I have been working through the Advent of Code problems in Perl6 this year and was attempting to use a grammar to parse the Day 3's input.
Given input in this form: #1 # 1,3: 4x4 and this grammar that I created:
grammar Claim {
token TOP {
'#' <id> \s* '#' \s* <coordinates> ':' \s* <dimensions>
}
token digits {
<digit>+
}
token id {
<digits>
}
token coordinates {
<digits> ',' <digits>
}
token dimensions {
<digits> 'x' <digits>
}
}
say Claim.parse('#1 # 1,3: 4x4');
I am interested in extracting the actual tokens that were matched i.e. id, x + y from coordinates, and height + width from the dimensions from the resulting parse. I understand that I can pull them from the resulting Match object of Claim.parse(<input>), but I have to dig down through each grammar production to get the value I need e.g.
say $match<id>.hash<digits>.<digit>;
this seems a little messy, is there a better way?
For the particular challenge you're solving, using a grammar is like using a sledgehammer to crack a nut.
Like #Scimon says, a single regex would be fine. You can keep it nicely readable by laying it out appropriately. You can name the captures and keep them all at the top level:
/ ^
'#' $<id>=(\d+) ' '
'# ' $<x>=(\d+) ',' $<y>=(\d+)
': ' $<w>=(\d+) x $<d>=(\d+)
$
/;
say ~$<id x y w d>; # 1 1 3 4 4
(The prefix ~ calls .Str on the value on its right hand side. Called on a Match object it stringifies to the matched strings.)
With that out the way, your question remains perfectly cromulent as it is because it's important to know how P6 scales in this regard from simple regexes like the one above to the largest and most complex parsing tasks. So that's what the rest of this answer covers, using your example as the starting point.
Digging less messily
say $match<id>.hash<digits>.<digit>; # [｢1｣]
this seems a little messy, is there a better way?
Your say includes unnecessary code and output nesting. You could just simplify to something like:
say ~$match<id> # 1
Digging a little deeper less messily
I am interested in extracting the actual tokens that were matched i.e. id, x + y from coordinates, and height + width from the dimensions from the resulting parse.
For matches of multiple tokens you no longer have the luxury of relying on Perl 6 guessing which one you mean. (When there's only one, guess which one it guesses you mean. :))
One way to write your say to get the y coordinate:
say ~$match<coordinates><digits>[1] # 3
If you want to drop the <digits> you can mark which parts of a pattern should be stored in a list of numbered captures. One way to do so is to put parentheses around those parts:
token coordinates { (<digits>) ',' (<digits>) }
Now you've eliminated the need to mention <digits>:
say ~$match<coordinates>[1] # 3
You could also name the new parenthesized captures:
token coordinates { $<x>=(<digits>) ',' $<y>=(<digits>) }
say ~$match<coordinates><y> # 3
Pre-digging
I have to dig down through each grammar production to get the value I need
The above techniques still all dig down into the automatically generated parse tree which by default precisely corresponds to the tree implicit in the grammar's hierarchy of rule calls. The above techniques just make the way you dig into it seem a little shallower.
Another step is to do the digging work as part of the parsing process so that the say is simple.
You could inline some code right into the TOP token to store just the interesting data you've made. Just insert a {...} block in the appropriate spot (for this sort of thing that means the end of the token given that you need the token pattern to have already done its matching work):
my $made;
grammar Claim {
token TOP {
'#' <id> \s* '#' \s* <coordinates> ':' \s* <dimensions>
{ $made = ~($<id>, $<coordinatess><x y>, $<dimensions><digits>[0,1]) }
}
...
Now you can write just:
say $made # 1 1 3 4 4
This illustrates that you can just write arbitrary code at any point in any rule -- something that's not possible with most parsing formalisms and their related tools -- and the code can access the parse state as it is at that point.
Pre-digging less messily
Inlining code is quick and dirty. So is using a variable.
The normal thing to do for storing data is to instead use the make function. This hangs data off the match object that's being constructed corresponding to a given rule. This can then be retrieved using the .made method. So instead of $make = you'd have:
{ make ~($<id>, $<coordinatess><x y>, $<dimensions><digits>[0,1]) }
And now you can write:
say $match.made # 1 1 3 4 4
That's much tidier. But there's more.
