Testing whether some code works for ALL input numbers? - testing

I've got an algorithm using a single (positive integer) number as an input to produce an output. And I've got the reverse function which should do the exact opposite, going back from the output to the same integer number. This should be a unique one-to-one reversible mapping.
I've tested this for some integers, but I want to be 100% sure that it works for all of them, up to a known limit.
The problem is that if I just test every integer, it takes an unreasonably long time to run. If I use 64-bit integers, that's a lot of numbers to check if I want to check them all. On the other hand, if I only test every 10th or 100th number, I'm not going to be 100% sure at the end. There might be some awkward weird constellation in one of the 90% or 99% which I didn't test.
Are there any general ways to identify edge cases so that just those "interesting" or "risky" numbers are checked? Or should I just pick numbers at random? Or test in increasing increments?
Or to put the question another way, how can I approach this so that I gain 100% confidence that every case will be properly handled?

The approach for this is generally checking every step of the computation for potential flaws. Concerning integer math, that is overflows, underflows and rounding errors from division, basically that the mathematical result can't be represented accurately. In addition, all operations derived from this suffer similar problems.
The process of auditing then looks at single steps in turn. For example, if you want to allocate memory for N integers, you need N times the size of an integer in bytes and this multiplication can overflow. You now determine those values where the multiplication overflows and create according tests that exercise these. Note that for the example of allocating memory, proper handling typically means that the function does not allocate memory but fail.
The principle behind this is that you determine the ranges for every operation where the outcome is somehow different (like e.g. where it overflows) and then make sure via tests that both variants work. This reduces the number of tests from all possible input values to just those where you expect a significant difference.

Related

Determining a program's execution time by its length in bits?

This is a question popped into my mind while reading the halting problem, collatz conjecture and Kolmogorov complexity. I have tried to search for something similar but I was unable to find a particular topic maybe because it is not of great value or it could just be a trivial question.
For the sake of simplicity I will give three examples of programs/functions.
function one(s):
return s
function two(s):
while (True):
print s
function three(s):
for i from 0 to 10^10:
print(s)
So my questions is, if there is a way to formalize the length of a program (like the bits used to describe it) and also the internal memory used by the program, to determine the minimum/maximum number of time/steps needed to decide whether the program will terminate or run forever.
For example, in the first function the program doesn't alter its internal memory and halts after some time steps.
In the second example, the program runs forever but the program also doesn't alter its internal memory. For example, if we considered all the programs with the same length as with the program two that do not alter their state, couldn't we determine an upper bound of steps, which if surpassed we could conclude that this program will never terminate ? (If not why ?)
On the last example, the program alters its state (variable i). So, at each step the upper bound may change.
[In short]
Kolmogorov complexity suggests a way of finding the (descriptive) complexity of an object such as a piece of text. I would like to know, given a formal way of describing the memory-space used by a program (computed in runtime), if we could compute a maximum number of steps, which if surpassed would allow us to know whether this program will terminate or run forever.
Finally, I would like to suggest me any source that I might find useful and help me figure out what I am exactly looking for.
Thank you. (sorry for my English, not my native language. I hope I was clear)
If a deterministic Turing machine enters precisely the same configuration twice (which we can detect b keeping a trace of configurations seen so far), then we immediately know the TM will loop forever.
If it known in advance that a deterministic Turing machine cannot possibly use more than some fixed constant amount of its input tape, then the TM must explicitly halt or eventually enter some configuration it has already visited. Suppose the TM can use at most k tape cells, the tape alphabet is T and the set of states is Q. Then there are (|T|+1)^k * |Q| unique configurations (the number of strings over (T union blank) of length k times the number of states) and by the pigeonhole principle we know that a TM that takes that many steps must enter some configuration it has already been to before.
one: because we are given that this function does not use internal memory, we know that it either halts or loops forever.
two: because we are given that this function does not use internal memory, we know that it either halts or loops forever.
three: because we are given that this function only uses a fixed amount of internal memory (like 34 bits) we can tell in fewer than 2^34 iterations of the loop whether the TM will halt or not for any given input s, guaranteed.
Now, knowing how much tape a TM is going to use, or how much memory a program is going to use, is not a problem a TM can solve. But if you have an oracle (like a person who was able to do a proof) that tells you a correct fixed upper bound on memory, then the halting problem is solvable.

