Related
What are "sequence points"?
What is the relation between undefined behaviour and sequence points?
I often use funny and convoluted expressions like a[++i] = i;, to make myself feel better. Why should I stop using them?
If you've read this, be sure to visit the follow-up question Undefined behavior and sequence points reloaded.
(Note: This is meant to be an entry to Stack Overflow's C++ FAQ. If you want to critique the idea of providing an FAQ in this form, then the posting on meta that started all this would be the place to do that. Answers to that question are monitored in the C++ chatroom, where the FAQ idea started out in the first place, so your answer is very likely to get read by those who came up with the idea.)
C++98 and C++03
This answer is for the older versions of the C++ standard. The C++11 and C++14 versions of the standard do not formally contain 'sequence points'; operations are 'sequenced before' or 'unsequenced' or 'indeterminately sequenced' instead. The net effect is essentially the same, but the terminology is different.
Disclaimer : Okay. This answer is a bit long. So have patience while reading it. If you already know these things, reading them again won't make you crazy.
Pre-requisites : An elementary knowledge of C++ Standard
What are Sequence Points?
The Standard says
At certain specified points in the execution sequence called sequence points, all side effects of previous evaluations
shall be complete and no side effects of subsequent evaluations shall have taken place. (§1.9/7)
Side effects? What are side effects?
Evaluation of an expression produces something and if in addition there is a change in the state of the execution environment it is said that the expression (its evaluation) has some side effect(s).
For example:
int x = y++; //where y is also an int
In addition to the initialization operation the value of y gets changed due to the side effect of ++ operator.
So far so good. Moving on to sequence points. An alternation definition of seq-points given by the comp.lang.c author Steve Summit:
Sequence point is a point in time at which the dust has settled and all side effects which have been seen so far are guaranteed to be complete.
What are the common sequence points listed in the C++ Standard?
Those are:
at the end of the evaluation of full expression (§1.9/16) (A full-expression is an expression that is not a subexpression of another expression.)1
Example :
int a = 5; // ; is a sequence point here
in the evaluation of each of the following expressions after the evaluation of the first expression (§1.9/18) 2
a && b (§5.14)
a || b (§5.15)
a ? b : c (§5.16)
a , b (§5.18) (here a , b is a comma operator; in func(a,a++) , is not a comma operator, it's merely a separator between the arguments a and a++. Thus the behaviour is undefined in that case (if a is considered to be a primitive type))
at a function call (whether or not the function is inline), after the evaluation of all function arguments (if any) which
takes place before execution of any expressions or statements in the function body (§1.9/17).
1 : Note : the evaluation of a full-expression can include the evaluation of subexpressions that are not lexically
part of the full-expression. For example, subexpressions involved in evaluating default argument expressions (8.3.6) are considered to be created in the expression that calls the function, not the expression that defines the default argument
2 : The operators indicated are the built-in operators, as described in clause 5. When one of these operators is overloaded (clause 13) in a valid context, thus designating a user-defined operator function, the expression designates a function invocation and the operands form an argument list, without an implied sequence point between them.
What is Undefined Behaviour?
The Standard defines Undefined Behaviour in Section §1.3.12 as
behavior, such as might arise upon use of an erroneous program construct or erroneous data, for which this International Standard imposes no requirements 3.
Undefined behavior may also be expected when this
International Standard omits the description of any explicit definition of behavior.
3 : permissible undefined behavior ranges from ignoring the situation completely with unpredictable results, to behaving during translation or program execution in a documented manner characteristic of the environment (with or with-
out the issuance of a diagnostic message), to terminating a translation or execution (with the issuance of a diagnostic message).
In short, undefined behaviour means anything can happen from daemons flying out of your nose to your girlfriend getting pregnant.
What is the relation between Undefined Behaviour and Sequence Points?
Before I get into that you must know the difference(s) between Undefined Behaviour, Unspecified Behaviour and Implementation Defined Behaviour.
You must also know that the order of evaluation of operands of individual operators and subexpressions of individual expressions, and the order in which side effects take place, is unspecified.
For example:
int x = 5, y = 6;
int z = x++ + y++; //it is unspecified whether x++ or y++ will be evaluated first.
Another example here.
Now the Standard in §5/4 says
Between the previous and next sequence point a scalar object shall have its stored value modified at most once by the evaluation of an expression.
What does it mean?
Informally it means that between two sequence points a variable must not be modified more than once.
In an expression statement, the next sequence point is usually at the terminating semicolon, and the previous sequence point is at the end of the previous statement. An expression may also contain intermediate sequence points.
From the above sentence the following expressions invoke Undefined Behaviour:
i++ * ++i; // UB, i is modified more than once btw two SPs
i = ++i; // UB, same as above
++i = 2; // UB, same as above
i = ++i + 1; // UB, same as above
++++++i; // UB, parsed as (++(++(++i)))
i = (i, ++i, ++i); // UB, there's no SP between `++i` (right most) and assignment to `i` (`i` is modified more than once btw two SPs)
But the following expressions are fine:
i = (i, ++i, 1) + 1; // well defined (AFAIK)
i = (++i, i++, i); // well defined
int j = i;
j = (++i, i++, j*i); // well defined
Furthermore, the prior value shall be accessed only to determine the value to be stored.
