Can't prove seemingly trivial equality in Ada Spark - ada

So I have those two files.
testing.ads
package Testing with
SPARK_Mode
is
function InefficientEuler1Sum2 (N: Natural) return Natural;
procedure LemmaForTesting with
Ghost,
Post => (InefficientEuler1Sum2(0) = 0);
end Testing;
and testing.adb
package body Testing with
SPARK_Mode
is
function InefficientEuler1Sum2 (N: Natural) return Natural is
Sum: Natural := 0;
begin
for I in 0..N loop
if I mod 3 = 0 then
Sum := Sum + I;
end if;
if I mod 5 = 0 then
Sum := Sum + I;
end if;
if I mod 15 = 0 then
Sum := Sum - I;
end if;
end loop;
return Sum;
end InefficientEuler1Sum2;
procedure LemmaForTesting
is
begin
null;
end LemmaForTesting;
end Testing;
When I run SPARK -> Prove File, I get such message:
GNATprove
E:\Ada\Testing SPARK\search\src\testing.ads
10:14 medium: postcondition might fail
cannot prove InefficientEuler1Sum2(0) = 0
Why is that so? What I have misunderstood or maybe done wrong?
Thanks in advance.

To prove the trivial equality, you need to make sure it is covered by the function's post-condition. If so, you can prove the equality using a simple Assert statement as shown in the example below. No lemma is needed at this point.
However, a post-condition is not enough to prove the absence of runtime errors (AoRTE): given the allowable input range of the function, the summation may, for some values of N, overflow. To mitigate the issue, you need to bound the input values of N and show the prover that the value for Sum remains bounded during the loop using a loop invariant (see here, here and here for some background information on loop invariants). For illustration purposes, I've chosen a conservative bound of (2 * I) * I, which will severely restrict the allowable range of input values, but does allow the prover to proof the absence of runtime errors in the example.
testing.ads
package Testing with SPARK_Mode is
-- Using the loop variant in the function body, one can guarantee that no
-- overflow will occur for all values of N in the range
--
-- 0 .. Sqrt (Natural'Last / 2) <=> 0 .. 32767
--
-- Of course, this bound is quite conservative, but it may be enough for a
-- given application.
--
-- The post-condition can be used to prove the trivial equality as stated
-- in your question.
subtype Domain is Natural range 0 .. 32767;
function Inefficient_Euler_1_Sum_2 (N : Domain) return Natural
with Post => (if N = 0 then Inefficient_Euler_1_Sum_2'Result = 0);
end Testing;
testing.adb
package body Testing with SPARK_Mode is
-------------------------------
-- Inefficient_Euler_1_Sum_2 --
-------------------------------
function Inefficient_Euler_1_Sum_2 (N : Domain) return Natural is
Sum: Natural := 0;
begin
for I in 0 .. N loop
if I mod 3 = 0 then
Sum := Sum + I;
end if;
if I mod 5 = 0 then
Sum := Sum + I;
end if;
if I mod 15 = 0 then
Sum := Sum - I;
end if;
-- Changed slightly since initial post, no effect on Domain.
pragma Loop_Invariant (Sum <= (2 * I) * I);
end loop;
return Sum;
end Inefficient_Euler_1_Sum_2;
end Testing;
main.adb
with Testing; use Testing;
procedure Main with SPARK_Mode is
begin
pragma Assert (Inefficient_Euler_1_Sum_2 (0) = 0);
end Main;
output
$ gnatprove -Pdefault.gpr -j0 --level=1 --report=all
Phase 1 of 2: generation of Global contracts ...
Phase 2 of 2: flow analysis and proof ...
main.adb:5:19: info: assertion proved
testing.adb:13:15: info: division check proved
testing.adb:14:24: info: overflow check proved
testing.adb:16:15: info: division check proved
testing.adb:17:24: info: overflow check proved
testing.adb:19:15: info: division check proved
testing.adb:20:24: info: overflow check proved
testing.adb:20:24: info: range check proved
testing.adb:23:33: info: loop invariant preservation proved
testing.adb:23:33: info: loop invariant initialization proved
testing.adb:23:42: info: overflow check proved
testing.adb:23:46: info: overflow check proved
testing.ads:17:19: info: postcondition proved
Summary logged in /obj/gnatprove/gnatprove.out

Related

How to make Pre and Post conditions for recursive functions in SPARK?

