a[i]? notation instead, result is an Option type
- Use a[i]'h notation instead, where h is a proof that index is valid
α : Type ?u.1704
β : Type ?u.1707
f : α → β
arr : Array α
soFar : Array β
i : Nat
⊢ i < Array.size arr


However, the conditional expression already checks the precise condition that the array index's validity demands (namely, i < arr.size). Adding a name to the if resolves the issue, because it adds an assumption that the array indexing tactic can use:

def arrayMapHelper (f : α → β) (arr : Array α) (soFar : Array β) (i : Nat) : Array β :=
if inBounds : i < arr.size then
arrayMapHelper f arr (soFar.push (f arr[i])) (i + 1)
else soFar


Lean does not, however, accept the modified program, because the recursive call is not made on an argument to one of the input constructors. In fact, both the accumulator and the index grow, rather than shrinking:

fail to show termination for
arrayMapHelper
with errors
argument #6 was not used for structural recursion
failed to eliminate recursive application
arrayMapHelper f✝ arr (Array.push soFar (f✝ arr[i])) (i + 1)

structural recursion cannot be used

failed to prove termination, use termination_by to specify a well-founded relation


Nevertheless, this function terminates, so simply marking it partial would be unfortunate.

Why does arrayMapHelper terminate? Each iteration checks whether the index i is still in bounds for the array arr. If so, i is incremented and the loop repeats. If not, the program terminates. Because arr.size is a finite number, i can be incremented only a finite number of times. Even though no argument to the function decreases on each call, arr.size - i decreases toward zero.

Lean can be instructed to use another expression for termination by providing a termination_by clause at the end of a definition. The termination_by clause has two components: names for the function's arguments and an expression using those names that should decrease on each call. For arrayMapHelper, the final definition looks like this:

def arrayMapHelper (f : α → β) (arr : Array α) (soFar : Array β) (i : Nat) : Array β :=
if inBounds : i < arr.size then
arrayMapHelper f arr (soFar.push (f arr[i])) (i + 1)
else soFar
termination_by arrayMapHelper _ arr _ i _ => arr.size - i


A similar termination proof can be used to write Array.find, a function that finds the first element in an array that satisfies a Boolean function and returns both the element and its index:

def Array.find (arr : Array α) (p : α → Bool) : Option (Nat × α) :=
findHelper arr p 0


Once again, the helper function terminates because arr.size - i decreases as i increases:

def findHelper (arr : Array α) (p : α → Bool) (i : Nat) : Option (Nat × α) :=
if h : i < arr.size then
let x := arr[i]
if p x then
some (i, x)
else findHelper arr p (i + 1)
else none
termination_by findHelper arr p i => arr.size - i


Not all termination arguments are as quite as simple as this one. However, the basic structure of identifying some expression based on the function's arguments that will decrease in each call occurs in all termination proofs. Sometimes, creativity can be required in order to figure out just why a function terminates, and sometimes Lean requires additional proofs in order to accept the termination argument.

## Exercises

• Implement a ForM (Array α) instance on arrays using a tail-recursive accumulator-passing function and a termination_by clause.
• Implement a function to reverse arrays using a tail-recursive accumulator-passing function that doesn't need a termination_by clause.
• Reimplement Array.map, Array.find, and the ForM instance using for ... in ... loops in the identity monad and compare the resulting code.
• Reimplement array reversal using a for ... in ... loop in the identity monad. Compare it to the tail-recursive function.