What does it mean? It means if an object is written to within a full expression, any and all accesses to it within the same expression must be directly involved in the computation of the value to be written.
For example in i = i + 1 all the access of i (in L.H.S and in R.H.S) are directly involved in computation of the value to be written. So it is fine.
This rule effectively constrains legal expressions to those in which the accesses demonstrably precede the modification.
Example 1:
std::printf("%d %d", i,++i); // invokes Undefined Behaviour because of Rule no 2
Example 2:
a[i] = i++ // or a[++i] = i or a[i++] = ++i etc
is disallowed because one of the accesses of i (the one in a[i]) has nothing to do with the value which ends up being stored in i (which happens over in i++), and so there's no good way to define--either for our understanding or the compiler's--whether the access should take place before or after the incremented value is stored. So the behaviour is undefined.
Example 3 :
int x = i + i++ ;// Similar to above
Follow up answer for C++11 here.
This is a follow up to my previous answer and contains C++11 related material..
Pre-requisites : An elementary knowledge of Relations (Mathematics).
Is it true that there are no Sequence Points in C++11?
Yes! This is very true.
Sequence Points have been replaced by Sequenced Before and Sequenced After (and Unsequenced and Indeterminately Sequenced) relations in C++11.
What exactly is this 'Sequenced before' thing?
Sequenced Before(§1.9/13) is a relation which is:
Asymmetric
Transitive
between evaluations executed by a single thread and induces a strict partial order1
Formally it means given any two evaluations(See below) A and B, if A is sequenced before B, then the execution of A shall precede the execution of B. If A is not sequenced before B and B is not sequenced before A, then A and B are unsequenced 2.
Evaluations A and B are indeterminately sequenced when either A is sequenced before B or B is sequenced before A, but it is unspecified which3.
[NOTES]
1 : A strict partial order is a binary relation "<" over a set P which is asymmetric, and transitive, i.e., for all a, b, and c in P, we have that:
........(i). if a < b then ¬ (b < a) (asymmetry);
........(ii). if a < b and b < c then a < c (transitivity).
2 : The execution of unsequenced evaluations can overlap.
3 : Indeterminately sequenced evaluations cannot overlap, but either could be executed first.
What is the meaning of the word 'evaluation' in context of C++11?
In C++11, evaluation of an expression (or a sub-expression) in general includes:
value computations (including determining the identity of an object for glvalue evaluation and fetching a value previously assigned to an object for prvalue evaluation) and
initiation of side effects.
Now (§1.9/14) says:
Every value computation and side effect associated with a full-expression is sequenced before every value computation and side effect associated with the next full-expression to be evaluated.
Trivial example:
int x;
x = 10;
++x;
Value computation and side effect associated with ++x is sequenced after the value computation and side effect of x = 10;
So there must be some relation between Undefined Behaviour and the above-mentioned things, right?
Yes! Right.
In (§1.9/15) it has been mentioned that
Except where noted, evaluations of operands of individual operators and of subexpressions of individual expressions are unsequenced4.
For example :
int main()
{
int num = 19 ;
num = (num << 3) + (num >> 3);
}
Evaluation of operands of + operator are unsequenced relative to each other.
Evaluation of operands of << and >> operators are unsequenced relative to each other.
4: In an expression that is evaluated more than once during the execution
of a program, unsequenced and indeterminately sequenced evaluations of its subexpressions need not be performed consistently in different evaluations.
(§1.9/15)
The value computations of the operands of an
operator are sequenced before the value computation of the result of the operator.
That means in x + y the value computation of x and y are sequenced before the value computation of (x + y).
More importantly
(§1.9/15) If a side effect on a scalar object is unsequenced relative to either
(a) another side effect on the same scalar object
or
(b) a value computation using the value of the same scalar object.
the behaviour is undefined.
Examples:
int i = 5, v[10] = { };
void f(int, int);
i = i++ * ++i; // Undefined Behaviour
i = ++i + i++; // Undefined Behaviour
i = ++i + ++i; // Undefined Behaviour
i = v[i++]; // Undefined Behaviour
i = v[++i]: // Well-defined Behavior
i = i++ + 1; // Undefined Behaviour
i = ++i + 1; // Well-defined Behaviour
++++i; // Well-defined Behaviour
f(i = -1, i = -1); // Undefined Behaviour (see below)
When calling a function (whether or not the function is inline), every value computation and side effect associated with any argument expression, or with the postfix expression designating the called function, is sequenced before execution of every expression or statement in the body of the called function. [Note: Value computations and side effects associated with different argument expressions are unsequenced. — end note]
Expressions (5), (7) and (8) do not invoke undefined behaviour. Check out the following answers for a more detailed explanation.
