Why does this R function not short-circuit properly? - r

I'm working my way through the Data Science courses at DataCamp. (Not a plug.) One of the practice lessons has the following completed solution:
# logs is available in your workspace
extract_info <- function(x, property = "success", include_all = TRUE) {
info <- c()
for (log in x) {
if (include_all || !log$success) {
info <- c(info, log[[property]])
}
}
return(info)
}
# Call extract_info() on logs, no additional arguments
extract_info(logs)
# Call extract_info() on logs, set include_all to FALSE
extract_info(logs, include_all = FALSE)
The first call (extract_info(logs)) works as I would expect it to: it returns a vector containing all the log entries (regardless of the value of log$success).
The second call (extract_info(logs, include_all = FALSE)) does not return the results I would expect. It returns a vector containing only those results where log$success evaluates to FALSE.
It seems to me that the use of the || operator should cause the if block to short-circuit, and the second call should return nothing. From what I can tell, R evaluates expressions from left to right; but this looks like it's evaluating from right to left.
Can someone explain what's going on here?
(According to the site, this is the correct solution, and there's nothing wrong with the code. I want to know why it works the way it does. Even if the answer is that I'm overlooking something painfully obvious and stupid.)

Well || is the "or" operator. You don't short circuit the "or" operator with a FALSE value; you basically ignore that parameter and just look at the next one because you are looking for any TRUE value.
Assume a is a boolean value. These should be equivalent (<==>).
# or
FALSE || a <==> a
TRUE || a <==> TRUE
# and
TRUE && a <==> a
FALSE && a <==> FALSE

It seems like this was a temporary confusion.
|| is OR and so if either condition evaluates to TRUE, the compound expression evaluates to TRUE. If include_all was TRUE, you could short-circuit the expression, but when include_all is FALSE, you must wait to see what the other part is.

