Exercise #1: Find Arithmetic Expression to Construct a Value from Given Numbers by Zoran Horvat @zoranh75
Problem Statement
Goal of this exercise is to write code which accepts a set of numbers and then
tries to devise an arithmetic expression that yields a requested value, using
four basic arithmetic operations: addition, subtraction, multiplication and
division. Each input number must be used exactly once in the expression.
Division is applicable only to numbers that are divisible without remainder.
All input numbers and the target number are integers greater than zero. There
are no more than 5 input numbers and target number is not larger than 1000.
Example 1: Suppose that numbers 4, 8 and 9 are given and value 18 should be
constructed. One solution is: 9 * 8 / 4.
Example 2: If numbers 6, 7 and 9 are given, number 3 requested, then solution
is: 6 / (9  7).
Problem Analysis
We can approach this problem in bottomup fashion: start from input numbers and
then combine them into larger and larger expressions. Each expression that is
reached can be combined further. For each expression list of participating
input numbers participating is maintained. Two expressions can be combined only
if their lists are disjoint  one input number can be used at most in one of
the expressions.
Combining two expressions actually means to apply all operators that are
applicable. Basically, addition, subtraction and multiplication can always be
applied. Only division is questionable  it is applicable only if results of
two expressions can be divided without remainder. Addition and multiplication
are commutative (a+b=b+a and a*b=b*a), meaning that order of operand is not
important. Subtraction and division are not commutative, meaning that they can
be applied in two different ways for each pair of expressions. Consequently, we
have a total of six possible operations that can be applied to any pair of
expressions. In other words, one pair of expressions can be expanded into up to
six other expressions. For example, suppose that values 3 and 6 are available.
These two values can produce: 3+6=9, 36=3, 63=3, 3*6=18 and 6/3=2  total of
five new values. We cannot divide 3 by 6 using integer division. Even more, we
can reject expression 36=3 because it can always be reached in the opposite
direction  by subtracting the result of expression 63=3 from any other
expression.
By this point we have decided how to construct larger expressions from smaller
ones. But now we have a problem of a different sort: there are results that can
be constructed from same set of numbers in more than one way. For example, if
there are numbers 2 and 2, we can create number 4 as 2+2 or 2*2. It could be a
serious problem should we repeat all subsequent calculations for the second
form. Number of multiple paths that lead to the same value would quickly start
to build up. Take a similar example, numbers: 1, 2 and 3. These numbers can
produce value 5 in quite a few ways: 2*1+3, 2/1+3, 2+3*1, 2+3/1, 2*31. There
must be a way to detect that these three numbers were employed to reach value 5
(e.g. like 2*1+3) and then to discard all subsequent solutions to the same
problem. So the next element of the solution is to make sure that all values
produced are remembered in a kind of a cache, all in order to discard further
solutions to the same partial problem. But note that expressions 2+3=5 and
2*1+3=5 are different: they differ in numbers that are used to construct them.
Generally, two expressions are considered the same (in terms that they carry
the same information) if they have the same lists of input numbers and produce
the same value.
Next issue to discuss is how does the algorithm proceed. It is obvious that
existing expressions are producing new expressions that are simply added to the
set of all valid expressions. Now we need to decide on order in which
expressions are going to be combined so to guarantee that all pairs of
expressions are combined before the algorithm completes. One way to introduce
such a guarantee is to maintain a queue of expressions that have not been
processed, i.e. paired with other expressions. In each step of the algorithm,
an expression is dequeued, then combined with all existing expressions
(possibly producing new expressions that are not equal to any existing
expression), and only then added to the set of all valid expressions. In this
way, it is guaranteed that any pair of expressions is picked up for expansion,
consequently providing a guarantee that all pairs of expressions will be
combined before the end of the execution. Should there be a valid solution, it
will certainly be found.
Final question to answer is about starting conditions. When algorithm
commences, set of valid expressions consists of input values  each value is a
valid expression on its own right. So if we have a set of four input values,
then we begin with four valid expressions. At the same time, all four
expressions are added to the queue of expressions to process. That is the state
in which algorithm starts to unfold.