Multiple preincrement operations on a variable in C++0x
Unsequenced Value Computations
Final Note :
If you find any flaw in the post please leave a comment. Power-users (With rep >20000) please do not hesitate to edit the post for correcting typos and other mistakes.
C++17 (N4659) includes a proposal Refining Expression Evaluation Order for Idiomatic C++
which defines a stricter order of expression evaluation.
In particular, the following sentence
8.18 Assignment and compound assignment operators:....
In all cases, the assignment is sequenced after the value
computation of the right and left operands, and before the value computation of the assignment expression.
The right operand is sequenced before the left operand.
together with the following clarification
An expression X is said to be sequenced before an expression Y if every
value computation and every side effect associated with the expression X is sequenced before every value
computation and every side effect associated with the expression Y.
make several cases of previously undefined behavior valid, including the one in question:
a[++i] = i;
However several other similar cases still lead to undefined behavior.
In N4140:
i = i++ + 1; // the behavior is undefined
But in N4659
i = i++ + 1; // the value of i is incremented
i = i++ + i; // the behavior is undefined
Of course, using a C++17 compliant compiler does not necessarily mean that one should start writing such expressions.
I am guessing there is a fundamental reason for the change, it isn't merely cosmetic to make the old interpretation clearer: that reason is concurrency. Unspecified order of elaboration is merely selection of one of several possible serial orderings, this is quite different to before and after orderings, because if there is no specified ordering, concurrent evaluation is possible: not so with the old rules. For example in:
f (a,b)
previously either a then b, or, b then a. Now, a and b can be evaluated with instructions interleaved or even on different cores.
In C99(ISO/IEC 9899:TC3) which seems absent from this discussion thus far the following steteents are made regarding order of evaluaiton.
[...]the order of evaluation of subexpressions and the order in which
side effects take place are both unspecified. (Section 6.5 pp 67)
The order of evaluation of the operands is unspecified. If an attempt
is made to modify the result of an assignment operator or to access it
after the next sequence point, the behavior[sic] is undefined.(Section
6.5.16 pp 91)
I'm trying to write a Petrick's method, which is a technique for Quine–McCluskey algorithm.
Assume I have a math equation, which consists of + and *. For example:
(K+L)(K+M)(L+N)(M+P)(N+Q)(P+Q)
How can I exand the equation to get all of the sum of products, like this?
K*K*L*M*N*P + K*K*L*M*N*Q + .... (63 terms)
(You can see the inferred result with WolframAlpha)
I somehow doubt this is what you want, but to obtain the result as an array of characters...
w = Expand[(K + L) (K + M) (L + N) (M + P) (N + Q) (P + Q)];
x = ToString#InputForm[w];
z = StringReplace[x, y_ ~~ "^2" :> StringJoin[y, "*", y]]
K*K*L*M*N*P + K*L*L*M*N*P + K*L*M*M*N*P + ... + L*M*N*P*Q*Q
DeleteCases[Characters#z, " "]
{K,*,K,*,L,*,M,*,N,*,P,+, ... ,+,L,*,M,*,N,*,P,*,Q,*,Q}
I have got fewer terms than you expected - only five rather than 63:
As Boolean expressions:
(k+l) & (l+n) & (k+m) & (m+p) & (n+q) & (p+q)
knp + lmq + lmnp + klpq + kmnq
It might be interesting to look at tha JavaScript code behind this site. It is an implementation of Petrick's method in JavaScript.
Regarding your statement
"I'm trying to write a Petrick's method, which is a technique for Quine–McCluskey algorithm."
