More Inequalities
Lean's built-in proof automation is sufficient to check that arrayMapHelper
and findHelper
terminate.
All that was needed was to provide an expression whose value decreases with each recursive call.
However, Lean's built-in automation is not magic, and it often needs some help.
Merge Sort
One example of a function whose termination proof is non-trivial is merge sort on List
.
Merge sort consists of two phases: first, a list is split in half.
Each half is sorted using merge sort, and then the results are merged using a function that combines two sorted lists into a larger sorted list.
The base cases are the empty list and the singleton list, both of which are already considered to be sorted.
To merge two sorted lists, there are two basic cases to consider:
- If one of the input lists is empty, then the result is the other list.
- If both lists are non-empty, then their heads should be compared. The result of the function is the smaller of the two heads, followed by the result of merging the remaining entries of both lists.
This is not structurally recursive on either list. The recursion terminates because an entry is removed from one of the two lists in each recursive call, but it could be either list. Behind the scenes, Lean uses this fact to prove that it terminates:
def merge [Ord α] (xs : List α) (ys : List α) : List α :=
match xs, ys with
| [], _ => ys
| _, [] => xs
| x'::xs', y'::ys' =>
match Ord.compare x' y' with
| .lt | .eq => x' :: merge xs' (y' :: ys')
| .gt => y' :: merge (x'::xs') ys'
A simple way to split a list is to add each entry in the input list to two alternating output lists:
def splitList (lst : List α) : (List α × List α) :=
match lst with
| [] => ([], [])
| x :: xs =>
let (a, b) := splitList xs
(x :: b, a)
This splitting function is structurally recursive.
Merge sort checks whether a base case has been reached. If so, it returns the input list. If not, it splits the input, and merges the result of sorting each half:
def mergeSort [Ord α] (xs : List α) : List α :=
if h : xs.length < 2 then
match xs with
| [] => []
| [x] => [x]
else
let halves := splitList xs
merge (mergeSort halves.fst) (mergeSort halves.snd)
Lean's pattern match compiler is able to tell that the assumption h
introduced by the if
that tests whether xs.length < 2
rules out lists longer than one entry, so there is no "missing cases" error.
However, even though this program always terminates, it is not structurally recursive, and Lean is unable to automatically discover a decreasing measure:
fail to show termination for
mergeSort
with errors
failed to infer structural recursion:
Not considering parameter α of mergeSort:
it is unchanged in the recursive calls
Not considering parameter #2 of mergeSort:
it is unchanged in the recursive calls
Cannot use parameter xs:
failed to eliminate recursive application
mergeSort halves.fst
failed to prove termination, possible solutions:
- Use `have`-expressions to prove the remaining goals
- Use `termination_by` to specify a different well-founded relation
- Use `decreasing_by` to specify your own tactic for discharging this kind of goal
α : Type u_1
xs : List α
h : ¬xs.length < 2
halves : List α × List α := splitList xs
⊢ sizeOf (splitList xs).fst < sizeOf xs
The reason it terminates is that splitList
always returns lists that are shorter than its input, at least when applied to lists that contain at least two elements.
Thus, the length of halves.fst
and halves.snd
are less than the length of xs
.
This can be expressed using a termination_by
clause:
def mergeSort [Ord α] (xs : List α) : List α :=
if h : xs.length < 2 then
match xs with
| [] => []
| [x] => [x]
else
let halves := splitList xs
merge (mergeSort halves.fst) (mergeSort halves.snd)
termination_by xs.length
With this clause, the error message changes.
Instead of complaining that the function isn't structurally recursive, Lean instead points out that it was unable to automatically prove that (splitList xs).fst.length < xs.length
:
failed to prove termination, possible solutions:
- Use `have`-expressions to prove the remaining goals
- Use `termination_by` to specify a different well-founded relation
- Use `decreasing_by` to specify your own tactic for discharging this kind of goal
α : Type u_1
xs : List α
h : ¬xs.length < 2
halves : List α × List α := splitList xs
⊢ (splitList xs).fst.length < xs.length
Splitting a List Makes it Shorter
It will also be necessary to prove that (splitList xs).snd.length < xs.length
.
Because splitList
alternates between adding entries to the two lists, it is easiest to prove both statements at once, so the structure of the proof can follow the algorithm used to implement splitList
.