Least memory intensive way of storing small integers in VBA

Occasionally I will store the state of some system as an integer. I often find myself using small values for these states (say 1-10), since the system is relatively simple.
In general, what's the best declaration for a variable which stores small positive integers - where best is defined as fastest read/write time & smallest memory consumption? Small is here defined as 1-10, although a complete list of integer storing methods and their ranges would be useful.
Originally I used Integer as on the face of it, it uses less memory. But I have since learned that that is not the case, as it is silently converted to Long
I then used Long for the above reason, and in the knowledge that it uses less memory than Double
I have since discovered Byte and switched to that, since it stores smaller integers (0-255 or 256, I never remember which), and I guess uses less memory from it's minute name. But I don't really trust VBA and wonder if there's any internal type conversions done here too.
Boolean I thought was only 0 or 1, but I've read that any non-zero number is converted to True, does this mean it can also store numbers?
Originally I used Integer as on the face of it, it uses less memory. But I have since learned that that is not the case, as it is silently converted to Long
That's right there is no advantage in using Integer over Long because of that conversion, but Integer might be necessary when communicating with old 16 bit APIs.
Also read "Why Use Integer Instead of Long?"
I then used Long for the above reason, and in the knowledge that it uses less memory than Double
You would not decide between Long or Double because one uses less memory. You decide between them because …
you need floating point numbers (Double)
or you don't accept floating point numbers. (Long)
Deciding on memory usage in this specific case is just a very bad idea because these types are fundamentally different.
I have since discovered Byte and switched to that, since it stores smaller integers (0-255 or 256, I never remember which), and I guess uses less memory from it's minute name. But I don't really trust VBA and wonder if there's any internal type conversions done here too.
I don't see any case where you use Office/Excel and run into any memory issues by using Long instead of Byte to iterate from 1 to 10. If you need to limit it to 255 (some old APIs, whatever) then you might use Byte. If there is no need for that I would use Long just to be flexible and not run into any coding issues because you need to remember which counters are only Byte and which are Long.
E.g. If I use i for iterating I would expect Long. I see no advantage in using Byte for that case.
Stay as simple as possible. Don't do strange things one would not expect only because you can. Avoiding future coding issues is worth more than one (or three) byte of memory usage. Sometimes it is worthier to write good human readable and maintainable code than faster code especially if you can't notice the differences (which you really can't in this case). Bad readable code always results in errors or vulnerabilities sooner or later.
Boolean I thought was only 0 or 1, but I've read that any non-zero number is converted to True, does this mean it can also store numbers?
No that's wrong. Boolean is -1 for True and 0 for False. But note that if you cast e.g. a Long into Boolean which is not 0 then it will automatically cast and result in True.
But Boolean in VBA is clearly defined as:
0 = False
-1 = True
The smallest chunk of memory that can be addressed is a byte (8 bits).
I cannot guarantee that VBA Bytes are stored as bytes in all cases, but using this type you are on the safest side.
By the way, the largest byte value is 11111111b, i.e 255d. The value 256d is 100000000b which requires 9 bits.
Also note that using Bytes every possible time might be unproductive as it can have a cost in terms of running time, if numerical conversions are required, while the spared memory space may be insignificant.
Except for very special applications, this kind of micro-optimization is of no use.