I will show you a
ready to use implementation of Petrick's method and
also a full fledged Quine & McCluskey Implementation and
an explanation of the algorithm that I implemented
First of all, the complete solution can be found here:
MCDC
The source code is an elegant solution using set operations for an efficient implementation:
// Functor operator for applying Petricks methhod
ProductTermVector PetricksMethod::operator ()(const CNF& cnf)
{
// We select an iterative approach. Start with the first Element of the CNF (which is a DNF)
// And we store the result of each iterative operation again in this element
DNF resultingDNF{ cnf[0] };
// We will always start with the element 1 (not element 0) because in 0 is the initial value
// or respectively the intermediate result
for (CNF::size_type dnfInCnfIndex = 1; dnfInCnfIndex < cnf.size(); ++dnfInCnfIndex)
{
// Result of multipliying out the intermediate (initial) value with the current CNF Product term
DNF intermediateCalculatedDNF;
// Now go through all elements of the intermediate (initial) product term/DNF
// For (1+2)(3+4) this would be the (1+2) part
for (const ProductTerm& productTermLeftSide : resultingDNF)
{
// Next we will iterate over all Minterms in the next DNF
// For (1+2)(3+4) this would be the (3+4) part
for (const ProductTerm& productTermRightSide : cnf[dnfInCnfIndex])
{
ProductTerm productTerm{ productTermLeftSide }; // Resulting Product term is now 1
// Add all elements from the right side
productTerm.insert(productTermRightSide.begin(), productTermRightSide.end()); // Resulting Product term is now 1,2
intermediateCalculatedDNF.insert(std::move(productTerm)); // Store this one
// And continue to add more product terms. The stl::set will ensure the idempotence law and prevent memory waste
}
}
// And now add all found terms to the result and continue with the next element of the right hand side
// Please note: also here the set will prevent double terms
resultingDNF = std::move(intermediateCalculatedDNF);
}
// Now we have the result (with 10 lines of code). The result contains all product terms in DNF
// But for our prupose we are only interested in the minimum size terms
// so, lets find the element with the minimu size (can be more than one)
uint minLength{ narrow_cast<uint>(std::min_element(resultingDNF.begin(), resultingDNF.end(), [](const ProductTerm & left, const ProductTerm & right) noexcept {return left.size() < right.size(); })->size()) };
// And from the big list of the DNF with all product terms, we copy all elements having the minimu size to the result. These are our best coverage sets
ProductTermVector cheapestVector;
// Copy result and return it to caller
std::copy_if(resultingDNF.begin(), resultingDNF.end(), std::back_inserter(cheapestVector), [&minLength](const ProductTerm& pt) noexcept {return pt.size() == minLength; });
return cheapestVector;
}
The number of net lines of code is 14. There are some additional definitions used, to make understanding and usage of types easier:
using BooleanVariable = uint_fast8_t;
using ProductTerm = std::set<BooleanVariable>;
using ProductTermVector = std::vector<ProductTerm>;
// Disjunctive Normal Form
using DNF = std::set<ProductTerm>;
// Conjunctive Normal Form
using CNF = std::vector<DNF>;
class PetricksMethod // Functor
{
public:
ProductTermVector operator()(const CNF& cnf); // Functor operator
};
Please note. The type "BooleanVariable" can also be a char, a string or whatever you like. That doesn't matter for the implementation, but will have an impact on the consumed memory.
The idea behind this algorithm is to use the "STL set" and to employ properties of set operations. If you look for example at the term (a+b)(c+d): If you want to multiply this out, then the result will be: ac+ad+bc+bd. If you treat a boolean variable as a special product term with just one member and implement this product term as a set, then the operation is to just add variables to existing sets. So, if you have a set containing "a" and if you want to multiply this with the set containing "b", then you can just add "b" to "a". The set will then contain "ab".
So, we will insert the set containing "b" to the set containing "a" and so on and so on. This we will do in a loop and will get 4 sets (product terms). These 4 sets make up a resulting DNF. The just calculated DNF can be combined further with additional terms of a CNF.
If we would have "(a+b)(c+d)(e+f)", we would treat it as "((a+b)(c+d)) (e+f)". We would first multiply out the first 2 MaxTerms, get (ac+ad+bc+bd) and apply the same algorithm on (e+f). We will always add new variables to existing sets. And this we will do iteratively, until the complete expression is evaluated.
The problem is the many many resulting subterms. But luckily, here the properties of the set, with unique sorted elements will help. For (a+b)(b+a) we would get ab+aa+bb+ba. The stl set will provide the idempotence law for us. Meaning "a" AND "a" is "a", "b" or "b" is "b". So trying to add "a" to a set containing an "a" already, will not work. The result is still an "a". Same with complete product terms like 2 times "ab". They will not be added to a DNF double. So, the result of above operation is:
ab+aa+bb+ba --> ab+ab+aa+bb --> ab+aa+bb --> a+b+ab
With that approach, there will be no double terms and in general shorter terms.
But please be aware. The calculation time and the memory consumption will grow geometrically with the number of terms. So the function can only be applied with a limited number of variables / terms.
I hope I could give an understandable explanation. If you need more info, please ask.
I have a problem and try to solve it for hours. Here is a pseudocode:
x = 30
if x > 100 then max(function_1(x), function_2(x))
elseif x > 50 then max(function_3(x), function_4(x))
elseif x > 20 then max(function_5(x), function_6(x))
elseif x < 10 then function_7(x)
else function_8(x)
This was a code I run with different values of x. Then functions are mathematical formulas. Now, I have the result of the above for each x and I want to revert and go back to x again.
I found all the reversed mathematical formulas of functions. For example for function_1(x), I have a rev_function_1(y) that will get the result and will give me the initial x.
But, since the original code has a lot of cases, plus the MAX, I am not sure how I can run one code, for every value and return the original one.
Edit: All the functions are one-to-one
Edit2: It seems that the whole function is not one-to-one while each of them individually are. As a result, I have two x for every y and I cannot revert it.
You need to study the result space (or domain) of you functions.
