Following code is part of contnrs unit of FreePascal
constructor TFPCustomHashTable.Create;
begin
CreateWith(196613,#RSHash);
end;
I am curious about 196613. I know it is hash table size. Is there any particular reason why this value is used?
In my test, constructor took about 3-4 ms to execute, which in my particular situation is not accepted. I suspect this is related to this constant value.
Update:
My question are:
Why 196613 is chosen? Why not other prime number?
Does it affect constructor call execution time?
196613 is one of the numbers being recommended for hash tables sizes (prime and far away from powers of two), for more info see e.g. https://planetmath.org/goodhashtableprimes.
It affects the constructor call execution time, yes. You can always construct TFPCustomHashTable using CreateWith and pass a size of your choice (any number is fine, as resizing algorithm checks for suitable sizes anyways) as well as your own hash function (or the pre-defined RSHash):
MyHashTable:=TFPCustomHashTable.CreateWith(193,#RSHash);
Keep in mind though, that resizing a hash table is an expensive operation as it requires to recalculate the hash function for all elements, so starting with a too small value is neither a good idea.
Related
I was reading up on the std::string class in C++ and noticed there are quite a few different constructors available giving us a wide set of initialization features. This got me wondering how a compiler picks which constructor to choose when given parameters, or in the case of overloads, how a compiler matches a function signature with a given set of parameters.
If we have the following functions declared in pseudo-code:
function f1(int numberHere) {
//....do something
}
function f1(int numberHere, string stringHere) {
//....do something
}
And I decide to call f1(4), there are obviously two options to choose from, but what if there are 10000 options/signatures? Would it take proportionally longer? If so, what takes longer? Does the compiler have some sneaky O(n) way to index overloads such that it can call the right one in O(1) time once the program is running or would it compile in O(1) no matter how many overloads exist but take longer to run the finished result because of on-the-fly signature matching?
Can this question even be answered effectively?
Thanks!
Matching function signatures is actually not different from any other search or lookup problem. There are three basic ways to do it depending on the data structure you are storing the available function signatures in:
Use an unsorted list or array and get O(n) time complexity.
Use a sorted array or a tree-like structure and get O(log(n)). (You can sort by type of 1st argument, then 2nd and so on, assuming that each type has an integer id assigned to it.)
Use a hash map and get O(1).
But I doubt that time complxity has any practical relevance in this case. It describes the asymptotic behaviour of algorithms for large values of n. Even for n=100, an unsorted array search might be faster than hash map lookup because it has less overhead.
And from a usability point of view it is a very bad idea to design an API having functions with 10 or even 100 overloads.
The question
What are the ways of coercing octave to create a real copy of whatever object? Structures are the main interest.
My underlying problem
In my problem I'm obtaining a rather large structure from another function in a loop but for the current task only a few pieces of it are needed. For example:
for i=1:many
res=solver(params);
store1{i}=res.string1;
store2{i}=res.arr(:,1);
end
res is a sizable chunk of data and due to lazy-copy those store-s are references to tiny portions of bytes in that chunk. After I store those tiny portions, I don't need res itself, however, since middle of that chunk is referenced by store, the memory area is unfit for res obtained on the next iteration (they are of the same size) and thus another sizable piece of memory is allocated, which is then again crossed by few tiny links an so on.
Without storing parts of res, the program successfully keeps the memory consumption same after first couple of iterations.
So how do I make a complete copy of structure field?
I've tried using struct-related functions like rmfield but those keep references instead of their own objects.
I've tried to wrap the assignment of in its own function:
new_struct=copy( rmfield(old_struct,"bigdata"));
function c=copy(a);
c=a;
end;
This by the way doesn't work even for arrays.
I'm interested in method applicable to any generic variable.
Minimal working example of the problem
a=cell(3,1);
for i=1:length(a);
r=rand(100000,1000);
a{i}=r(1:100,end);
whos; fflush(stdout);
pause(2);
end;
The above code will cause memory usage to gradually grow by far more than 8.08 kb reported by whos due to references stored by a{i} blocking bigger memory block than they actually need. If you force the proper copy, the problem is not present.
Numerical arrays
For numeric types addition of zero is enough to warrant a new array.
c=a+0;
Strings
For string which is 1 x n char array, something along the following lines will work:
c=[a "a"](1:end-1);
Multidimensional char arrays will require concatenation with a column:
c=[a true(size(a,1),1)](:,1:end-1);
Here true is used to generate dummy array of size compatible with char. (There seems to be no procedural method of generating char array of arbitrary size) char(zeros(size(a,1),1)) and char(true(size(a,1),1)) caused excess memory usage during their creation on some calls.