Complete algorithm that solves the problem is now very simple:
E  set of all valid expressions
Q  queue of expressions that have not been expanded yet
N  set of input numbers
v  target value
Goal: To create an expression N>v, which uses all numbers from N to produce value v
for all numbers n in N
Add expression n>n to Q
Add expression n>n to E
while Q is not empty and E does not contain expression N>v
begin
e = expression dequeued from Q
for each expression f in E
begin
G = set of expressions obtained by combining e and f
for each expression g in G
if g is not in E then
Enqueue g to Q
Add g to E
end
end
if E contains expression N>v then
print expression N>v
Implementation
Now that we have decided on algorithm that solves the problem, we need to
discuss implementation details. Namely, we have to answer the following
questions:
 How do we express the arithmetic expression?
 How do we check whether expression has already been generated?
 How do we combine two expressions to create more expressions?
 How do we add expressions to the set and to the queue?
In each of these segments there can be many viable solutions. Generally, the
simpler the better. Answer to first question, how to represent an expression,
can be as follows. Each expression is defined recursively by pointing to two
expressions that represent left and right operand and by specifying the
operation applied to the two. In addition, expression carries its value (which
is generally redundant, but quite useful to avoid constant reevaluation of all
expressions during algorithm execution). One more redundant information comes
handy: a list of input numbers used to construct the expression (this list is
redundant because it can be constructed recursively by joining corresponding
lists of the operand expressions). Recursion stops at input numbers  each
number is treated as an expression which does not have operands or operation 
number defines its value and it is the sole element in the list of numbers
used.
Second issue deals with identifying expressions. As already explained above,
two expressions are considered equal if they share the same set of input
numbers and have the same value when calculated. This leads to an idea that
input numbers could be remembered as a bitmask which would then be combined
with expression value. Each bit in the mask indicates whether corresponding
input number participates in the expression. This is the point when an example
would come handy. Let input numbers be 1, 2, 3, 4 and expression 2*1+3=5 should
be encoded. Numeric code which corresponds with this expression is shown on the
following picture.
Lower four bits of the number are dedicated to input numbers  three bits one
indicate that corresponding numbers (1, 2 and 3) are participating in the
expression, while fourth bit zero indicates that the remaining input number (4)
does not take place in this expression. Bits above the fourth position contain
value obtained when expression is evaluated (5 in this case). Note that
expression 2/1+3=5 has the same signature, and that is exactly what we wanted
to obtain.
Next question is the one about combining expressions. Two arbitrary expressions
can be combined only if their input numbers sets are disjoint. In example
above, input numbers are indicated by lowest four bits in the expression code.
Hence the solution  lowest bits of the two expressions codes must be disjoint
(bitwise AND operation produces all zeros). After testing whether two
expressions can be combined in the first place, next operation is to actually
combine them. We have already explained that there are six possible arithmetic
operations that can be applied to any pair of expressions. Solution to the
problem is simply to try all of them and to produce up to six new expressions.
Any expression generated would have a value that is determined by input
expressions' values and the operation applied. Masks indicating input numbers
should be combined into one mask (bitwise OR operation). That would naturally
lead to creating a signature of the new expression. Off course, new expression
would have to point to original expressions as its left and right operand.
Final question is about maintaining a set and a queue of expressions. At this
step it becomes obvious why we had to devise expression signatures. With that
tool at hand, we can create an array of whatever values we need and then simply
use expression signature as an index pointing to the corresponding value in the
array. The queue would be maintained equally simply  it would contain just
expression signatures, since the signature is quite sufficient to access all
the information about the expression.