There exists an inverse only if each x results in a unique f(x) that cannot be obtained for any other value of x. This property is called one-to-one
Let me give you an example:
Let's say that f(1) == 8 and that also f(10) == 8.
Then you don't know if the inverse of 8 is 1 or 10.
If the function is one-to-one the inverse will be a unique value. If it is not one-to-one the inverse may be more than one value.
The next step is to figure out which inverse to call.
One way to do it is to call the inverse of all subfunctions.
For each x value you get, calculate f(x). If f(x) gets back the value you wanted to inverse, then keep that x, otherwise throw it away.
When you have gone through all values you will have one (or more) matching x value.
Edit:
Another way is to pre-compute which function that corresponds to a certain interval of output values. You can store these in a database as the tuples:
lowerbound, upperbound, inverse_function
You can then find which function to use (assuming SQL):
SELECT inverse_function FROM lookup_table
WHERE :fx > lowerbound and :fx < upperbound
:fx is the value you want to inverse.
You have an output y for each x. If two xs produce the same y then you can't undo the mapping since y could have come from either x. If no two xs produce the same y then you know it came from that y's x.
NOTE: Since a reverse algorithm is required and OP have not made mandatory to use the original functions or their corresponding reverse functions so following method can be used.
"Now, I have the result of the above for each x and I want to revert and go back to x again.". Its seems that its a case of [Key] => [Value].
//one-to-many case.
if x > 100 then max(function_1(x), function_2(x))
elseif x > 50 then max(function_3(x), function_4(x))
Above piece of code tells that multiple different inputs "x" can produce same output "y".
So you can use std::multimap if you are using C++.
Now multimap can be directly used at input output level, that is, if given a input "x" and it produces an output "y" after running all the formulas then multimap.insert(std::pair<int,int>(y,x));
Therefore, now given an output "y" you can find all the prospective input "x" which could produce an output "y" as follows:
std::pair <std::multimap<int,int>::iterator, std::multimap<int,int>::iterator> ret;
ret = multimap.equal_range(y);
for (std::multimap<int,int>::iterator it=ret.first; it!=ret.second; ++it)
std::cout << ' ' << it->second;
If the relation between input "x" and its corresponding "y" is one-to-one then, std::map can be used.
I think that this is not possible, let's take this example
function_1(x) = x - 200
function_2(x) = x - 201
function_7(x) = x - 5
then for x = 200 => y =0 and for x = 5 => y =0
So for a given value of y we can have multiple values of x
There is no solution in the general case. Think about this set of formulas:
function_1(x) { return x }
function_2(x) { return x }
function_3(x) { return x }
....
I guess it's obvious why it can't work.
I'm working on a homework problem that asks me this:
Tiven a finite set of numbers, and a target number, find if the set can be used to calculate the target number using basic math operations (add, sub, mult, div) and using each number in the set exactly once (so I need to exhaust the set). This has to be done with recursion.
So, for example, if I have the set
{1, 2, 3, 4}
and target 10, then I could get to it by using
((3 * 4) - 2)/1 = 10.
I'm trying to phrase the algorithm in pseudo-code, but so far haven't gotten too far. I'm thinking graphs are the way to go, but would definitely appreciate help on this. thanks.
This isn't meant to be the fastest solution, but rather an instructive one.
It recursively generates all equations in postfix notation
It also provides a translation from postfix to infix notation
There is no actual arithmetic calculation done, so you have to implement that on your own
Be careful about division by zero
With 4 operands, 4 possible operators, it generates all 7680 = 5 * 4! * 4^3
possible expressions.
5 is Catalan(3). Catalan(N) is the number of ways to paranthesize N+1 operands.
4! because the 4 operands are permutable
4^3 because the 3 operators each have 4 choice
This definitely does not scale well, as the number of expressions for N operands is [1, 8, 192, 7680, 430080, 30965760, 2724986880, ...].
In general, if you have n+1 operands, and must insert n operators chosen from k possibilities, then there are (2n)!/n! k^n possible equations.
Good luck!
import java.util.*;
public class Expressions {
static String operators = "+-/*";
static String translate(String postfix) {
Stack<String> expr = new Stack<String>();
Scanner sc = new Scanner(postfix);
while (sc.hasNext()) {
String t = sc.next();
if (operators.indexOf(t) == -1) {
expr.push(t);
} else {
expr.push("(" + expr.pop() + t + expr.pop() + ")");
}
}
return expr.pop();
}
static void brute(Integer[] numbers, int stackHeight, String eq) {
if (stackHeight >= 2) {
for (char op : operators.toCharArray()) {
brute(numbers, stackHeight - 1, eq + " " + op);
}
}
boolean allUsedUp = true;
for (int i = 0; i < numbers.length; i++) {
if (numbers[i] != null) {
allUsedUp = false;
Integer n = numbers[i];
numbers[i] = null;
brute(numbers, stackHeight + 1, eq + " " + n);
numbers[i] = n;
}
}
if (allUsedUp && stackHeight == 1) {
System.out.println(eq + " === " + translate(eq));
}
}
static void expression(Integer... numbers) {
brute(numbers, 0, "");
}
public static void main(String args[]) {
expression(1, 2, 3, 4);
}
}
Before thinking about how to solve the problem (like with graphs), it really helps to just look at the problem. If you find yourself stuck and can't seem to come up with any pseudo-code, then most likely there is something that is holding you back; Some other question or concern that hasn't been addressed yet. An example 'sticky' question in this case might be, "What exactly is recursive about this problem?"