I'm translating an exercise I made in Dafny into SPARK, where one verifies a tail recursive function against a recursive one. The Dafny source (censored, because it might still be used for classes):
function Sum(n:nat):nat
decreases n
{
if n==0 then n else n+Sum(n-1)
}
method ComputeSum(n:nat) returns (s:nat)
ensures s == Sum(n)
{
s := 0;
// ...censored...
}
What I got in SPARK so far:
function Sum (n : in Natural) return Natural
is
begin
if n = 0 then
return n;
else
return n + Sum(n - 1);
end if;
end Sum;
function ComputeSum(n : in Natural) return Natural
with
Post => ComputeSum'Result = Sum(n)
is
s : Natural := 0;
begin
-- ...censored...
return s;
end ComputeSum;
I cannot seem to figure out how to express the decreases n condition (which now that I think about it might be a little odd... but I got graded for it a few years back so who am I to judge, and the question remains how to get it done). As a result I get warnings of possible overflow and/or infinite recursion.
I'm guessing there is a pre or post condition to be added. Tried Pre => n <= 1 which obviously does not overflow, but I still get the warning. Adding Post => Sum'Result <= n**n on top of that makes the warning go away, but that condition gets a "postcondition might fail" warning, which isn't right, but guess the prover can't tell. Also not really the expression I should check against, but I cannot seem to figure what other Post I'm looking for. Possibly something very close to the recursive expression, but none of my attempts work. Must be missing out on some language construct...
So, how could I express the recursive constraints?
Edit 1:
Following links to this SO answer and this SPARK doc section, I tried this:
function Sum (n : in Natural) return Natural
is
(if n = 0 then 0 else n + Sum(n - 1))
with
Pre => (n in 0 .. 2),
Contract_Cases => (n = 0 => Sum'Result = 0,
n >= 1 => Sum'Result = n + Sum(n - 1)),
Subprogram_Variant => (Decreases => n);
However getting these warnings from SPARK:
spark.adb:32:30: medium: overflow check might fail [reason for check: result of addition must fit in a 32-bits machine integer][#0]
spark.adb:36:56: warning: call to "Sum" within its postcondition will lead to infinite recursion
If you want to prove that the result of some tail-recursive summation function equals the result of a given recursive summation function for some value N, then it should, in principle, suffice to only define the recursive function (as an expression function) without any post-condition. You then only need to mention the recursive (expression) function in the post-condition of the tail-recursive function (note that there was no post-condition (ensures) on the recursive function in Dafny either).
However, as one of SPARK's primary goal is to proof the absence of runtime errors, you must have to prove that overflow cannot occur and for this reason, you do need a post-condition on the recursive function. A reasonable choice for such a post-condition is, as #Jeffrey Carter already suggested in the comments, the explicit summation formula for arithmetic progression:
Sum (N) = N * (1 + N) / 2
The choice is actually very attractive as with this formula we can now also functionally validate the recursive function itself against a well-known mathematically explicit expression for computing the sum of a series of natural numbers.
Unfortunately, using this formula as-is will only bring you somewhere half-way. In SPARK (and Ada as well), pre- and post-conditions are optionally executable (see also RM 11.4.2 and section 5.11.1 in the SPARK Reference Guide) and must therefore themselves be free of any runtime errors. Therefore, using the formula as-is will only allow you to prove that no overflow occurs for any positive number up until
max N s.t. N * (1 + N) <= Integer'Last <-> N = 46340
as in the post-condition, the multiplication is not allowed to overflow either (note that Natural'Last = Integer'Last = 2**31 - 1).
To work around this, you'll need to make use of the big integers package that has been introduced in the Ada 202x standard library (see also RM A.5.6; this package is already included in GNAT CE 2021 and GNAT FSF 11.2). Big integers are unbounded and computations with these integers never overflow. Using these integers, one can proof that overflow will not occur for any positive number up until
max N s.t. N * (1 + N) / 2 <= Natural'Last <-> N = 65535 = 2**16 - 1
The usage of these integers in a post-condition is illustrated in the example below.
Some final notes:
The Subprogram_Variant aspect is only needed to prove that a recursive subprogram will eventually terminate. Such a proof of termination must be requested explicitly by adding an annotation to the function (also shown in the example below and as discussed in the SPARK documentation pointed out by #egilhh in the comments). The Subprogram_Variant aspect is, however, not needed for your initial purpose: proving that the result of some tail-recursive summation function equals the result of a given recursive summation function for some value N.
To compile a program that uses functions from the new Ada 202x standard library, use compiler option -gnat2020.
While I use a subtype to constrain the range of permissible values for N, you could also use a precondition. This should not make any difference. However, in SPARK (and Ada as well), it is in general considered to be a best practise to express contraints using (sub)types as much as possible.
Consider counterexamples as possible clues rather than facts. They may or may not make sense. Counterexamples are optionally generated by some solvers and may not make sense. See also the section 7.2.6 in the SPARK user’s guide.