In other words, it is easiest to prove that ∀(lst : List), (splitList lst).fst.length < lst.length ∧ (splitList lst).snd.length < lst.length
.
Unfortunately, the statement is false.
In particular, splitList []
is ([], [])
. Both output lists have length 0
, which is not less than 0
, the length of the input list.
Similarly, splitList ["basalt"]
evaluates to (["basalt"], [])
, and ["basalt"]
is not shorter than ["basalt"]
.
However, splitList ["basalt", "granite"]
evaluates to (["basalt"], ["granite"])
, and both of these output lists are shorter than the input list.
It turns out that the lengths of the output lists are always less than or equal to the length of the input list, but they are only strictly shorter when the input list contains at least two entries. It turns out to be easiest to prove the former statement, then extend it to the latter statement. Begin with a theorem statement:
theorem splitList_shorter_le (lst : List α) :
(splitList lst).fst.length ≤ lst.length ∧
(splitList lst).snd.length ≤ lst.length := by
skip
unsolved goals
α : Type u_1
lst : List α
⊢ (splitList lst).fst.length ≤ lst.length ∧ (splitList lst).snd.length ≤ lst.length
Because splitList
is structurally recursive on the list, the proof should use induction.
The structural recursion in splitList
fits a proof by induction perfectly: the base case of the induction matches the base case of the recursion, and the inductive step matches the recursive call.
The induction
tactic gives two goals:
theorem splitList_shorter_le (lst : List α) :
(splitList lst).fst.length ≤ lst.length ∧
(splitList lst).snd.length ≤ lst.length := by
induction lst with
| nil => skip
| cons x xs ih => skip
unsolved goals
case nil
α : Type u_1
⊢ (splitList []).fst.length ≤ [].length ∧ (splitList []).snd.length ≤ [].length
unsolved goals
case cons
α : Type u_1
x : α
xs : List α
ih : (splitList xs).fst.length ≤ xs.length ∧ (splitList xs).snd.length ≤ xs.length
⊢ (splitList (x :: xs)).fst.length ≤ (x :: xs).length ∧ (splitList (x :: xs)).snd.length ≤ (x :: xs).length
The goal for the nil
case can be proved by invoking the simplifier and instructing it to unfold the definition of splitList
, because the length of the empty list is less than or equal to the length of the empty list.
Similarly, simplifying with splitList
in the cons
case places Nat.succ
around the lengths in the goal:
theorem splitList_shorter_le (lst : List α) :
(splitList lst).fst.length ≤ lst.length ∧
(splitList lst).snd.length ≤ lst.length := by
induction lst with
| nil => simp [splitList]
| cons x xs ih =>
simp [splitList]
unsolved goals
case cons
α : Type u_1
x : α
xs : List α
ih : (splitList xs).fst.length ≤ xs.length ∧ (splitList xs).snd.length ≤ xs.length
⊢ (splitList xs).snd.length ≤ xs.length ∧ (splitList xs).fst.length ≤ xs.length + 1
This is because the call to List.length
consumes the head of the list x :: xs
, converting it to a Nat.succ
, in both the length of the input list and the length of the first output list.
Writing A ∧ B
in Lean is short for And A B
.
And
is a structure type in the Prop
universe:
structure And (a b : Prop) : Prop where
intro ::
left : a
right : b
In other words, a proof of A ∧ B
consists of the And.intro
constructor applied to a proof of A
in the left
field and a proof of B
in the right
field.
The cases
tactic allows a proof to consider each constructor of a datatype or each potential proof of a proposition in turn.
It corresponds to a match
expression without recursion.
Using cases
on a structure results in the structure being broken apart, with an assumption added for each field of the structure, just as a pattern match expression extracts the field of a structure for use in a program.
Because structures have only one constructor, using cases
on a structure does not result in additional goals.