A sparse subtree of a parse tree
.oO ( 🎶 On the first day of an imagined 2019 Perl 6 Christmas Advent calendar 🎶 a StackOverflow title said to me ... )
In the above example I constructed a .made payload for just the TOP node. For larger grammars it's common to form a sparse subtree (a term I coined for this because I couldn't find a standard existing term).
This sparse subtree consists of the .made payload for the TOP that's a data structure referring to .made payloads of lower level rules which in turn refer to lower level rules and so on, skipping uninteresting intermediate rules.
The canonical use case for this is to form an Abstract Syntax Tree after parsing some programming code.
In fact there's an alias for .made, namely .ast:
say $match.ast # 1 1 3 4 4
While this is trivial to use, it's also fully general. P6 uses a P6 grammar to parse P6 code -- and then builds an AST using this mechanism.
Making it all elegant
For maintainability and reusability you can and typically should not insert code inline at the end of rules but should instead use Action objects.
In summary
There are a range of general mechanisms that scale from simple to complex scenarios and can be combined as best fits any given use case.
Add parentheses as I explained above, naming the capture that those parentheses zero in on, if that is a nice simplification for digging into the parse tree.
Inline any action you wish to take during parsing of a rule. You get full access to the parse state at that point. This is great for making it easy to extract just the data you want from a parse because you can use the make convenience function. And you can abstract all actions that are to be taken at the end of successfully matching rules out of a grammar, ensuring this is a clean solution code-wise and that a single grammar remains reusable for multiple actions.
One final thing. You may wish to prune the parse tree to omit unnecessary leaf detail (to reduce memory consumption and/or simplify parse tree displays). To do so, write <.foo>, with a dot preceding the rule name, to switch the default automatic capturing off for that rule.
You can refer to each of you named portions directly. So to get the cordinates you can access :
say $match.<coordinates>.<digits>
this will return you the Array of digits matches. Ig you just want the values the easiest way is probably :
say $match.<coordinates>.<digits>.map( *.Int) or say $match.<coordinates>.<digits>>>.Int or even say $match.<coordinates>.<digits>».Int
to cast them to Ints
For the id field it's even easier you can just cast the <id> match to an Int :
say $match.<id>.Int
I have a file with 13 columns and 41 lines consisting of the coefficients for the Joback Method for 41 different groups. Some of the values are non-existing, though, and the table lists them as "X". I saved the table as a .csv and in my code read the file to an array. An excerpt of two lines from the .csv (the second one contains non-exisiting coefficients) looks like this:
48.84,11.74,0.0169,0.0074,9.0,123.34,163.16,453.0,1124.0,-31.1,0.227,-0.00032,0.000000146
X,74.6,0.0255,-0.0099,X,23.61,X,797.0,X,X,X,X,X
What I've tried doing was to read and define an array to hold each IOSTAT value so I can know if an "X" was read (that is, IOSTAT would be positive):
DO I = 1, 41
(READ(25,*,IOSTAT=ReadStatus(I,J)) JobackCoeff, J = 1, 13)
END DO
The problem, I've found, is that if the first value of the line to be read is "X", producing a positive value of ReadStatus, then the rest of the values of those line are not read correctly.
My intent was to use the ReadStatus array to produce an error message if JobackCoeff(I,J) caused a read error, therefore pinpointing the "X"s.
Can I force the program to keep reading a line after there is a reading error? Or is there a better way of doing this?
As soon as an error occurs during the input execution then processing of the input list terminates. Further, all variables specified in the input list become undefined. The short answer to your first question is: no, there is no way to keep reading a line after a reading error.
We come, then, to the usual answer when more complicated input processing is required: read the line into a character variable and process that. I won't write complete code for you (mostly because it isn't clear exactly what is required), but when you have a character variable you may find the index intrinsic useful. With this you can locate Xs (with repeated calls on substrings to find all of them on a line).
Alternatively, if you provide an explicit format (rather than relying on list-directed (fmt=*) input) you may be able to do something with non-advancing input (advance='no' in the read statement). However, as soon as an error condition comes about then the position of the file becomes indeterminate: you'll also have to handle this. It's probably much simpler to process the line-as-a-character-variable.