main.adb
with Ada.Numerics.Big_Numbers.Big_Integers;
procedure Main with SPARK_Mode is
package BI renames Ada.Numerics.Big_Numbers.Big_Integers;
use type BI.Valid_Big_Integer;
-- Conversion functions.
function To_Big (Arg : Integer) return BI.Valid_Big_Integer renames BI.To_Big_Integer;
function To_Int (Arg : BI.Valid_Big_Integer) return Integer renames BI.To_Integer;
subtype Domain is Natural range 0 .. 2**16 - 1;
function Sum (N : Domain) return Natural is
(if N = 0 then 0 else N + Sum (N - 1))
with
Post => Sum'Result = To_Int (To_Big (N) * (1 + To_Big (N)) / 2),
Subprogram_Variant => (Decreases => N);
-- Request a proof that Sum will terminate for all possible values of N.
pragma Annotate (GNATprove, Terminating, Sum);
begin
null;
end Main;
output (gnatprove)
$ gnatprove -Pdefault.gpr --output=oneline --report=all --level=1 --prover=z3
Phase 1 of 2: generation of Global contracts ...
Phase 2 of 2: flow analysis and proof ...
main.adb:13:13: info: subprogram "Sum" will terminate, terminating annotation has been proved
main.adb:14:30: info: overflow check proved
main.adb:14:32: info: subprogram variant proved
main.adb:14:39: info: range check proved
main.adb:16:18: info: postcondition proved
main.adb:16:31: info: range check proved
main.adb:16:53: info: predicate check proved
main.adb:16:69: info: division check proved
main.adb:16:71: info: predicate check proved
Summary logged in [...]/gnatprove.out
ADDENDUM (in response to comment)
So you can add the post condition as a recursive function, but that does not help in proving the absence of overflow; you will still have to provide some upper bound on the function result in order to convince the prover that the expression N + Sum (N - 1) will not cause an overflow.
To check the absence of overflow during the addition, the prover will consider all possible values that Sum might return according to it's specification and see if at least one of those value might cause the addition to overflow. In the absence of an explicit bound in the post condition, Sum might, according to its return type, return any value in the range Natural'Range. That range includes Natural'Last and that value will definitely cause an overflow. Therefore, the prover will report that the addition might overflow. The fact that Sum never returns that value given its allowable input values is irrelevant here (that's why it reports might). Hence, a more precise upper bound on the return value is required.
If an exact upper bound is not available, then you'll typically fallback onto a more conservative bound like, in this case, N * N (or use saturation math as shown in the Fibonacci example from the SPARK user manual, section 5.2.7, but that approach does change your function which might not be desirable).
Here's an alternative example:
example.ads
package Example with SPARK_Mode is
subtype Domain is Natural range 0 .. 2**15;
function Sum (N : Domain) return Natural
with Post =>
Sum'Result = (if N = 0 then 0 else N + Sum (N - 1)) and
Sum'Result <= N * N; -- conservative upper bound if the closed form
-- solution to the recursive function would
-- not exist.
end Example;
example.adb
package body Example with SPARK_Mode is
function Sum (N : Domain) return Natural is
begin
if N = 0 then
return N;
else
return N + Sum (N - 1);
end if;
end Sum;
end Example;
output (gnatprove)
$ gnatprove -Pdefault.gpr --output=oneline --report=all
Phase 1 of 2: generation of Global contracts ...
Phase 2 of 2: flow analysis and proof ...
example.adb:8:19: info: overflow check proved
example.adb:8:28: info: range check proved
example.ads:7:08: info: postcondition proved
example.ads:7:45: info: overflow check proved
example.ads:7:54: info: range check proved
Summary logged in [...]/gnatprove.out
I landed in something that sometimes works, which I think is enough for closing the title question:
function Sum (n : in Natural) return Natural
is
(if n = 0 then 0 else n + Sum(n - 1))
with
Pre => (n in 0 .. 10), -- works with --prover=z3, not Default (CVC4)
-- Pre => (n in 0 .. 100), -- not working - "overflow check might fail, e.g. when n = 2"
Subprogram_Variant => (Decreases => n),
Post => ((n = 0 and then Sum'Result = 0)
or (n > 0 and then Sum'Result = n + Sum(n - 1)));
-- Contract_Cases => (n = 0 => Sum'Result = 0,
-- n > 0 => Sum'Result = n + Sum(n - 1)); -- warning: call to "Sum" within its postcondition will lead to infinite recursion
-- Contract_Cases => (n = 0 => Sum'Result = 0,
-- n > 0 => n + Sum(n - 1) = Sum'Result); -- works
-- Contract_Cases => (n = 0 => Sum'Result = 0,
-- n > 0 => Sum'Result = n * (n + 1) / 2); -- works and gives good overflow counterexamples for high n, but isn't really recursive
Command line invocation in GNAT Studio (Ctrl+Alt+F), --counterproof=on and --prover=z3 my additions to it:
gnatprove -P%PP -j0 %X --output=oneline --ide-progress-bar --level=0 -u %fp --counterexamples=on --prover=z3
Takeaways:
Subprogram_Variant => (Decreases => n) is required to tell the prover n decreases for each recursive invocation, just like the Dafny version.
Works inconsistently for similar contracts, see commented Contract_Cases.
Default prover (CVC4) fails, using Z3 succeeds.
Counterproof on fail makes no sense.
n = 2 presented as counterproof for range 0 .. 100, but not for 0 .. 10.
Possibly related to this mention in the SPARK user guide: However, note that since the counterexample is always generated only using CVC4 prover, it can just explain why this prover cannot prove the property.
Cleaning between changing options required, e.g. --prover.