Because ih
is a proof of List.length (splitList xs).fst ≤ List.length xs ∧ List.length (splitList xs).snd ≤ List.length xs
, using cases ih
results in an assumption that List.length (splitList xs).fst ≤ List.length xs
and an assumption that List.length (splitList xs).snd ≤ List.length xs
:
theorem splitList_shorter_le (lst : List α) :
(splitList lst).fst.length ≤ lst.length ∧
(splitList lst).snd.length ≤ lst.length := by
induction lst with
| nil => simp [splitList]
| cons x xs ih =>
simp [splitList]
cases ih
unsolved goals
case cons.intro
α : Type u_1
x : α
xs : List α
left✝ : (splitList xs).fst.length ≤ xs.length
right✝ : (splitList xs).snd.length ≤ xs.length
⊢ (splitList xs).snd.length ≤ xs.length ∧ (splitList xs).fst.length ≤ xs.length + 1
Because the goal of the proof is also an And
, the constructor
tactic can be used to apply And.intro
, resulting in a goal for each argument:
theorem splitList_shorter_le (lst : List α) :
(splitList lst).fst.length ≤ lst.length ∧
(splitList lst).snd.length ≤ lst.length := by
induction lst with
| nil => simp [splitList]
| cons x xs ih =>
simp [splitList]
cases ih
constructor
unsolved goals
case cons.intro.left
α : Type u_1
x : α
xs : List α
left✝ : (splitList xs).fst.length ≤ xs.length
right✝ : (splitList xs).snd.length ≤ xs.length
⊢ (splitList xs).snd.length ≤ xs.length
case cons.intro.right
α : Type u_1
x : α
xs : List α
left✝ : (splitList xs).fst.length ≤ xs.length
right✝ : (splitList xs).snd.length ≤ xs.length
⊢ (splitList xs).fst.length ≤ xs.length + 1
The left
goal is identical to the left✝
assumption, so the assumption
tactic dispatches it:
theorem splitList_shorter_le (lst : List α) :
(splitList lst).fst.length ≤ lst.length ∧
(splitList lst).snd.length ≤ lst.length := by
induction lst with
| nil => simp [splitList]
| cons x xs ih =>
simp [splitList]
cases ih
constructor
case left => assumption
unsolved goals
case cons.intro.right
α : Type u_1
x : α
xs : List α
left✝ : (splitList xs).fst.length ≤ xs.length
right✝ : (splitList xs).snd.length ≤ xs.length
⊢ (splitList xs).fst.length ≤ xs.length + 1
The right
goal resembles the right✝
assumption, except the goal adds a + 1
only to the length of the input list.
It's time to prove that the inequality holds.
Adding One to the Greater Side
The inequality needed to prove splitList_shorter_le
is ∀(n m : Nat), n ≤ m → n ≤ Nat.succ m
.
The incoming assumption that n ≤ m
essentially tracks the difference between n
and m
in the number of Nat.le.step
constructors.
Thus, the proof should add an extra Nat.le.step
in the base case.
Starting out, the statement reads:
theorem Nat.le_succ_of_le : n ≤ m → n ≤ m + 1 := by
skip
unsolved goals
n m : Nat
⊢ n ≤ m → n ≤ m + 1
The first step is to introduce a name for the assumption that n ≤ m
:
theorem Nat.le_succ_of_le : n ≤ m → n ≤ m + 1 := by
intro h
unsolved goals
n m : Nat
h : n ≤ m
⊢ n ≤ m + 1
The proof is by induction on this assumption:
theorem Nat.le_succ_of_le : n ≤ m → n ≤ m + 1 := by
intro h
induction h with
| refl => skip
| step _ ih => skip
In the case for refl
, where n = m
, the goal is to prove that n ≤ n + 1
:
unsolved goals
case refl
n m : Nat
⊢ n ≤ n + 1
In the case for step
, the goal is to prove that n ≤ m + 1
under the assumption that n ≤ m
:
unsolved goals
case step
n m m✝ : Nat
a✝ : n.le m✝
ih : n ≤ m✝ + 1
⊢ n ≤ m✝.succ + 1
For the refl
case, the step
constructor can be applied:
theorem Nat.le_succ_of_le : n ≤ m → n ≤ m + 1 := by
intro h
induction h with
| refl => constructor
| step _ ih => skip
unsolved goals
case refl.a
n m : Nat
⊢ n.le n
After step
, refl
can be used, which leaves only the goal for step
:
theorem Nat.le_succ_of_le : n ≤ m → n ≤ m + 1 := by
intro h
induction h with
| refl => constructor; constructor
| step _ ih => skip
unsolved goals
case step
n m m✝ : Nat
a✝ : n.le m✝
ih : n ≤ m✝ + 1
⊢ n ≤ m✝.succ + 1
For the step, applying the step
constructor transforms the goal into the induction hypothesis:
theorem Nat.le_succ_of_le : n ≤ m → n ≤ m + 1 := by
intro h
induction h with
| refl => constructor; constructor
| step _ ih => constructor
unsolved goals
case step.a
n m m✝ : Nat
a✝ : n.le m✝
ih : n ≤ m✝ + 1
⊢ n.le (m✝ + 1)
The final proof is as follows:
theorem Nat.le_succ_of_le : n ≤ m → n ≤ m + 1 := by
intro h
induction h with
| refl => constructor; constructor
| step => constructor; assumption
To reveal what's going on behind the scenes, the apply
and exact
tactics can be used to indicate exactly which constructor is being applied.