Related

How to pass FsCheck Test Correctly

let list p = if List.contains " " p || List.contains null p then false else true
I have such a function to check if the list is well formatted or not. The list shouldn't have an empty string and nulls. I don't get what I am missing since Check.Verbose list returns falsifiable output.
How should I approach the problem?
I think you don't quite understand FsCheck yet. When you do Check.Verbose someFunction, FsCheck generates a bunch of random input for your function, and fails if the function ever returns false. The idea is that the function you pass to Check.Verbose should be a property that will always be true no matter what the input is. For example, if you reverse a list twice then it should return the original list no matter what the original list was. This property is usually expressed as follows:
let revTwiceIsSameList (lst : int list) =
List.rev (List.rev lst) = lst
Check.Verbose revTwiceIsSameList // This will pass
Your function, on the other hand, is a good, useful function that checks whether a list is well-formed in your data model... but it's not a property in the sense that FsCheck uses the term (that is, a function that should always return true no matter what the input is). To make an FsCheck-style property, you want to write a function that looks generally like:
let verifyMyFunc (input : string list) =
if (input is well-formed) then // TODO: Figure out how to check that
myFunc input = true
else
myFunc input = false
Check.Verbose verifyMyFunc
(Note that I've named your function myFunc instead of list, because as a general rule, you should never name a function list. The name list is a data type (e.g., string list or int list), and if you name a function list, you'll just confuse yourself later on when the same name has two different meanings.)
Now, the problem here is: how do you write the "input is well-formed" part of my verifyMyFunc example? You can't just use your function to check it, because that would be testing your function against itself, which is not a useful test. (The test would essentially become "myFunc input = myFunc input", which would always return true even if your function had a bug in it — unless your function returned random input, of course). So you'd have to write another function to check if the input is well-formed, and here the problem is that the function you've written is the best, most correct way to check for well-formed input. If you wrote another function to check, it would boil down to not (List.contains "" || List.contains null) in the end, and again, you'd be essentially checking your function against itself.
In this specific case, I don't think FsCheck is the right tool for the job, because your function is so simple. Is this a homework assignment, where your instructor is requiring you to use FsCheck? Or are you trying to learn FsCheck on your own, and using this exercise to teach yourself FsCheck? If it's the former, then I'd suggest pointing your instructor to this question and see what he says about my answer. If it's the latter, then I'd suggest finding some slightly more complicated function to use to learn FsCheck. A useful function here would be one where you can find some property that should always be true, like in the List.rev example (reversing a list twice should restore the original list, so that's a useful property to test with). Or if you're having trouble finding an always-true property, at least find a function that you can implement in at least two different ways, so that you can use FsCheck to check that both implementations return the same result for any given input.
Adding to #rmunn's excellent answer:
if you wanted to test myFunc (yes I also renamed your list function) you could do it by creating some fixed cases that you already know the answer to, like:
let myFunc p = if List.contains " " p || List.contains null p then false else true
let tests =
testList "myFunc" [
testCase "empty list" <| fun()-> "empty" |> Expect.isTrue (myFunc [ ])
testCase "nonempty list" <| fun()-> "hi" |> Expect.isTrue (myFunc [ "hi" ])
testCase "null case" <| fun()-> "null" |> Expect.isFalse (myFunc [ null ])
testCase "empty string" <| fun()-> "\"\"" |> Expect.isFalse (myFunc [ "" ])
]
Tests.runTests config tests
Here I am using a testing library called Expecto.
If you run this you would see one of the tests fails:
Failed! myFunc/empty string:
"". Actual value was true but had expected it to be false.
because your original function has a bug; it checks for space " " instead of empty string "".
After you fix it all tests pass:
4 tests run in 00:00:00.0105346 for myFunc – 4 passed, 0 ignored, 0
failed, 0 errored. Success!
At this point you checked only 4 simple and obvious cases with zero or one element each. Many times functions fail when fed more complex data. The problem is how many more test cases can you add? The possibilities are literally infinite!
FsCheck
This is where FsCheck can help you. With FsCheck you can check for properties (or rules) that should always be true. It takes a little bit of creativity to think of good ones to test for and granted, sometimes it is not easy.
In your case we can test for concatenation. The rule would be like this:
If two lists are concatenated the result of MyFunc applied to the concatenation should be true if both lists are well formed and false if any of them is malformed.
You can express that as a function this way:
let myFuncConcatenation l1 l2 = myFunc (l1 # l2) = (myFunc l1 && myFunc l2)
l1 # l2 is the concatenation of both lists.
Now if you call FsCheck:
FsCheck.Verbose myFuncConcatenation
It tries a 100 different combinations trying to make it fail but in the end it gives you the Ok:
0:
["X"]
["^"; ""]
1:
["C"; ""; "M"]
[]
2:
[""; ""; ""]
[""; null; ""; ""]
3:
...
Ok, passed 100 tests.
This does not necessarily mean your function is correct, there still could be a failing combination that FsCheck did not try or it could be wrong in a different way. But it is a pretty good indication that it is correct in terms of the concatenation property.
Testing for the concatenation property with FsCheck actually allowed us to call myFunc 300 times with different values and prove that it did not crash or returned an unexpected value.
FsCheck does not replace case by case testing, it complements it:
Notice that if you had run FsCheck.Verbose myFuncConcatenation over the original function, which had a bug, it would still pass. The reason is the bug was independent of the concatenation property. This means that you should always have the case by case testing where you check the most important cases and you can complement that with FsCheck to test other situations.
Here are other properties you can check, these test the two false conditions independently:
let myFuncHasNulls l = if List.contains null l then myFunc l = false else true
let myFuncHasEmpty l = if List.contains "" l then myFunc l = false else true
Check.Quick myFuncHasNulls
Check.Quick myFuncHasEmpty
// Ok, passed 100 tests.
// Ok, passed 100 tests.

how stacks are formed and value from a method return when the method has TWO recursive calls of itself from within itself

I have tried creating stacks for recursive inorder,preorder,postoreder traversal for binary tree and I was doing it pretty well. In other cases like, for example, for a test case my answer should be 'true',say.And, for example,
boolean method(root)
{
// more code
method(root.left());
method(root.right());
}
,somewhere,the call of method(root.left()) returns false and a call of method(root.right()) returns true that should be our answer. But since call of method(root.left() ) completes first and somewhere, in between it's execution, it might have returned false. then how do we get our result true from method(root.right())?? I think it is related to how stacks are formed and values from a method are returned when recursive calls ,in this way, happen.Explain it and correct me if I am wrong.
You need to return values. The method need to make use of the returned values in its logic to stop/continue the search.
You need to have that the base cases return either true of false. Then when doing the first recursive call you need only do the first if the result is true. The second recursive call would be the result of the method if it's needed. Thus you are looking at something like this:
boolean method(root)
{
if( root == null ) { // base case 1
return false;
}
if( root.value == someValue ) { // base case 2, what should be a positive
return true;
}
// default search left first and return true if true
if( method(root.left()) ) {
return true;
}
// default search right and return true if true
if( method(root.right()) ){
return true;
}
// return false since neither recursive calls were true
return false;
}
This is very verbose and can be written like this instead:
boolean method(root)
{
return root != null && ( root.value == someValue ||
method(root.left()) ||
method(root.right()));
}
I find the last more readable but novices might find the more verbose first one to be more clear.
In both the callee resumes operation after the first recursive call (which might have had it's share of calls as well) and continues it's logic and recurses on the right side if needed.
Don't care about the system stack. Care about the base case and test them. Then do the simplest of added complexity to do the default case so that you see the problem becoming smaller in the recursive call(s). It's much better going from simple to more complex than to try figuring this stuff out by starting at a large tree looking at whats happening with a very deep recursive round.