Before you read the next paragraph, try to answer this question first. If you knew what was recursive about the problem, then writing a recursive method to solve it might not be very difficult.
You want to know if some expression that uses a set of numbers (each number used only once) gives you a target value. There are four binary operations, each with an inverse. So, in other words, you want to know if the first number operated with some expression of the other numbers gives you the target. Well, in other words, you want to know if some expression of the 'other' numbers is [...]. If not, then using the first operation with the first number doesn't really give you what you need, so try the other ops. If they don't work, then maybe it just wasn't meant to be.
Edit: I thought of this for an infix expression of four operators without parenthesis, since a comment on the original question said that parenthesis were added for the sake of an example (for clarity?) and the use of parenthesis was not explicitly stated.
Well, you didn't mention efficiency so I'm going to post a really brute force solution and let you optimize it if you want to. Since you can have parantheses, it's easy to brute force it using Reverse Polish Notation:
First of all, if your set has n numbers, you must use exactly n - 1 operators. So your solution will be given by a sequence of 2n - 1 symbols from {{your given set}, {*, /, +, -}}
st = a stack of length 2n - 1
n = numbers in your set
a = your set, to which you add *, /, +, -
v[i] = 1 if the NUMBER i has been used before, 0 otherwise
void go(int k)
{
if ( k > 2n - 1 )
{
// eval st as described on Wikipedia.
// Careful though, it might not be valid, so you'll have to check that it is
// if it evals to your target value great, you can build your target from the given numbers. Otherwise, go on.
return;
}
for ( each symbol x in a )
if ( x isn't a number or x is a number but v[x] isn't 1 )
{
st[k] = x;
if ( x is a number )
v[x] = 1;
go(k + 1);
}
}
Generally speaking, when you need to do something recursively it helps to start from the "bottom" and think your way up.
Consider: You have a set S of n numbers {a,b,c,...}, and a set of four operations {+,-,*,/}. Let's call your recursive function that operates on the set F(S)
If n is 1, then F(S) will just be that number.
If n is 2, F(S) can be eight things:
pick your left-hand number from S (2 choices)
then pick an operation to apply (4 choices)
your right-hand number will be whatever is left in the set
Now, you can generalize from the n=2 case:
Pick a number x from S to be the left-hand operand (n choices)
Pick an operation to apply
your right hand number will be F(S-x)
I'll let you take it from here. :)
edit: Mark poses a valid criticism; the above method won't get absolutely everything. To fix that problem, you need to think about it in a slightly different way:
At each step, you first pick an operation (4 choices), and then
partition S into two sets, for the left and right hand operands,
and recursively apply F to both partitions
Finding all partitions of a set into 2 parts isn't trivial itself, though.
Your best clue about how to approach this problem is the fact that your teacher/professor wants you to use recursion. That is, this isn't a math problem - it is a search problem.
Not to give too much away (it is homework after all), but you have to spawn a call to the recursive function using an operator, a number and a list containing the remaining numbers. The recursive function will extract a number from the list and, using the operation passed in, combine it with the number passed in (which is your running total). Take the running total and call yourself again with the remaining items on the list (you'll have to iterate the list within the call but the sequence of calls is depth-first). Do this once for each of the four operators unless Success has been achieved by a previous leg of the search.
I updated this to use a list instead of a stack
When the result of the operation is your target number and your list is empty, then you have successfully found the set of operations (those that traced the path to the successful leaf) - set the Success flag and unwind. Note that the operators aren't on a list nor are they in the call: the function itself always iterates over all four. Your mechanism for "unwinding" the operator sequence from the successful leaf to get the sequence is to return the current operator and number prepended to the value returned by recursive call (only one of which will be successful since you stop at success - that, obviously, is the one to use). If none are successful, then what you return isn't important anyhow.
Update This is much harder when you have to consider expressions like the one that Daniel posted. You have combinatorics on the numbers and the groupings (numbers due to the fact that / and - are order sensitive even without grouping and grouping because it changes precedence). Then, of course, you also have the combinatorics of the operations. It is harder to manage the differences between (4 + 3) * 2 and 4 + (3 * 2) because grouping doesn't recurse like operators or numbers (which you can just iterate over in a breadth-first manner while making your (depth-first) recursive calls).
Here's some Python code to get you started: it just prints all the possible expressions, without worrying too much about redundancy. You'd need to modify it to evaluate expressions and compare to the target number, rather than simply printing them.