The apply
tactic solves the current goal by applying a function or constructor whose return type matches, creating new goals for each argument that was not provided, while exact
fails if any new goals would be needed:
theorem Nat.le_succ_of_le : n ≤ m → n ≤ m + 1 := by
intro h
induction h with
| refl => apply Nat.le.step; exact Nat.le.refl
| step _ ih => apply Nat.le.step; exact ih
The proof can be golfed:
theorem Nat.le_succ_of_le (h : n ≤ m) : n ≤ m + 1:= by
induction h <;> repeat (first | constructor | assumption)
In this short tactic script, both goals introduced by induction
are addressed using repeat (first | constructor | assumption)
.
The tactic first | T1 | T2 | ... | Tn
means to use try T1
through Tn
in order, using the first tactic that succeeds.
In other words, repeat (first | constructor | assumption)
applies constructors as long as it can, and then attempts to solve the goal using an assumption.
The proof can be shortened even further by using omega
, a built-in solver for linear arithmetic:
theorem Nat.le_succ_of_le (h : n ≤ m) : n ≤ m + 1:= by
omega
Finally, the proof can be written as a recursive function:
theorem Nat.le_succ_of_le : n ≤ m → n ≤ m + 1
| .refl => .step .refl
| .step h => .step (Nat.le_succ_of_le h)
Each style of proof can be appropriate to different circumstances. The detailed proof script is useful in cases where beginners may be reading the code, or where the steps of the proof provide some kind of insight. The short, highly-automated proof script is typically easier to maintain, because automation is frequently both flexible and robust in the face of small changes to definitions and datatypes. The recursive function is typically both harder to understand from the perspective of mathematical proofs and harder to maintain, but it can be a useful bridge for programmers who are beginning to work with interactive theorem proving.
Finishing the Proof
Now that both helper theorems have been proved, the rest of splitList_shorter_le
will be completed quickly.
The current proof state has one goal remaining:
unsolved goals
case cons.intro.right
α : Type u_1
x : α
xs : List α
left✝ : (splitList xs).fst.length ≤ xs.length
right✝ : (splitList xs).snd.length ≤ xs.length
⊢ (splitList xs).fst.length ≤ xs.length + 1
Using Nat.le_succ_of_le
together with the right✝
assumption completes the proof:
theorem splitList_shorter_le (lst : List α) :
(splitList lst).fst.length ≤ lst.length ∧ (splitList lst).snd.length ≤ lst.length := by
induction lst with
| nil => simp [splitList]
| cons x xs ih =>
simp [splitList]
cases ih
constructor
case left => assumption
case right =>
apply Nat.le_succ_of_le
assumption
The next step is to return to the actual theorem that is needed to prove that merge sort terminates: that so long as a list has at least two entries, both results of splitting it are strictly shorter.
theorem splitList_shorter (lst : List α) (_ : lst.length ≥ 2) :
(splitList lst).fst.length < lst.length ∧
(splitList lst).snd.length < lst.length := by
skip
unsolved goals
α : Type u_1
lst : List α
x✝ : lst.length ≥ 2
⊢ (splitList lst).fst.length < lst.length ∧ (splitList lst).snd.length < lst.length
Pattern matching works just as well in tactic scripts as it does in programs.