Note that empty concatenation c=[a ""]; will not result in a copying. Also it is possible to do c=[a+0 ""]; which will result in a copying due to +0 but that one infers type conversions to and from double which is 8 times larger in size. (char(zeros( doesn't seem to cause that)
Other types
In general you can use casting for the types allowed by it in order to not tailor the expressions manually as I had to do above:
typelist={"double","single","char"}; %full list of supported types is available in the link
class_of_a = typelist{ isa(a,typelist) };
c=typecast( [typecast(a,'single'); single(1)] (1:end-1), class_of_a);
Single is seemingly smallest datatype available in octave.
Note that logical is not supported by this method.
Copying structures
Apparently you'd have to write your own function to go around struct fields, copy them with above methods and recursively go to substructs.
(As it doesn't involve complexities relevant here, I'd rather leave that to be done by those who actually needs that, my own problem being solved by +0's.)
In my template-matching code I need the user to pass a floating-point parameter, which specifies whether the algorithm should concentrate only on the best matches (thus work faster) or analyse even low-probability areas (making it slower).
The parameter is linear and normalized such that possible values are in range <0, 1>. It doesn't matter whether the number of resulting matches increases or decreases as the parameter grows, as this can be easily changed. The default value is around 0.5; when the value is on one end of the range, the algorithm should possibly return only one match (and work fast); whereas the other end should mean lots of possible matches and long processing time.
What name should I choose for this parameter such that it makes sense to the end-user? I've been thinking about MatchingQuality or MatchingDepth but neither seems appropriate and self-explanatory.
I would probably call it matchingAccuracy, matchingPrecision or something like that.
How about MatchThresholdCoefficient?
It goes without saying that using hard-coded, hex literal pointers is a disaster:
int *i = 0xDEADBEEF;
// god knows if that location is available
However, what exactly is the danger in using hex literals as variable values?
int i = 0xDEADBEEF;
// what can go wrong?
If these values are indeed "dangerous" due to their use in various debugging scenarios, then this means that even if I do not use these literals, any program that during runtime happens to stumble upon one of these values might crash.
Anyone care to explain the real dangers of using hex literals?
Edit: just to clarify, I am not referring to the general use of constants in source code. I am specifically talking about debug-scenario issues that might come up to the use of hex values, with the specific example of 0xDEADBEEF.
There's no more danger in using a hex literal than any other kind of literal.
If your debugging session ends up executing data as code without you intending it to, you're in a world of pain anyway.
Of course, there's the normal "magic value" vs "well-named constant" code smell/cleanliness issue, but that's not really the sort of danger I think you're talking about.
With few exceptions, nothing is "constant".
We prefer to call them "slow variables" -- their value changes so slowly that we don't mind recompiling to change them.
However, we don't want to have many instances of 0x07 all through an application or a test script, where each instance has a different meaning.
We want to put a label on each constant that makes it totally unambiguous what it means.
if( x == 7 )
What does "7" mean in the above statement? Is it the same thing as
d = y / 7;
Is that the same meaning of "7"?
Test Cases are a slightly different problem. We don't need extensive, careful management of each instance of a numeric literal. Instead, we need documentation.
We can -- to an extent -- explain where "7" comes from by including a tiny bit of a hint in the code.
assertEquals( 7, someFunction(3,4), "Expected 7, see paragraph 7 of use case 7" );
A "constant" should be stated -- and named -- exactly once.
A "result" in a unit test isn't the same thing as a constant, and requires a little care in explaining where it came from.
A hex literal is no different than a decimal literal like 1. Any special significance of a value is due to the context of a particular program.
I believe the concern raised in the IP address formatting question earlier today was not related to the use of hex literals in general, but the specific use of 0xDEADBEEF. At least, that's the way I read it.
There is a concern with using 0xDEADBEEF in particular, though in my opinion it is a small one. The problem is that many debuggers and runtime systems have already co-opted this particular value as a marker value to indicate unallocated heap, bad pointers on the stack, etc.
I don't recall off the top of my head just which debugging and runtime systems use this particular value, but I have seen it used this way several times over the years. If you are debugging in one of these environments, the existence of the 0xDEADBEEF constant in your code will be indistinguishable from the values in unallocated RAM or whatever, so at best you will not have as useful RAM dumps, and at worst you will get warnings from the debugger.
Anyhow, that's what I think the original commenter meant when he told you it was bad for "use in various debugging scenarios."