Memory efficiency in If statements

I'm thinking more about how much system memory my programs will use nowadays. I'm currently doing A level Computing at college and I know that in most programs the difference will be negligible but I'm wondering if the following actually makes any difference, in any language.
Say I wanted to output "True" or "False" depending on whether a condition is true. Personally, I prefer to do something like this:
Dim result As String
If condition Then
Result = "True"
Else
Result = "False"
EndIf
Console.WriteLine(result)
However, I'm wondering if the following would consume less memory, etc.:
If condition Then
Console.WriteLine("True")
Else
Console.WriteLine("False")
EndIf
Obviously this is a very much simplified example and in most of my cases there is much more to be outputted, and I realise that in most commercial programs these kind of statements are rare, but hopefully you get the principle.
I'm focusing on VB.NET here because that is the language used for the course, but really I would be interested to know how this differs in different programming languages.
The main issue making if's fast or slow is predictability.
Modern CPU's (anything after 2000) use a mechanism called branch prediction.
Read the above link first, then read on below...
Which is faster?
The if statement constitutes a branch, because the CPU needs to decide whether to follow or skip the if part.
If it guesses the branch correctly the jump will execute in 0 or 1 cycle (1 nanosecond on a 1Ghz computer).
If it does not guess the branch correctly the jump will take 50 cycles (give or take) (1/200th of a microsecord).
Therefore to even feel these differences as a human, you'd need to execute the if statement many millions of times.
The two statements above are likely to execute in exactly the same amount of time, because:
assigning a value to a variable takes negligible time; on average less than a single cpu cycle on a multiscalar CPU*.
calling a function with a constant parameter requires the use of an invisible temporary variable; so in all likelihood code A compiles to almost the exact same object code as code B.
*) All current CPU's are multiscalar.
Which consumes less memory
As stated above, both versions need to put the boolean into a variable.
Version A uses an explicit one, declared by you; version B uses an implicit one declared by the compiler.
However version A is guaranteed to only have one call to the function WriteLine.
Whilst version B may (or may not) have two calls to the function WriteLine.
If the optimizer in the compiler is good, code B will be transformed into code A, if it's not it will remain with the redundant calls.
How bad is the waste
The call takes about 10 bytes for the assignment of the string (Unicode 2 bytes per char).
But so does the other version, so that's the same.
That leaves 5 bytes for a call. Plus maybe a few extra bytes to set up a stackframe.
So lets say due to your totally horrible coding you have now wasted 10 bytes.
Not much to worry about.
From a maintainability point of view
Computer code is written for humans, not machines.
So from that point of view code A is clearly superior.
Imagine not choosing between 2 options -true or false- but 20.
You only call the function once.
If you decide to change the WriteLine for another function you only have to change it in one place, not two or 20.
How to speed this up?
With 2 values it's pretty much impossible, but if you had 20 values you could use a lookup table.
Obviously that optimization is not worth it unless code gets executed many times.
If you need to know the precise amount of memory the instructions are going to take, you can use ildasm on your code, and see for yourself. However, the amount of memory consumed by your code is much less relevant today, when the memory is so cheap and abundant, and compilers are smart enough to see common patterns and reduce the amount of code that they generate.
A much greater concern is readability of your code: if a complex chain of conditions always leads to printing a conditionally set result, your first code block expresses this idea in a cleaner way than the second one does. Everything else being equal, you should prefer whatever form of code that you find the most readable, and let the compiler worry about optimization.
P.S. It goes without saying that Console.WriteLine(condition) would produce the same result, but that is of course not the point of your question.

How does rand() work? Does it have certain tendencies? Is there something better to use?