Because lst
has at least two entries, they can be exposed with match
, which also refines the type through dependent pattern matching:
theorem splitList_shorter (lst : List α) (_ : lst.length ≥ 2) :
(splitList lst).fst.length < lst.length ∧
(splitList lst).snd.length < lst.length := by
match lst with
| x :: y :: xs =>
skip
unsolved goals
α : Type u_1
lst : List α
x y : α
xs : List α
x✝ : (x :: y :: xs).length ≥ 2
⊢ (splitList (x :: y :: xs)).fst.length < (x :: y :: xs).length ∧
(splitList (x :: y :: xs)).snd.length < (x :: y :: xs).length
Simplifying using splitList
removes x
and y
, resulting in the computed lengths of lists each gaining a + 1
:
theorem splitList_shorter (lst : List α) (_ : lst.length ≥ 2) :
(splitList lst).fst.length < lst.length ∧
(splitList lst).snd.length < lst.length := by
match lst with
| x :: y :: xs =>
simp [splitList]
unsolved goals
α : Type u_1
lst : List α
x y : α
xs : List α
x✝ : (x :: y :: xs).length ≥ 2
⊢ (splitList xs).fst.length < xs.length + 1 ∧ (splitList xs).snd.length < xs.length + 1
Replacing simp
with simp +arith
removes these + 1
s, because simp +arith
makes use of the fact that n + 1 < m + 1
implies n < m
:
theorem splitList_shorter (lst : List α) (_ : lst.length ≥ 2) :
(splitList lst).fst.length < lst.length ∧
(splitList lst).snd.length < lst.length := by
match lst with
| x :: y :: xs =>
simp +arith [splitList]
unsolved goals
α : Type u_1
lst : List α
x y : α
xs : List α
x✝ : (x :: y :: xs).length ≥ 2
⊢ (splitList xs).fst.length ≤ xs.length ∧ (splitList xs).snd.length ≤ xs.length
This goal now matches splitList_shorter_le
, which can be used to conclude the proof:
theorem splitList_shorter (lst : List α) (_ : lst.length ≥ 2) :
(splitList lst).fst.length < lst.length ∧
(splitList lst).snd.length < lst.length := by
match lst with
| x :: y :: xs =>
simp +arith [splitList]
apply splitList_shorter_le
The facts needed to prove that mergeSort
terminates can be pulled out of the resulting And
:
theorem splitList_shorter_fst (lst : List α) (h : lst.length ≥ 2) :
(splitList lst).fst.length < lst.length :=
splitList_shorter lst h |>.left
theorem splitList_shorter_snd (lst : List α) (h : lst.length ≥ 2) :
(splitList lst).snd.length < lst.length :=
splitList_shorter lst h |>.right
Merge Sort Terminates
Merge sort has two recursive calls, one for each sub-list returned by splitList
.
Each recursive call will require a proof that the length of the list being passed to it is shorter than the length of the input list.
It's usually convenient to write a termination proof in two steps: first, write down the propositions that will allow Lean to verify termination, and then prove them.
Otherwise, it's possible to put a lot of effort into proving the propositions, only to find out that they aren't quite what's needed to establish that the recursive calls are on smaller inputs.
The sorry
tactic can prove any goal, even false ones.
It isn't intended for use in production code or final proofs, but it is a convenient way to "sketch out" a proof or program ahead of time.
Any definitions or theorems that use sorry
are annotated with a warning.
The initial sketch of mergeSort
's termination argument that uses sorry
can be written by copying the goals that Lean couldn't prove into have
-expressions.
In Lean, have
is similar to let
.
When using have
, the name is optional.
Typically, let
is used to define names that refer to interesting values, while have
is used to locally prove propositions that can be found when Lean is searching for evidence that an array lookup is in-bounds or that a function terminates.
def mergeSort [Ord α] (xs : List α) : List α :=
if h : xs.length < 2 then
match xs with
| [] => []
| [x] => [x]
else
let halves := splitList xs
have : halves.fst.length < xs.length := by
sorry
have : halves.snd.length < xs.length := by
sorry
merge (mergeSort halves.fst) (mergeSort halves.snd)
termination_by xs.length
The warning is located on the name mergeSort
:
declaration uses 'sorry'
Because there are no errors, the proposed propositions are enough to establish termination.
