I came across these two implementations of binary search in the book "Competitive Programmer's Handbook" https://cses.fi/book/book.pdf.
Method 1:
int a = 0, b = n-1;
while (a <= b) {
int k = (a+b)/2;
if (array[k] == x) {
// x found at index k
}
if (array[k] > x)
b = k-1;
else
a = k+1;
}
Method 2:
int k = 0;
for (int b = n/2; b >= 1; b /= 2){
while (k+b < n && array[k+b] <= x)
k += b;
}
if (array[k] == x){
// x found at index k
}
I guess method 2 is not exactly binary search.
I understand that Both method 1 and method 2 have O(log n) complexity. Also the code for method 2 is simpler and therefore might result in fewer bugs.
My questions are:
Is there any improvement in performance when method-2 is used?
Does method-2 have any other advantage?
For such short code and so few differences, it is impossible to do any prediction. The time performance will depend on how the compiler optimizes, but also on the distribution of the keys in the array (in particular, the probability of a hit rather than a miss).
I disagree with all comments "against" the second method (even claimed buggy when it is perfectly correct). It is based on a principle that potentially makes it better: there's only one test in the body of the loop.
Having a comparison for equality (Method 1) gives the false feeling that the algorithm will terminate early when the key is found and make the search faster*. But this is not so true, because for half of the keys the full depth of the decision tree is anyway necessary, and this not counter-balanced by the fact that there are two comparisons instead of one.
*In fact, you just spare one test on average !
Only benchmarking can tell you if one of the methods is faster with particular test cases. My bet is that the distributions of the running times overlap a lot. (Not counting that it is virtually impossible to benchmark such a fast algorithm in a way that is representative of its behavior in real context.)
Last comment: the method 2 is a binary search, while in fact method 1 is ternary !
Problem Statement:
You are given two non-negative integers: the longs pairOr and pairSum.
Determine whether it is possible that for two non-negative integers A and B we have both:
A or B = pairOr
A + B = pairSum
Above, "or" denotes the bitwise-or operator.
Return True if we can find such A and B, and False if not.
My Algorithm goes like this:
I've taken the equation: A | B = X and A + B =Y,
Now after substituting A's value from 2nd Equation, (Y-B) | B= X.
I'm going to traverse from 0 till Y (in place of B) to check if the above equation is true.
Code Snippet:
boolean isPossible(long orAandB,long plusAandB) {
for(long i=0;i<=plusAandB;i++) {
if(((plusAandB-i)|i)==orAandB ){
return true;
}
}
return false;
It will give TLE if the value of plusAndB is of number 10^18. Could you please help me optimize?
You don't need the full iteration, giving O(N). There's a way to do it in O(logN).
But completely solving the problem for you takes away most of the fun... ;-), so here's the main clue:
Your equation (Y-B) | B= X is one great observation, and the second is to have a look at this equation bit by bit, starting from the right (so you don't have to worry about borrow-bits in the first place). Which last-bit combinations of Y, X, and B can make your equation true? And if you found a B bit, how do you continue recursively with the higher bits (don't forget that subtraction may need a borrow)? I hope you remember the rules for subtracting binary numbers.
And keeping in mind that the problem only asks for true or false, not for any specific A or B value, can save you exponential complexity.
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.
My last question (Understanding Frama-C slicer results) was on a precise example, but as I said, my goal is to know if it is possible to do some conditioned slicing (forward and backward) with Frama-C. Is it possible?
More precisely, I can't obtain a precise slice of this program :
/*# requires a >= b;
# assigns \nothing;
# ensures \result == a;
*/
int example4_instr1(int a, int b){
int max = a;
if(a < b)
max = b;
return max;
}
Is it possible, by using good parameters/options, to get what I want in this case/in the general case?
As Pascal mentioned in his answer to your previous question, Frama-C's backward and forward slicing are based on the results of an analysis called Value Analysis. This analysis is non-relational; this means that it only keeps information about the numeric range of variables, but not about e.g. the difference between two variables. Thus, it is not able to keep track of your inequality a >= b. This explains why both branches of the test if (a < b) appear to be followed.
Without more information from either the user (but, in this example, nothing that you could write will help the Value Analysis), or another analysis, the backward slicing must consider that the if may or may not be taken. This unfortunately results in a program from which nothing has been sliced away.
Ok, so still getting use to the basics with processing, and I am unsure if this is the correct way to do multiple arithmetic expressions with the same data, should I be typing each as its own code, or doing it like this?
here is the question;
Write the statements which perform the following arithmetic operations (note: the variable names can be changed). (i) a=50 b=60
c=43 result1 = a+b+c result2=a*b result3 = a/b
here is my code;
short a = 50;
short b = 60;
short c = 43;
int sum = a+b+c; // Subsection i
print (sum);
int sum2 = a*b; // Subsection ii
print (sum2);
int sum3 =a/b; // Subsection iii
print (sum3);
Using the same variable for a in all three expressions, like you're doing, is the right way. This means that if you wanted to change a, b, or c you'd only have to change it in one place.
You didn't mention what language, but there are a couple problems. It's hard to say what your knowledge level is, so I apologize in advance if this is beyond the scope of the assignment.
First, your variables are defined as short but they end up being assigned to int variables. That's implicit typecasting. Granted, short is basically a subset of int in most languages, but you should be aware that you're doing it and implicit typecasting can cause problems. It's slightly bad practice.
Second, your variable names are all called sumX but only one is a sum. That's definitely bad practice. Variable names should be meaningful and represent what they actually are.
Third, your division is dividing two integers and storing the result into an integer. This means that if you're using a strongly typed language you will be truncating the fractional portion of the quotient. You will get 0 as your output: 50 / 60 = 0.8333[...] which when converted to an integer truncates to 0. You may wish to consider using double or float as your data types if your answer is supposed to be accurate.