Catching use of return without parentheses in R

I just tracked down a silly bug in some R code that I had written. The bug was equivalent to this:
brokenEarlyReturn = function(x=TRUE) {
if (x) return # broken with bare return
stop("Should not get here if x is TRUE. x == ", x)
}
brokenEarlyReturn(TRUE)
# Error in brokenEarlyReturn(TRUE) :
# Should not get here if x is TRUE. x == TRUE
The problem is that instead of return() I had just a bare return without the following parentheses. This causes the if statement be roughly equivalent to if (x) constant, where the body is a bareword that performs no action. In this case, the bareword is the definition of the return function itself, and the function continues rather than returning. The correct version would look like this:
workingEarlyReturn = function(x=TRUE) {
if (x) return() # parentheses added to return
stop("Should not get here if x is TRUE. x == ", x)
}
It makes sense that R requires parentheses after return, but as a C programmer I'm likely to occasionally forget to add them. Usually there would be a parsing error if they are omitted, but in this case of a bare return in the body of an if statement there is not.
Assuming I want the ability to put a "guard" statement at the top of a function that will return without a value if some condition is not met, how I can avoid making this error in the future? Or at least, how can I make it easier to track down this error when I do make it? Is there some "expression has no effect" warning that I can turn on?

What is the proper idiomatic way of checking if a map has no elements in coffeescript?

since a code example is worth a thousand words:
console.log(#searchEnginesMap, {}, #searchEnginesMap == {}, #searchEnginesMap is {}, #searchEnginesMap.empty?, #searchEnginesMap.length)
returns:
{} {} false false false undefined
what's the correct syntax to get a true value for this? (or how should I correctly check if I have a map with zero elements?)
EDIT: extra credit:
how do you compare these two dictionaries to have them be the same (by value, not be reference):
a = {"foo":"bar?q=%s","baz":"qux?q=%s"}
b = {"foo":"bar?q=%s","baz":"qux?q=%s"}
so I need to know what I can use to get get true while comparing these?
Thanks in advance.
There is no CoffeeScript magic solution here. If you want to know if an Object is empty then you have to count the keys. You could use Object.keys:
if Object.keys(obj).length == 0
# obj is empty
Or you could use a loop:
if (true for v of obj).length == 0
# obj is empty
The for ... of loop version could be wrapped in a short-circuiting function without much effort.
I would probably wimp out and grab Underscore or Lodash so that I could use _.isEmpty:
if _(obj).isEmpty()
# obj is empty
That would also solve your second problem because you'd get _.isEqual too:
_(foo: "bar?q=%s", baz: "qux?q=%s").isEqual(baz: "qux?q=%s", foo: "bar?q=%s")
# true
Underscore demo: http://jsfiddle.net/ambiguous/Jad6e/

Groovy NullObject should be null or not?

This example can be easily tested in the groovy console.
var a is evaluated to not null while b is evaluated to null.
Both are instances of org.codehaus.groovy.runtim.NullObject
def b = null
println b.getClass()
println b == null
def a = null.getClass().newInstance()
println a.getClass()
println a == null
Does anyone knows why?
This is a tricky thing when dealing with reflection code.
Actually I am wondering if this is not a bug. As an explanation... NullObject is a runtime/intermediate kind of Object. If you do anything on null, then NullObject is used. This, and the the implementation of NullObject#equals speaks for a==null returning true. It returns fails, because there is some internal code before that, that is for example determining if compareTo is called instead of equals and such things. Now this piece of code starts with
if (left == right) return true;
if (left == null || right == null) return false;
so null==null will return true, but NullObject==null will return false. On the other hand NullObject should not leak out if possible. Maybe we should fix newInstance() to return null.
I filled http://jira.codehaus.org/browse/GROOVY-5769 for this
In the equals method of NullObject, it only returns true if you are comparing it to null
As an instance of NullObject is not strictly null, it returns false...
Whether NullObject should return true if you call equals against another NullObject is probably a question best asked on the mailing list... I'll have a look and see if I can find any previous question.

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