Now that all technical difficulties have been dealt with, we are ready to
provide the full source code of the solution. The source code is commented so
that it can be read apart from the algorithm provided above. It is given in the
form of C# console application which depends on a couple of .NET Framework
classes (hashtable, dictionary, queue). But these classes are only collections
with well known behavior, meaning that you could rewrite the solution to any
other programming language or framework easily.
using System;
namespace Arithmetics
{
class Program
{
static int[] ReadInput(out int value)
{
Console.Write("Enter integer numbers to use (spaceseparated): ");
string s = Console.ReadLine();
string[] parts = s.Split(new char[] { ' ' }, StringSplitOptions.RemoveEmptyEntries);
int[] a = new int[parts.Length];
for (int i = 0; i < a.Length; i++)
a[i] = int.Parse(parts[i]);
Console.Write("Enter integer value to calculate: ");
value = int.Parse(Console.ReadLine());
return a;
}
static void SolveAndPrint(int[] numbers, int targetValue)
{
int targetKey = (targetValue << numbers.Length) + (1 << numbers.Length)  1;
System.Collections.Generic.HashSet<int> solvedKeys =
new System.Collections.Generic.HashSet<int>();
System.Collections.Generic.Dictionary<int, int> keyToLeftParent =
new System.Collections.Generic.Dictionary<int, int>();
System.Collections.Generic.Dictionary<int, int> keyToRightParent =
new System.Collections.Generic.Dictionary<int, int>();
System.Collections.Generic.Dictionary<int, char> keyToOperator =
new System.Collections.Generic.Dictionary<int, char>();
System.Collections.Generic.Queue<int> queue =
new System.Collections.Generic.Queue<int>();
for (int i = 0; i < numbers.Length; i++)
{
int key = (numbers[i] << numbers.Length) + (1 << i);
solvedKeys.Add(key);
queue.Enqueue(key);
}
while (queue.Count > 0 && !solvedKeys.Contains(targetKey))
{
int curKey = queue.Dequeue();
int curMask = curKey & ((1 << numbers.Length)  1);
int curValue = curKey >> numbers.Length;
int[] keys = new int[solvedKeys.Count];
solvedKeys.CopyTo(keys);
for (int i = 0; i < keys.Length; i++)
{
int mask = keys[i] & ((1 << numbers.Length)  1);
int value = keys[i] >> numbers.Length;
if ((mask & curMask) == 0)
{
for (int op = 0; op < 6; op++)
{
char opSign = '\0';
int newValue = 0;
switch (op)
{
case 0:
newValue = curValue + value;
opSign = '+';
break;
case 1:
newValue = curValue  value;
opSign = '';
break;
case 2:
newValue = value  curValue;
opSign = '';
break;
case 3:
newValue = curValue * value;
opSign = '*';
break;
case 4:
newValue = 1;
if (value != 0 && curValue % value == 0)
newValue = curValue value;
opSign = '';
break;
case 5:
newValue = 1;
if (curValue != 0 && value % curValue == 0)
newValue = value curValue;
opSign = '';
break;
}
if (newValue >= 0)
{
int newMask = (curMask  mask);
int newKey = (newValue << numbers.Length) + newMask;
if (!solvedKeys.Contains(newKey))
{
solvedKeys.Add(newKey);
if (op == 2  op == 5)
{
keyToLeftParent.Add(newKey, keys[i]);
keyToRightParent.Add(newKey, curKey);
}
else
{
keyToLeftParent.Add(newKey, curKey);
keyToRightParent.Add(newKey, keys[i]);
}
keyToOperator.Add(newKey, opSign);
solvedKeys.Add(newKey);
queue.Enqueue(newKey);
}
}
}
}
}
}
if (!solvedKeys.Contains(targetKey))
Console.WriteLine("Solution has not been found.");
else
{
PrintExpression(keyToLeftParent, keyToRightParent, keyToOperator, targetKey, numbers.Length);
Console.WriteLine("={0}", targetValue);
}
}
static void PrintExpression(System.Collections.Generic.Dictionary<int, int> keyToLeftParent,
System.Collections.Generic.Dictionary<int, int> keyToRightParent,
System.Collections.Generic.Dictionary<int, char> keyToOperator,
int key, int numbersCount)
{
if (!keyToOperator.ContainsKey(key))
Console.Write("{0}", key >> numbersCount);
else
{
Console.Write("(");
PrintExpression(keyToLeftParent, keyToRightParent, keyToOperator,
keyToLeftParent[key], numbersCount);
Console.Write(keyToOperator[key]);
PrintExpression(keyToLeftParent, keyToRightParent, keyToOperator,
keyToRightParent[key], numbersCount);
Console.Write(")");
}
}
static void Main(string[] args)
{
while (true)
{
int value;
int[] numbers = ReadInput(out value);
SolveAndPrint(numbers, value);
Console.Write("More? (y/n) ");
if (Console.ReadLine().ToLower() != "y")
break;
}
}
}
}
Demonstration
When source code provided above is compiled and run, it lets the user pick the
input numbers and the desired output number and then attempts to solve the
problem, printing out the expression if one is found. Below is the
demonstration of our algorithm in action.