The basic idea is: given a set S of numbers, partition S into two subsets left and right in all possible ways (where we don't care about the order or the elements in left and right), such that left and right are both nonempty. Now for each of these partitions, find all ways of combining the elements in left (recursively!), and similarly for right, and combine the two resulting values with all possible operators. The recursion bottoms out when a set has just one element, in which case there's only one value possible.
Even if you don't know Python, the expressions function should be reasonably easy to follow; the splittings function contains some Python oddities, but all it does is to find all the partitions of the list l into left and right pieces.
def splittings(l):
n = len(l)
for i in xrange(2**n):
left = [e for b, e in enumerate(l) if i & 2**b]
right = [e for b, e in enumerate(l) if not i & 2**b]
yield left, right
def expressions(l):
if len(l) == 1:
yield l[0]
else:
for left, right in splittings(l):
if not left or not right:
continue
for el in expressions(left):
for er in expressions(right):
for operator in '+-*/':
yield '(' + el + operator + er + ')'
for x in expressions('1234'):
print x
pusedo code:
Works(list, target)
for n in list
tmp=list.remove(n)
return Works(tmp,target+n) or Works(tmp,target-n) or Works(tmp, n-target) or ...
then you just have to put the base case in. I think I gave away to much.
I'm working on a homework problem that asks me this:
Tiven a finite set of numbers, and a target number, find if the set can be used to calculate the target number using basic math operations (add, sub, mult, div) and using each number in the set exactly once (so I need to exhaust the set). This has to be done with recursion.
So, for example, if I have the set
{1, 2, 3, 4}
and target 10, then I could get to it by using
((3 * 4) - 2)/1 = 10.
I'm trying to phrase the algorithm in pseudo-code, but so far haven't gotten too far. I'm thinking graphs are the way to go, but would definitely appreciate help on this. thanks.
This isn't meant to be the fastest solution, but rather an instructive one.
It recursively generates all equations in postfix notation
It also provides a translation from postfix to infix notation
There is no actual arithmetic calculation done, so you have to implement that on your own
Be careful about division by zero
With 4 operands, 4 possible operators, it generates all 7680 = 5 * 4! * 4^3
possible expressions.
5 is Catalan(3). Catalan(N) is the number of ways to paranthesize N+1 operands.
4! because the 4 operands are permutable
4^3 because the 3 operators each have 4 choice
This definitely does not scale well, as the number of expressions for N operands is [1, 8, 192, 7680, 430080, 30965760, 2724986880, ...].
In general, if you have n+1 operands, and must insert n operators chosen from k possibilities, then there are (2n)!/n! k^n possible equations.
Good luck!
import java.util.*;
public class Expressions {
static String operators = "+-/*";
static String translate(String postfix) {
Stack<String> expr = new Stack<String>();
Scanner sc = new Scanner(postfix);
while (sc.hasNext()) {
String t = sc.next();
if (operators.indexOf(t) == -1) {
expr.push(t);
} else {
expr.push("(" + expr.pop() + t + expr.pop() + ")");
}
}
return expr.pop();
}
static void brute(Integer[] numbers, int stackHeight, String eq) {
if (stackHeight >= 2) {
for (char op : operators.toCharArray()) {
brute(numbers, stackHeight - 1, eq + " " + op);
}
}
boolean allUsedUp = true;
for (int i = 0; i < numbers.length; i++) {
if (numbers[i] != null) {
allUsedUp = false;
Integer n = numbers[i];
numbers[i] = null;
brute(numbers, stackHeight + 1, eq + " " + n);
numbers[i] = n;
}
}
if (allUsedUp && stackHeight == 1) {
System.out.println(eq + " === " + translate(eq));
}
}
static void expression(Integer... numbers) {
brute(numbers, 0, "");
}
public static void main(String args[]) {
expression(1, 2, 3, 4);
}
}
Before thinking about how to solve the problem (like with graphs), it really helps to just look at the problem. If you find yourself stuck and can't seem to come up with any pseudo-code, then most likely there is something that is holding you back; Some other question or concern that hasn't been addressed yet. An example 'sticky' question in this case might be, "What exactly is recursive about this problem?"
Before you read the next paragraph, try to answer this question first. If you knew what was recursive about the problem, then writing a recursive method to solve it might not be very difficult.
You want to know if some expression that uses a set of numbers (each number used only once) gives you a target value. There are four binary operations, each with an inverse. So, in other words, you want to know if the first number operated with some expression of the other numbers gives you the target. Well, in other words, you want to know if some expression of the 'other' numbers is [...]. If not, then using the first operation with the first number doesn't really give you what you need, so try the other ops. If they don't work, then maybe it just wasn't meant to be.
Edit: I thought of this for an infix expression of four operators without parenthesis, since a comment on the original question said that parenthesis were added for the sake of an example (for clarity?) and the use of parenthesis was not explicitly stated.