An outline of the concept (without declarations, robustness) is given below.
read(iunit, '(A)') line
idx = 1
do i=1, 13
read(line(idx:), *, iostat=iostat) x(i)
if (iostat.gt.0) then
print '("Column ",I0," has an X")', i
x(i) = -HUGE(0.) ! Recall x(i) was left undefined
end if
idx = idx + INDEX(line(idx:), ',')
end do
An alternative, long used by many many Fortran programmers, and programmers in other languages, would be to use an editor of some sort (I like sed) and modify the file by changing all the Xs to NANs. Your compiler has to provide support for IEEE NaNs for this to work (most of the current crop in widespread use do) and they will correctly interpret NAN in the input file to a real number with value NaN.
This approach has the benefit, compared with the already accepted (and perfectly good) answer, of not requiring clever programming in Fortran to parse input lines containing mixed entries. Use an editor for string processing, use Fortran for reading numbers.
On the one hand we have:
>> source object
object: make function! [[
"Defines a unique object."
blk [block!] "Object words and values."
][
make object! append blk none
]]
For context we see:
>> source context
context: make function! [[
"Defines a unique object."
blk [block!] "Object words and values."
][
make object! blk
]]
So, for object the object is constructed from a block to which none has been appended. This doesn't change the length, or, to my knowledge, add anything. With context, on the other hand, the object is constructed with the passed-in block, as is.
Why the difference and why, for example, couldn't context just be an alias for object.
Backwards compatibility. We had a context function already in Rebol that worked a particular way (not initializing variables), but we needed a function that initialized variables to none, as a convenience function when creating objects as data structures rather than as code containers.
It made sense to call it object since that is the type name, and since "context" is actually kind of a bad name for objects in a language with context-sensitive semantics (for a more appropriate meaning of the word "context"). It really leads to some confusing conversations. Since R3 has modules now, most of the previous uses of the context function are covered better by modules. Keeping context at all is mostly for backwards compatibility.
The current object function is pretty much a placeholder for a better type construction wrapper that we haven't thought up yet. We need something like it, but there may be subtle changes in its behavior needed that we'll discover with more use. For one thing, the fact that it modifies its spec block makes it not very safe for recursion or concurrency. It will likely end up as a native if that improves it, or maybe as a construct option if that turns out to be a better approach.
One thing that did turn out to be a win is the practice of using the type name without the exclamation point as the name of a type construction function. We changed map to be that as well, and we may end up adding similar constructors for other types, though most that need them have them already.
I asked a related question here: Clojure: How do I turn clojure code into a string that is evaluatable? It mostly works but lists are translated to raw parens, which fails
The answer was great but I realized that is not exactly what I needed. I simplified the example for stackoverflow, but I am not just writing out datum, I am trying to write out function definitions and other things which contain structures that contain lists. So here is a simple example (co-opted from the last question).
I want to generate a file which contains the function:
(defn aaa []
(fff :update {:bbb "bbb" :xxx [1 2 3] :yyy (3 5 7)}))
Everything after the :update is a structure I have access to when writing the file, so I call str on it and it emerges in that state. This is fine, but the list, when I load-file on this generated function, tries to call 3 as a function (as it is the first element in the list).
So I want a file which contains my function definition that I can then call load-file and call the functions defined in it. How can I write out this function with associated data so that I can load it back in without clojure thinking what used to be lists are now function calls?
You need to quote the structure prior to obtaining the string representation:
(list 'quote foo)
where foo is the structure.
Three additional remarks:
traversing the code to quote all lists / seqs would not do at all, since the top-level (defn ...) form would also get quoted;
lists are not the only potentially problematic type -- symbols are another one (+ vs. #<core$_PLUS_ clojure.core$_PLUS_#451ef443>);
rather than using (str foo) (even with foo already quoted), you'll probably want to print out the quoted foo -- or rather the entire code block with the quoted foo inside -- using pr / prn.
The last point warrants a short discussion. pr explicitly promises to produce a readable representation if *print-readably* is true, whereas str only produces such a representation for Clojure's compound data structures "by accident" (of the implementation) and still only if *print-readably* is true:
(str ["asdf"])
; => "[\"asdf\"]"
(binding [*print-readably* false]
(str ["asdf"]))
; => "[asdf]"
The above behaviour is due to clojure.lang.RT/printString's (that's the method Clojure's data structures ultimately delegate their toString needs to) use of clojure.lang.RT/print, which in turn chooses output format depending on the value of *print-readably*.