Enter integer numbers to use (spaceseparated): 4 8 9
Enter integer value to calculate: 18
(9*(8/4))=18
More? (y/n) y
Enter integer numbers to use (spaceseparated): 6 7 9
Enter integer value to calculate: 3
(6/(97))=3
More? (y/n) y
Enter integer numbers to use (spaceseparated): 2 3 4 5
Enter integer value to calculate: 18
(((2*5)4)*3)=18
More? (y/n) y
Enter integer numbers to use (spaceseparated): 2 3 4
Enter integer value to calculate: 12
Solution has not been found.
More? (y/n) y
Enter integer numbers to use (spaceseparated): 1 3 4 6
Enter integer value to calculate: 24
Solution has not been found.
More? (y/n) n
FollowUp Exercises
Readers are suggested to build upon this solution and work up solutions to
extended tasks:
 Print all expressions that produce the requested number, not only the one that
utilizes all of the input numbers. Consider example 2,3,4>12 from the
demonstration, which does not have the complete solution but does have a simple
one: 3*4=12, which omits input value 2.
 If exact solution is not found, then print the solution which is closest to the
requested number.
 Extend the solution to support fractional numbers. In the demonstration above,
example 1,3,4,6>24 cannot be solved using the algorithm provided, but that
problem actually does have a solution when fractional numbers are supported.
(Try to figure out the solution before letting the program find it!)
See also:
Published: Mar 17, 2013; Modified: Dec 13, 2013
ZORAN HORVAT Zoran is software architect dedicated to clean design and CTO in a growing software company. Since 2014 Zoran is an author at Pluralsight where he is preparing a series of courses on objectoriented and functional design, design patterns, writing unit and integration tests and applying methods to improve code design and longterm maintainability. Follow him on Twitter @zoranh75 to receive updates and links to new articles. Watch Zoran's video courses at pluralsight.com (requires registration): Making Your C# Code More ObjectOriented This course will help leverage your conceptual understanding to produce proper objectoriented code, where objects will completely replace procedural code for the sake of flexibility and maintainability. More... Advanced Defensive Programming Techniques This course will lead you step by step through the process of developing defensive design practices, which can substitute common defensive coding, for the better of software design and implementation. More... Tactical Design Patterns in .NET: Creating Objects This course sheds light on issues that arise when implementing creational design patterns and then provides practical solutions that will make our code easier to write and more stable when running. More... Tactical Design Patterns in .NET: Managing Responsibilities Applying a design pattern to a realworld problem is not as straightforward as literature implicitly tells us. It is a more engaged process. This course gives an insight to tactical decisions we need to make when applying design patterns that have to do with separating and implementing class responsibilities. More... Tactical Design Patterns in .NET: Control Flow Improve your skills in writing simpler and safer code by applying coding practices and design patterns that are affecting control flow. More... Writing Highly Maintainable Unit Tests This course will teach you how to develop maintainable and sustainable tests as your production code grows and develops. More... Improving Testability Through Design This course tackles the issues of designing a complex application so that it can be covered with high quality tests. More... Share this article