Well, you didn't mention efficiency so I'm going to post a really brute force solution and let you optimize it if you want to. Since you can have parantheses, it's easy to brute force it using Reverse Polish Notation:
First of all, if your set has n numbers, you must use exactly n - 1 operators. So your solution will be given by a sequence of 2n - 1 symbols from {{your given set}, {*, /, +, -}}
st = a stack of length 2n - 1
n = numbers in your set
a = your set, to which you add *, /, +, -
v[i] = 1 if the NUMBER i has been used before, 0 otherwise
void go(int k)
{
if ( k > 2n - 1 )
{
// eval st as described on Wikipedia.
// Careful though, it might not be valid, so you'll have to check that it is
// if it evals to your target value great, you can build your target from the given numbers. Otherwise, go on.
return;
}
for ( each symbol x in a )
if ( x isn't a number or x is a number but v[x] isn't 1 )
{
st[k] = x;
if ( x is a number )
v[x] = 1;
go(k + 1);
}
}
Generally speaking, when you need to do something recursively it helps to start from the "bottom" and think your way up.
Consider: You have a set S of n numbers {a,b,c,...}, and a set of four operations {+,-,*,/}. Let's call your recursive function that operates on the set F(S)
If n is 1, then F(S) will just be that number.
If n is 2, F(S) can be eight things:
pick your left-hand number from S (2 choices)
then pick an operation to apply (4 choices)
your right-hand number will be whatever is left in the set
Now, you can generalize from the n=2 case:
Pick a number x from S to be the left-hand operand (n choices)
Pick an operation to apply
your right hand number will be F(S-x)
I'll let you take it from here. :)
edit: Mark poses a valid criticism; the above method won't get absolutely everything. To fix that problem, you need to think about it in a slightly different way:
At each step, you first pick an operation (4 choices), and then
partition S into two sets, for the left and right hand operands,
and recursively apply F to both partitions
Finding all partitions of a set into 2 parts isn't trivial itself, though.
Your best clue about how to approach this problem is the fact that your teacher/professor wants you to use recursion. That is, this isn't a math problem - it is a search problem.
Not to give too much away (it is homework after all), but you have to spawn a call to the recursive function using an operator, a number and a list containing the remaining numbers. The recursive function will extract a number from the list and, using the operation passed in, combine it with the number passed in (which is your running total). Take the running total and call yourself again with the remaining items on the list (you'll have to iterate the list within the call but the sequence of calls is depth-first). Do this once for each of the four operators unless Success has been achieved by a previous leg of the search.
I updated this to use a list instead of a stack
When the result of the operation is your target number and your list is empty, then you have successfully found the set of operations (those that traced the path to the successful leaf) - set the Success flag and unwind. Note that the operators aren't on a list nor are they in the call: the function itself always iterates over all four. Your mechanism for "unwinding" the operator sequence from the successful leaf to get the sequence is to return the current operator and number prepended to the value returned by recursive call (only one of which will be successful since you stop at success - that, obviously, is the one to use). If none are successful, then what you return isn't important anyhow.
Update This is much harder when you have to consider expressions like the one that Daniel posted. You have combinatorics on the numbers and the groupings (numbers due to the fact that / and - are order sensitive even without grouping and grouping because it changes precedence). Then, of course, you also have the combinatorics of the operations. It is harder to manage the differences between (4 + 3) * 2 and 4 + (3 * 2) because grouping doesn't recurse like operators or numbers (which you can just iterate over in a breadth-first manner while making your (depth-first) recursive calls).
Here's some Python code to get you started: it just prints all the possible expressions, without worrying too much about redundancy. You'd need to modify it to evaluate expressions and compare to the target number, rather than simply printing them.
The basic idea is: given a set S of numbers, partition S into two subsets left and right in all possible ways (where we don't care about the order or the elements in left and right), such that left and right are both nonempty. Now for each of these partitions, find all ways of combining the elements in left (recursively!), and similarly for right, and combine the two resulting values with all possible operators. The recursion bottoms out when a set has just one element, in which case there's only one value possible.
Even if you don't know Python, the expressions function should be reasonably easy to follow; the splittings function contains some Python oddities, but all it does is to find all the partitions of the list l into left and right pieces.
def splittings(l):
n = len(l)
for i in xrange(2**n):
left = [e for b, e in enumerate(l) if i & 2**b]
right = [e for b, e in enumerate(l) if not i & 2**b]
yield left, right
def expressions(l):
if len(l) == 1:
yield l[0]
else:
for left, right in splittings(l):
if not left or not right:
continue
for el in expressions(left):
for er in expressions(right):
for operator in '+-*/':
yield '(' + el + operator + er + ')'
for x in expressions('1234'):
print x
pusedo code:
Works(list, target)
for n in list
tmp=list.remove(n)
return Works(tmp,target+n) or Works(tmp,target-n) or Works(tmp, n-target) or ...
then you just have to put the base case in. I think I gave away to much.