Why my loop invariant might not be preserved by any iteration?

I'm trying to write a code in Spark that computes the value of the polynomial using the Horner method. The variable Result is calculated by Horner, and the variable Z is calculated in the classical way. I've done a lot of different tests and my loop invariant is always true. However, I get the message:
loop invariant might not be preserved by an arbitrary iteration
Are there any cases where the loop invariant doesn't work or do you need to add some more conditions to the invariant?
Here's my main func which call my Horner function:
with Ada.Integer_Text_IO;
use Ada.Integer_Text_IO;
with Poly;
use Poly;
procedure Main is
X : Integer;
A : Vector (0 .. 2);
begin
X := 2;
A := (5, 10, 15);
Put(Horner(X, A));
end Main;
And Horner function:
package body Poly with SPARK_Mode is
function Horner (X : Integer; A : Vector)
return Integer
is
Result : Integer := 0;
Z : Integer := 0;
begin
for i in reverse A'Range loop
pragma Loop_Invariant (Z=Result*(X**(i+1)));
Result := Result*X + A(i);
Z := Z + A(i)*X**(i);
end loop;
pragma Assert (Result = Z);
return Result;
end Horner;
end Poly;
How is Vector defined? Is it something like
type Vector is array(Integer range <>) of Float;
In this case maybe the condition could fail if some indexes of A are negative. Also, does the invariant hold even if the first index of A is not zero? Maybe another case when the invariant fails is when A'Last = Integer'Last; in this case the i+1 would overflow.
Usually SPARK gives a reason, a counterexample, when it is not able to prove something. I would suggest you to check that, it can give you an idea of when the invariant fails. Keep in mind that the counterexamples are sometimes some very extreme case such as A'Last = Integer'Last. If this is the case you need to tell SPARK that A'Last = Integer'Last will never happen, maybe by defining a specific subtype for Vector index or by adding a contract to your function.