Even with *print-readably* bound to true, str may produce output inappropriate for clojure.lang.Reader's consumption: e.g. (str "asdf") is just "asdf", while the readable representation is "\"asdf\"". Use (with-out-str (pr foo)) to obtain a string object containing the representation of foo, guaranteed readable if *print-readably* is true.
Try this instead...
(defn aaa []
(fff :update {:bbb "bbb" :xxx [1 2 3] :yyy (list 3 5 7)}))
Wrap it in a call to quote to read it without evaluating it.
What does "type-safe" mean?
Type safety means that the compiler will validate types while compiling, and throw an error if you try to assign the wrong type to a variable.
Some simple examples:
// Fails, Trying to put an integer in a string
String one = 1;
// Also fails.
int foo = "bar";
This also applies to method arguments, since you are passing explicit types to them:
int AddTwoNumbers(int a, int b)
{
return a + b;
}
If I tried to call that using:
int Sum = AddTwoNumbers(5, "5");
The compiler would throw an error, because I am passing a string ("5"), and it is expecting an integer.
In a loosely typed language, such as javascript, I can do the following:
function AddTwoNumbers(a, b)
{
return a + b;
}
if I call it like this:
Sum = AddTwoNumbers(5, "5");
Javascript automaticly converts the 5 to a string, and returns "55". This is due to javascript using the + sign for string concatenation. To make it type-aware, you would need to do something like:
function AddTwoNumbers(a, b)
{
return Number(a) + Number(b);
}
Or, possibly:
function AddOnlyTwoNumbers(a, b)
{
if (isNaN(a) || isNaN(b))
return false;
return Number(a) + Number(b);
}
if I call it like this:
Sum = AddTwoNumbers(5, " dogs");
Javascript automatically converts the 5 to a string, and appends them, to return "5 dogs".
Not all dynamic languages are as forgiving as javascript (In fact a dynamic language does not implicity imply a loose typed language (see Python)), some of them will actually give you a runtime error on invalid type casting.
While its convenient, it opens you up to a lot of errors that can be easily missed, and only identified by testing the running program. Personally, I prefer to have my compiler tell me if I made that mistake.
Now, back to C#...
C# supports a language feature called covariance, this basically means that you can substitute a base type for a child type and not cause an error, for example:
public class Foo : Bar
{
}
Here, I created a new class (Foo) that subclasses Bar. I can now create a method:
void DoSomething(Bar myBar)
And call it using either a Foo, or a Bar as an argument, both will work without causing an error. This works because C# knows that any child class of Bar will implement the interface of Bar.
However, you cannot do the inverse:
void DoSomething(Foo myFoo)
In this situation, I cannot pass Bar to this method, because the compiler does not know that Bar implements Foo's interface. This is because a child class can (and usually will) be much different than the parent class.
Of course, now I've gone way off the deep end and beyond the scope of the original question, but its all good stuff to know :)
Type-safety should not be confused with static / dynamic typing or strong / weak typing.
A type-safe language is one where the only operations that one can execute on data are the ones that are condoned by the data's type. That is, if your data is of type X and X doesn't support operation y, then the language will not allow you to to execute y(X).
This definition doesn't set rules on when this is checked. It can be at compile time (static typing) or at runtime (dynamic typing), typically through exceptions. It can be a bit of both: some statically typed languages allow you to cast data from one type to another, and the validity of casts must be checked at runtime (imagine that you're trying to cast an Object to a Consumer - the compiler has no way of knowing whether it's acceptable or not).
Type-safety does not necessarily mean strongly typed, either - some languages are notoriously weakly typed, but still arguably type safe. Take Javascript, for example: its type system is as weak as they come, but still strictly defined. It allows automatic casting of data (say, strings to ints), but within well defined rules. There is to my knowledge no case where a Javascript program will behave in an undefined fashion, and if you're clever enough (I'm not), you should be able to predict what will happen when reading Javascript code.
An example of a type-unsafe programming language is C: reading / writing an array value outside of the array's bounds has an undefined behaviour by specification. It's impossible to predict what will happen. C is a language that has a type system, but is not type safe.
Type safety is not just a compile time constraint, but a run time constraint. I feel even after all this time, we can add further clarity to this.
There are 2 main issues related to type safety. Memory** and data type (with its corresponding operations).
Memory**
A char typically requires 1 byte per character, or 8 bits (depends on language, Java and C# store unicode chars which require 16 bits).