There's no reason why you shouldn't assign 0xdeadbeef to a variable.
But woe betide the programmer who tries to assign decimal 3735928559, or octal 33653337357, or worst of all: binary 11011110101011011011111011101111.
Big Endian or Little Endian?
One danger is when constants are assigned to an array or structure with different sized members; the endian-ness of the compiler or machine (including JVM vs CLR) will affect the ordering of the bytes.
This issue is true of non-constant values, too, of course.
Here's an, admittedly contrived, example. What is the value of buffer[0] after the last line?
const int TEST[] = { 0x01BADA55, 0xDEADBEEF };
char buffer[BUFSZ];
memcpy( buffer, (void*)TEST, sizeof(TEST));
I don't see any problem with using it as a value. Its just a number after all.
There's no danger in using a hard-coded hex value for a pointer (like your first example) in the right context. In particular, when doing very low-level hardware development, this is the way you access memory-mapped registers. (Though it's best to give them names with a #define, for example.) But at the application level you shouldn't ever need to do an assignment like that.
I use CAFEBABE
I haven't seen it used by any debuggers before.
int *i = 0xDEADBEEF;
// god knows if that location is available
int i = 0xDEADBEEF;
// what can go wrong?
The danger that I see is the same in both cases: you've created a flag value that has no immediate context. There's nothing about i in either case that will let me know 100, 1000 or 10000 lines that there is a potentially critical flag value associated with it. What you've planted is a landmine bug that, if I don't remember to check for it in every possible use, I could be faced with a terrible debugging problem. Every use of i will now have to look like this:
if (i != 0xDEADBEEF) { // Curse the original designer to oblivion
// Actual useful work goes here
}
Repeat the above for all of the 7000 instances where you need to use i in your code.
Now, why is the above worse than this?
if (isIProperlyInitialized()) { // Which could just be a boolean
// Actual useful work goes here
}
At a minimum, I can spot several critical issues:
Spelling: I'm a terrible typist. How easily will you spot 0xDAEDBEEF in a code review? Or 0xDEADBEFF? On the other hand, I know that my compile will barf immediately on isIProperlyInitialised() (insert the obligatory s vs. z debate here).
Exposure of meaning. Rather than trying to hide your flags in the code, you've intentionally created a method that the rest of the code can see.
Opportunities for coupling. It's entirely possible that a pointer or reference is connected to a loosely defined cache. An initialization check could be overloaded to check first if the value is in cache, then to try to bring it back into cache and, if all that fails, return false.
In short, it's just as easy to write the code you really need as it is to create a mysterious magic value. The code-maintainer of the future (who quite likely will be you) will thank you.
The word seems to get used in a number of contexts. The best I can figure is that they mean a variable that can't change. Isn't that what constants/finals (darn you Java!) are for?
An invariant is more "conceptual" than a variable. In general, it's a property of the program state that is always true. A function or method that ensures that the invariant holds is said to maintain the invariant.
For instance, a binary search tree might have the invariant that for every node, the key of the node's left child is less than the node's own key. A correctly written insertion function for this tree will maintain that invariant.
As you can tell, that's not the sort of thing you can store in a variable: it's more a statement about the program. By figuring out what sort of invariants your program should maintain, then reviewing your code to make sure that it actually maintains those invariants, you can avoid logical errors in your code.
It is a condition you know to always be true at a particular place in your logic and can check for when debugging to work out what has gone wrong.
The magic of wikipedia: Invariant (computer science)
In computer science, a predicate that,
if true, will remain true throughout a
specific sequence of operations, is
called (an) invariant to that
sequence.
This answer is for my 5 year old kid. Do not think of an invariant as a constant or fixed numerical value. But it can be. However, it is more than that.
Rather, an invariant is something like of a fixed relationship between varying entities. For example, your age will always be less than that compared to your biological parents. Both your age, and your parent's age changes in the passage of time, but the relationship that i mentioned above is an invariant.
An invariant can also be a numerical constant. For example, the value of pi is an invariant ratio between the circle's circumference over its diameter. No matter how big or small the circle is, that ratio will always be pi.
I usually view them more in terms of algorithms or structures.
For example, you could have a loop invariant that could be asserted--always true at the beginning or end of each iteration. That is, if your loop was supposed to process a collection of objects from one stack to another, you could say that |stack1|+|stack2|=c, at the top or bottom of the loop.
If the invariant check failed, it would indicate something went wrong. In this example, it could mean that you forgot to push the processed element onto the final stack, etc.