Ada constraint error: Discriminant check failed. What does this mean?

I've tried searching the docs and the code, but I'm unable to find what this is and therefore how to correct it.
Scenario:
I'm using the Ada SPARK vectors library and I have the following code:
package MyPackage
with SPARK_Mode => On
is
package New_Vectors is new Formal_Vectors (Index_Type => test, Element_Type => My_Element.Object);
type Object is private;
private
type Object is
record
Data : New_Vectors.Vector (Block_Vectors.Last_Count);
Identifier : Identifier_Range;
end record;
I get the error when the code calls:
function Make (Identifier : Identifier_Range) return Object is
begin
return (
Data => New_Vectors.Empty_Vector,
Identifier => Identifier);
end Make;
Pointing to Empty_Vector. The difficulty is that Empty_Vector defines the Capacity as 0 which appears to be leading to the problem. Now I'm not sure then how to deal with that as Capacity seems to be in the type definition (having looked in a-cofove.ads).
So basically I'm stuck as to how to resolve this; or quite how to spot this happening in future.
Your analysis is correct. The error occurs because you attempt to assign an empty vector (i.e. a vector with capacity 0) to a vector with capacity Block_Vectors.Last_Count (which appears to be non-zero).
You actually do not need to initialize the vector explicitly in order to use it. A default initialization (using <>, see, for example, here) suffices as shown in de example below.
However, in order to prove the absence of runtime errors, you do need to explicitly clear the vector using Clear. The Empty_Vector function can then be used to in assertions that check if a vector is empty or not as shown in the example below. The example can be shown to be free of runtime errors using gnatprove. For example by opening the prove settings via menu SPARK > Prove in GNAT Studio, selecting "Report checks moved" in the "General" section (top left) and then running the analysis by selecting "Execute" (bottom right).
main.adb
with Ada.Text_IO; use Ada.Text_IO;
with Ada.Containers.Formal_Vectors;
procedure Main with SPARK_Mode is
package My_Vectors is new Ada.Containers.Formal_Vectors
(Index_Type => Natural,
Element_Type => Integer);
use My_Vectors;
type Object is record
Data : Vector (Capacity => 10); -- Max. # of elements: 10
Value : Integer;
end record;
-- Initialize with default value (i.e. <>), no explicit initialization needed.
Obj : Object :=
(Data => <>,
Value => 42);
begin
-- Clear the vector, required for the assertions to be proven.
Clear (Obj.Data);
-- Assert that the vector is not empty.
pragma Assert (Obj.Data = Empty_Vector);
-- Populate the vector with some elements.
Append (Obj.Data, 4);
Append (Obj.Data, 5);
Append (Obj.Data, 6);
-- Assert that the vector is populated.
pragma Assert (Obj.Data /= Empty_Vector);
-- Show the contents of Obj.Data.
Put_Line ("Contents of Obj.Data:");
for I in Natural range 0 .. Natural (Length (Obj.Data)) - 1 loop
Put_Line ("[" & I'Image & "]" & Element (Obj.Data, I)'Image);
end loop;
New_Line;
-- or, alternatively using an iterator ...
declare
I : Extended_Index := Iter_First (Obj.Data);
begin
while Iter_Has_Element (Obj.Data, I) loop
Put_Line ("[" & I'Image & "]" & Element (Obj.Data, I)'Image);
I := Iter_Next (Obj.Data, I);
end loop;
end;
New_Line;
-- Show the contents of Obj.Value.
Put_Line ("Contents of Obj.Value:");
Put_Line (Obj.Value'Image);
New_Line;
end Main;
output
Contents of Obj.Data:
[ 0] 4
[ 1] 5
[ 2] 6
[ 0] 4
[ 1] 5
[ 2] 6
Contents of Obj.Value:
42

My code in Pascal does not want to work correctly. What is the problem in?