The proofs begin by applying the helper theorems:
def mergeSort [Ord α] (xs : List α) : List α :=
if h : xs.length < 2 then
match xs with
| [] => []
| [x] => [x]
else
let halves := splitList xs
have : halves.fst.length < xs.length := by
apply splitList_shorter_fst
have : halves.snd.length < xs.length := by
apply splitList_shorter_snd
merge (mergeSort halves.fst) (mergeSort halves.snd)
termination_by xs.length
Both proofs fail, because splitList_shorter_fst
and splitList_shorter_snd
both require a proof that xs.length ≥ 2
:
unsolved goals
case h
α : Type ?u.31067
inst✝ : Ord α
xs : List α
h : ¬xs.length < 2
halves : List α × List α := splitList xs
⊢ xs.length ≥ 2
To check that this will be enough to complete the proof, add it using sorry
and check for errors:
def mergeSort [Ord α] (xs : List α) : List α :=
if h : xs.length < 2 then
match xs with
| [] => []
| [x] => [x]
else
let halves := splitList xs
have : xs.length ≥ 2 := by sorry
have : halves.fst.length < xs.length := by
apply splitList_shorter_fst
assumption
have : halves.snd.length < xs.length := by
apply splitList_shorter_snd
assumption
merge (mergeSort halves.fst) (mergeSort halves.snd)
termination_by xs.length
Once again, there is only a warning.
declaration uses 'sorry'
There is one promising assumption available: h : ¬List.length xs < 2
, which comes from the if
.
Clearly, if it is not the case that xs.length < 2
, then xs.length ≥ 2
.
The omega
tactic solves this goal, and the program is now complete:
def mergeSort [Ord α] (xs : List α) : List α :=
if h : xs.length < 2 then
match xs with
| [] => []
| [x] => [x]
else
let halves := splitList xs
have : xs.length ≥ 2 := by
omega
have : halves.fst.length < xs.length := by
apply splitList_shorter_fst
assumption
have : halves.snd.length < xs.length := by
apply splitList_shorter_snd
assumption
merge (mergeSort halves.fst) (mergeSort halves.snd)
termination_by xs.length
The function can be tested on examples:
#eval mergeSort ["soapstone", "geode", "mica", "limestone"]
["geode", "limestone", "mica", "soapstone"]
#eval mergeSort [5, 3, 22, 15]
[3, 5, 15, 22]
Division as Iterated Subtraction
Just as multiplication is iterated addition and exponentiation is iterated multiplication, division can be understood as iterated subtraction. The very first description of recursive functions in this book presents a version of division that terminates when the divisor is not zero, but that Lean does not accept. Proving that division terminates requires the use of a fact about inequalities.
Lean cannot prove that this definition of division terminates:
def div (n k : Nat) : Nat :=
if n < k then
0
else
1 + div (n - k) k
fail to show termination for
div
with errors
failed to infer structural recursion:
Cannot use parameter n:
failed to eliminate recursive application
div (n - k) k
Cannot use parameter k:
failed to eliminate recursive application
div (n - k) k
Could not find a decreasing measure.
The basic measures relate at each recursive call as follows:
(<, ≤, =: relation proved, ? all proofs failed, _: no proof attempted)
n k
1) 9:10-23 ≤ =
Please use `termination_by` to specify a decreasing measure.
That's a good thing, because it doesn't!
When k
is 0
, value of n
does not decrease, so the program is an infinite loop.
Rewriting the function to take evidence that k
is not 0
allows Lean to automaically prove termination:
def div (n k : Nat) (ok : k ≠ 0) : Nat :=
if h : n < k then
0
else
1 + div (n - k) k ok
This definition of div
terminates because the first argument n
is smaller on each recursive call.
This can be expressed using a termination_by
clause:
def div (n k : Nat) (ok : k ≠ 0) : Nat :=
if h : n < k then
0
else
1 + div (n - k) k ok
termination_by n
Exercises
Prove the following theorems:
- For all natural numbers \( n \), \( 0 < n + 1 \).
- For all natural numbers \( n \), \( 0 \leq n \).
- For all natural numbers \( n \) and \( k \), \( (n + 1) - (k + 1) = n - k \)
- For all natural numbers \( n \) and \( k \), if \( k < n \) then \( n \neq 0 \)
- For all natural numbers \( n \), \( n - n = 0 \)
- For all natural numbers \( n \) and \( k \), if \( n + 1 < k \) then \( n < k \)