I have read that it has something to do with time, also you get from including time.h, so I assumed that much, but how does it work exactly? Also, does it have any tendencies towards odd or even numbers or something like that? And finally is there something with better distribution in the C standard library or the Foundation framework?
Briefly:
You use time.h to get a seed, which is an initial random number. C then does a bunch of operations on this number to get the next random number, then operations on that one to get the next, then... you get the picture.
rand() is able to touch on every possible integer. It will not prefer even or odd numbers regardless of the input seed, happily. Still, it has limits - it repeats itself relatively quickly, and in almost every implementation only gives numbers up to 32767.
C does not have another built-in random number generator. If you need a real tough one, there are many packages available online, but the Mersenne Twister algorithm is probably the most popular pick.
Now, if you are interested on the reasons why the above is true, here are the gory details on how rand() works:
rand() is what's called a "linear congruential generator." This means that it employs an equation of the form:
xn+1 = (*a****xn + ***b*) mod m
where xn is the nth random number, and a and b are some predetermined integers. The arithmetic is performed modulo m, with m usually 232 depending on the machine, so that only the lowest 32 bits are kept in the calculation of xn+1.
In English, then, the idea is this: To get the next random number, multiply the last random number by something, add a number to it, and then take the last few digits.
A few limitations are quickly apparent:
First, you need a starting random number. This is the "seed" of your random number generator, and this is where you've heard of time.h being used. Since we want a really random number, it is common practice to ask the system what time it is (in integer form) and use this as the first "random number." Also, this explains why using the same seed twice will always give exactly the same sequence of random numbers. This sounds bad, but is actually useful, since debugging is a lot easier when you control the inputs to your program
Second, a and b have to be chosen very, very carefully or you'll get some disastrous results. Fortunately, the equation for a linear congruential generator is simple enough that the math has been worked out in some detail. It turns out that choosing an a which satisfies *a***mod8 = 5 together with ***b* = 1 will insure that all m integers are equally likely, independent of choice of seed. You also want a value of a that is really big, so that every time you multiply it by xn you trigger a the modulo and chop off a lot of digits, or else many numbers in a row will just be multiples of each other. As a result, two common values of a (for example) are 1566083941 and 1812433253 according to Knuth. The GNU C library happens to use a=1103515245 and b=12345. A list of values for lots of implementations is available at the wikipedia page for LCGs.
Third, the linear congruential generator will actually repeat itself because of that modulo. This gets to be some pretty heady math, but the result of it all is happily very simple: The sequence will repeat itself after m numbers of have been generated. In most cases, this means that your random number generator will repeat every 232 cycles. That sounds like a lot, but it really isn't for many applications. If you are doing serious numerical work with Monte Carlo simulations, this number is hopelessly inadequate.
A fourth much less obvious problem is that the numbers are actually not really random. They have a funny sort of correlation. If you take three consecutive integers, (x, y, z), from an LCG with some value of a and m, those three points will always fall on the lattice of points generated by all linear combinations of the three points (1, a, a2), (0, m, 0), (0, 0, m). This is known as Marsaglia's Theorem, and if you don't understand it, that's okay. All it means is this: Triplets of random numbers from an LCG will show correlations at some deep, deep level. Usually it's too deep for you or I to notice, but its there. It's possible to even reconstruct the first number in a "random" sequence of three numbers if you are given the second and third! This is not good for cryptography at all.
The good part is that LCGs like rand() are very, very low footprint. It typically requires only 32 bits to retain state, which is really nice. It's also very fast, requiring very few operations. These make it good for noncritical embedded systems, video games, casual applications, stuff like that.
PRNGs are a fascinating topic. Wikipedia is always a good place to go if you are hungry to learn more on the history or the various implementations that are around today.
rand returns numbers generated by a pseudo-random number generator (PRNG). The sequence of numbers it returns is deterministic, based on the value with which the PRNG was initialized (by calling srand).
The numbers should be distributed such that they appear somewhat random, so, for example, odd and even numbers should be returned at roughly the same frequency. The actual implementation of the random number generator is left unspecified, so the actual behavior is specific to the implementation.
The important thing to remember is that rand does not return random numbers; it returns pseudo-random numbers, and the values it returns are determined by the seed value and the number of times rand has been called. This behavior is fine for many use cases, but is not appropriate for others (for example, rand would not be appropriate for use in many cryptographic applications).
How does rand() work?
http://en.wikipedia.org/wiki/Pseudorandom_number_generator
I have read that it has something to
do with time, also you get from
including time.h
rand() has nothing at all to do with the time. However, it's very common to use time() to obtain the "seed" for the PRNG so that you get different "random" numbers each time your program is run.
Also, does it have any tendencies
towards odd or even numbers or
something like that?
Depends on the exact method used. There's one popular implementation of rand() that alternates between odd and even numbers. So avoid writing code like rand() % 2 that depends on the lowest bit being random.