I am writing program: sum of real numbers using recursive function.
What is wrong with it? It shows me just last entered numebr.
type
Indexy = 1..100;
TPoleReal = array [Indexy] of Real;
var
j: word;
r, realRes: real;
tpr: TPoleReal;
function SoucetCisel(n: TPoleReal; j: word): real;
begin
if j>0 then begin
SoucetCisel:=SoucetCisel + n[j];
j:=j-1;
end
end;
begin i:=0; j:=0;
while not seekeof do begin
read(r); Inc(j);
tpr[j]:=r;
writeln(j, ' ', tpr[j]);
end;
realRes:= SoucetCisel(tpr, j);
writeln(realRes);
end.
For debugging purposes I suggest you simplify the main part of your code to
begin
i:=0;
j:=0;
tpr[j] := 1;
Inc(j);
tpr[2] := 2;
realRes:= SoucetCisel(tpr, j);
writeln(realRes);
end.
That should make it make it much easier to appreciate what the problem is.
The first problem with your SoucetCisel function is that it isn't actually recursive.
A recursive function is one which calls itself with altered arguments, as in the
archetypical Factorial function
function Factorial(N : Integer)
begin
if N = 1 then
Factorial := 1
else
Factorial := N * Factorial(N - 1);
end;
The recursive call in this is the line
Factorial := Factorial(N - 1);
Your SoucetCisel doesn't do that, it simply adds the initial value of the function result
to the value of n[j], so it is not recursive at all.
The other problem is that, as written, it has no defined return value. In all the
Pascal implementations I've come across, the return value is undefined on entry to the
function and stays undefined until some value is explicitly assigned to it. The
function result is usually some space on the stack which the compiler-generated
code of the function reserves but which initially (on entry to the function) holds some random value, resulting from previous usage of the stack.
So, what the result of your SoucetCisel function is evaluated from is effectively
SoucetCisel := ARandomNumber + n[j]
which of course is just another random number. Obviously, you fix this aspect
of your function by ensuring that an explicit assignment to the function result is made
immediately on entry to the function. As a general rule, all execution paths through a function should lead through a statement which explicitly assigns a
value to the function result.
Then, you need to rewrite the remainder of it so that it actually is recursive
in the way your task requires.
While you're doing those two things, I would suggest that you use a more
helpful parameter name than the anonymous 'n'. 'n' is usually used to refer to an uninteresting integer.
update I'm not sure from your comment whether it was supposed to be serious. In case it was, consider these two functions
function SumOfReals(Reals : TPoleReal; j : word): real;
var
i : Integer;
begin
SumOfReals := 0;
for i := 1 to j do
SumOfReals := SumOfReals + Reals[i];
end;
function SumOfRealsRecursive(Reals : TPoleReal; j : word): real;
var
i : Integer;
begin
SumOfRealsRecursive := Reals[j];
if j > 1 then
SumOfRealsRecursive := SumOfRealsRecursive + SumOfRealsRecursive(Reals, j -1);
end;
These functions both do the same thing, namely evaluate the sum of the contents
of the Reals array up to and including the index j. The first one does so iteratively,
simply traversing the Reals array, which the second does it recursively. However,
it should be obvious that the recursive version is absolutely pointless in this case because
the iterative version does the same thing but far more efficiently, because
it does not involve copying the entire Reals array for each recursive call, which the recursive version does.
As I told you in a comment before. Try this code for your pascal program:
type
Indexy = 1..100;
TPoleReal = array [Indexy] of Real;
var
j: word;
r, realRes: real;
tpr: TPoleReal;
function SoucetCisel(n: TPoleReal; j: word): real;
begin
if j>0 then begin
SoucetCisel:=SoucetCisel(n, j-1) + n[j];
end
end;
begin i:=0; j:=0;
while not seekeof do begin
read(r); Inc(j);
tpr[j]:=r;
writeln(j, ' ', tpr[j]);
end;
realRes:= SoucetCisel(tpr, j);
writeln(realRes);
end.