As this line states:
In computer science, a predicate that, if true, will remain true throughout a specific sequence of operations, is called (an) invariant to that sequence.
To better understand this hope this example in C++ helps.
Consider a scenario where you have to get some values and get the total count of them in a variable called as count and add them in a variable called as sum
The invariant (again it's more like a concept):
// invariant:
// we have read count grades so far, and
// sum is the sum of the first count grades
The code for the above would be something like this,
int count=0;
double sum=0,x=0;
while (cin >> x) {
++count;
sum+=x;
}
What the above code does?
1) Reads the input from cin and puts them in x
2) After one successful read, increment count and sum = sum + x
3) Repeat 1-2 until read stops ( i.e ctrl+D)
Loop invariant:
The invariant must be True ALWAYS. So initially you start out your code with just this
while(cin>>x){
}
This loop reads data from standard input and stores in x. Well and good. But the invariant becomes false because the first part of our invariant wasn't followed (or kept true).
// we have read count grades so far, and
How to keep the invariant true?
Simple! increment count.
So ++count; would do good!. Now our code becomes something like this,
while(cin>>x){
++count;
}
But
Even now our invariant (a concept which must be TRUE) is False because now we didn't satisfy the second part of our invariant.
// sum is the sum of the first count grades
So what to do now?
Add x to sum and store it in sum ( sum+=x) and the next time
cin>>x will read a new value into x.
Now our code becomes something like this,
while(cin>>x){
++count;
sum+=x;
}
Let's check
Whether code matches our invariant
// invariant:
// we have read count grades so far, and
// sum is the sum of the first count grades
code:
while(cin>>x){
++count;
sum+=x;
}
Ah!. Now the loop invariant is True always and code works fine.
The above example was taken and modified from the book Accelerated C++ by Andrew-koening and Barbara-E
Something that doesn't change within a block of code
All the answers here are great, but i felt that i can shed more light on the matter:
Invariant from a language point of view means something that never changes. The concept though comes actually from math, it's one of the popular proof techniques when combined with induction.
Here is how a proof goes, If you can find an invariant that is in the initial state, And that this invariant persists regardless of any [legal] transformation applied to the state, then you can prove that If a certain state does not have this invariant then it can never occur, no matter what sequence of transformations are applied to the initial state.
Now the previous way of thinking (again combined with induction) makes it possible to predicate the logic of computer software. Especially important when the execution goes in loops, in which an invariant can be used to prove that a certain loop will yield a certain result or that it will never change the state of a program in a certain way.
When invariant is used to predicate a loop logic its called loop invariant. It can be used outside loops, but for loops it is really important, because you often have a lot of possibilities, or an infinite number of possibilities.
Notice that i use the word "predicate" the logic of a computer software, and not prove. And that's because while in math invariant can be used as a proof, it can never prove that the computer software when executed will yield what is expected, due to the fact that the software is executed on top of many abstractions, that can never be proved that they will yield what is expected (think of the hardware abstraction for example).
Finally while theoretically and rigorously predicting software logic is only important for high critical applications like Medical, and Military ones. Invariant can still be used to aid the typical programmer when debugging. It can be used to know where at a certain location The program failed because it has failed to maintain a certain invariant - many of us use it anyway without giving a thought about it.
Class Invariant
Class Invariant is a condition which should be always true before and after calling relevant function
For example balanced tree has an Invariant which is called isBalanced. When you modify your tree through some methods (e.g. addNode, removeNode...) - isBalanced should be always true before and after modifying the tree
Following on from what it is, invariants are quite useful in writing clean code, since knowing conceptually what invariants should be present in your code allows you to easily decide how to organize your code to reach those aims. As mentioned ealier, they're also useful in debugging, as checking to see if the invariant's being maintained is often a good way of seeing if whatever manipulation you're attempting to perform is actually doing what you want it to.
It's typically a quantity that does not change under certain mathematical operations.
An example is a scalar, which does not change under rotations. In magnetic resonance imaging, for example, it is useful to characterize a tissue property by a rotational invariant, because then its estimation ideally does not depend on the orientation of the body in the scanner.
The ADT invariant specifes relationships
among the data fields (instance variables)
that must always be true before and after
the execution of any instance method.
There is an excellent example of an invariant and why it matters in the book Java Concurrency in Practice.
Although Java-centric, the example describes some code that is responsible for calculating the factors of a provided integer. The example code attempts to cache the last number provided, and the factors that were calculated to improve performance. In this scenario there is an invariant that was not accounted for in the example code which has left the code susceptible to race conditions in a concurrent scenario.