Storage algorithm question - verify sequential data with little memory

I found this on an "interview questions" site and have been pondering it for a couple of days. I will keep churning, but am interested what you guys think
"10 Gbytes of 32-bit numbers on a magnetic tape, all there from 0 to 10G in random order. You have 64 32 bit words of memory available: design an algorithm to check that each number from 0 to 10G occurs once and only once on the tape, with minimum passes of the tape by a read head connected to your algorithm."
32-bit numbers can take 4G = 2^32 different values. There are 2.5*2^32 numbers on tape total. So after 2^32 count one of numbers will repeat 100%. If there were <= 2^32 numbers on tape then it was possible that there are two different cases – when all numbers are different or when at least one repeats.
It's a trick question, as Michael Anderson and I have figured out. You can't store 10G 32b numbers on a 10G tape. The interviewer (a) is messing with you and (b) is trying to find out how much you think about a problem before you start solving it.
The utterly naive algorithm, which takes as many passes as there are numbers to check, would be to walk through and verify that the lowest number is there. Then do it again checking that the next lowest is there. And so on.
This requires one word of storage to keep track of where you are - you could cut down the number of passes by a factor of 64 by using all 64 words to keep track of where you're up to in several different locations in the search space - checking all of your current ones on each pass. Still O(n) passes, of course.
You could probably cut it down even more by using portions of the words - given that your search space for each segment is smaller, you won't need to keep track of the full 32-bit range.
Perform an in-place mergesort or quicksort, using tape for storage? Then iterate through the numbers in sequence, tracking to see that each number = previous+1.
Requires cleverly implemented sort, and is fairly slow, but achieves the goal I believe.
Edit: oh bugger, it's never specified you can write.
Here's a second approach: scan through trying to build up to 30-ish ranges of contiginous numbers. IE 1,2,3,4,5 would be one range, 8,9,10,11,12 would be another, etc. If ranges overlap with existing, then they are merged. I think you only need to make a limited number of passes to either get the complete range or prove there are gaps... much less than just scanning through in blocks of a couple thousand to see if all digits are present.
It'll take me a bit to prove or disprove the limits for this though.
Do 2 reduces on the numbers, a sum and a bitwise XOR.
The sum should be (10G + 1) * 10G / 2
The XOR should be ... something
It looks like there is a catch in the question that no one has talked about so far; the interviewer has only asked the interviewee to write a program that CHECKS
(i) if each number that makes up the 10G is present once and only once--- what should the interviewee do if the numbers in the given list are present multple times? should he assume that he should stop execting the programme and throw exception or should he assume that he should correct the mistake by removing the repeating number and replace it with another (this may actually be a costly excercise as this involves complete reshuffle of the number set)? correcting this is required to perform the second step in the question, i.e. to verify that the data is stored in the best possible way that it requires least possible passes.
(ii) When the interviewee was asked to only check if the 10G weight data set of numbers are stored in such a way that they require least paases to access any of those numbers;
what should the interviewee do? should he stop and throw exception the moment he finds an issue in the algorithm they were stored in, or correct the mistake and continue till all the elements are sorted in the order of least possible passes?
If the intension of the interviewer is to ask the interviewee to write an algorithm that finds the best combinaton of numbers that can be stored in 10GB, given 64 32 Bit registers; and also to write an algorithm to save these chosen set of numbers in the best possible way that require least number of passes to access each; he should have asked this directly, woudn't he?
I suppose the intension of the interviewer may be to only see how the interviewee is approaching the problem rather than to actually extract a working solution from the interviewee; wold any buy this notion?
Regards,
Samba