Cartesian Product of Lists Using Ada

I am currently working on programming this (https://rosettacode.org/wiki/Cartesian_product_of_two_or_more_lists) in Ada, I am trying to do a Cartesian product between different sets. I need help figuring it out, the main issue is how would I be able to declare empty Pairs and calculate that if it's empty, then the result should be empty. Thank you!
Numbers I am trying to use:
{1, 2} × {3, 4}
{3, 4} × {1, 2}
{1, 2} × {}
{} × {1, 2}
My code:
with Ada.Text_IO; use Ada.Text_IO; -- Basically importing the functions that will be used to print out the results.
procedure Hello is -- Procedure is where variables & functions are declared!
type T_Pair is array(1..2) of Integer; -- Declare a type of array that contains a set of 2 numbers (Used for final result!).
type T_Result is array(1..4) of T_Pair; -- Declare a type of array that contains a set of T_Pair(s), used to hold the result.
Demo1 : T_Result;
Demo1A : T_Pair := (1, 2);
Demo1B : T_Pair := (3, 4);
function Fun_CartProd(p1: T_Pair; p2: T_Pair) return T_Result is
results: T_Result;
i: integer := 1;
begin
for j in 1..2 loop
for h in 1..2 loop
results(i) := (p1(j), p2(h));
i := i + 1;
end loop;
end loop;
return results;
end Fun_CartProd;
begin -- This is where the statements go
Demo1 := Fun_CartProd(Demo1A, Demo1B);
for K in 1 .. Demo1'length loop
Put(" [");
for B in 1 .. Demo1(K)'length loop
Put(Integer'Image(Demo1(K)(B)));
if Demo1(K)'length /= B then
Put(",");
end if;
end loop;
Put("]");
if Demo1'length /= K then
Put(",");
end if;
end loop;
Put_Line(""); -- Create a new line.
end Hello;
Since each set of integers can be any length, including empty, I would start with a type that can handle all those situations:
type Integer_Set is array(Positive range <>) of Integer; -- Input type
type Integer_Tuple is array(Positive range <>_ of Integer; -- Output type
and you can represent the empty sets and tuples this way:
Empty_Set : constant Integer_Set(1..0) := (others => <>);
Empty_Tuple : constant Integer_Tuple(1..0) := (others => <>);
The other problem isn't just how many elements are in each set, but how many sets you will be finding the product of. For this I would recommend some kind of container. An array won't work here because each of the individual sets can have different sizes (including empty), but Ada has a variety of "indefinite" containers that can handle that. Here is an example using vectors:
package Set_Vectors is new Ada.Containers.Indefinite_Vectors
(Index_Type => Positive,
Element_Type => Integer_Set);
package Tuple_Vectors is new Ada.Containers.Indefinite_Vectors
(Index_Type => Positive,
Element_Type => Integer_Tuple);
and you can then represent an empty result as:
Empty_Tuple_Vector : constant Tuple_Vectors.Vector := Tupler_Vectors.Empty_Vector;
Now you can create a function that takes in a vector of sets and returns a Cartesian product which will also be a vector of sets:
function Cartesian_Product(Inputs : Set_Vectors.Vector) return Tuple_Vectors.Vector;
If one of the input sets is empty, you return an Empty_Tuple_Vector. You can check if one of the input sets are empty by checking their Length attribute result. It will be 0 if they are empty. Additionally if the input vector is completely empty, you can decide to either return Empty_Tuple_Vector or raise an exception. For example:
if Inputs'Length = 0 then
return Empty_Tuple_Vector; -- or raise an exception, etc.
end if;
for Set of Inputs loop
if Set'Length = 0 then
return Empty_Tuple_Vector;
end if;
-- Maybe do other stuff here if you need
end loop;
Note that the logic you presented assumes only pairs of inputs. I don't have enough experience to convert your logic to account for variable inputs, but perhaps someone can comment on that if you need it.
Also note as Flyx commented, this does not semantically check if a set is a set or not on the inputs (I.E. no duplicate values).

Resources