An int requires 4 bytes, or 32 bits (usually).
Visually:
char: |-|-|-|-|-|-|-|-|
int : |-|-|-|-|-|-|-|-| |-|-|-|-|-|-|-|-| |-|-|-|-|-|-|-|-| |-|-|-|-|-|-|-|-|
A type safe language does not allow an int to be inserted into a char at run-time (this should throw some kind of class cast or out of memory exception). However, in a type unsafe language, you would overwrite existing data in 3 more adjacent bytes of memory.
int >> char:
|-|-|-|-|-|-|-|-| |?|?|?|?|?|?|?|?| |?|?|?|?|?|?|?|?| |?|?|?|?|?|?|?|?|
In the above case, the 3 bytes to the right are overwritten, so any pointers to that memory (say 3 consecutive chars) which expect to get a predictable char value will now have garbage. This causes undefined behavior in your program (or worse, possibly in other programs depending on how the OS allocates memory - very unlikely these days).
** While this first issue is not technically about data type, type safe languages address it inherently and it visually describes the issue to those unaware of how memory allocation "looks".
Data Type
The more subtle and direct type issue is where two data types use the same memory allocation. Take a int vs an unsigned int. Both are 32 bits. (Just as easily could be a char[4] and an int, but the more common issue is uint vs. int).
|-|-|-|-|-|-|-|-| |-|-|-|-|-|-|-|-| |-|-|-|-|-|-|-|-| |-|-|-|-|-|-|-|-|
|-|-|-|-|-|-|-|-| |-|-|-|-|-|-|-|-| |-|-|-|-|-|-|-|-| |-|-|-|-|-|-|-|-|
A type unsafe language allows the programmer to reference a properly allocated span of 32 bits, but when the value of a unsigned int is read into the space of an int (or vice versa), we again have undefined behavior. Imagine the problems this could cause in a banking program:
"Dude! I overdrafted $30 and now I have $65,506 left!!"
...'course, banking programs use much larger data types. ;) LOL!
As others have already pointed out, the next issue is computational operations on types. That has already been sufficiently covered.
Speed vs Safety
Most programmers today never need to worry about such things unless they are using something like C or C++. Both of these languages allow programmers to easily violate type safety at run time (direct memory referencing) despite the compilers' best efforts to minimize the risk. HOWEVER, this is not all bad.
One reason these languages are so computationally fast is they are not burdened by verifying type compatibility during run time operations like, for example, Java. They assume the developer is a good rational being who won't add a string and an int together and for that, the developer is rewarded with speed/efficiency.
Many answers here conflate type-safety with static-typing and dynamic-typing. A dynamically typed language (like smalltalk) can be type-safe as well.
A short answer: a language is considered type-safe if no operation leads to undefined behavior. Many consider the requirement of explicit type conversions necessary for a language to be strictly typed, as automatic conversions can sometimes leads to well defined but unexpected/unintuitive behaviors.
A programming language that is 'type-safe' means following things:
You can't read from uninitialized variables
You can't index arrays beyond their bounds
You can't perform unchecked type casts
An explanation from a liberal arts major, not a comp sci major:
When people say that a language or language feature is type safe, they mean that the language will help prevent you from, for example, passing something that isn't an integer to some logic that expects an integer.
For example, in C#, I define a function as:
void foo(int arg)
The compiler will then stop me from doing this:
// call foo
foo("hello world")
In other languages, the compiler would not stop me (or there is no compiler...), so the string would be passed to the logic and then probably something bad will happen.
Type safe languages try to catch more at "compile time".
On the down side, with type safe languages, when you have a string like "123" and you want to operate on it like an int, you have to write more code to convert the string to an int, or when you have an int like 123 and want to use it in a message like, "The answer is 123", you have to write more code to convert/cast it to a string.
To get a better understanding do watch the below video which demonstrates code in type safe language (C#) and NOT type safe language ( javascript).
http://www.youtube.com/watch?v=Rlw_njQhkxw
Now for the long text.
Type safety means preventing type errors. Type error occurs when data type of one type is assigned to other type UNKNOWINGLY and we get undesirable results.
For instance JavaScript is a NOT a type safe language. In the below code “num” is a numeric variable and “str” is string. Javascript allows me to do “num + str” , now GUESS will it do arithmetic or concatenation .
Now for the below code the results are “55” but the important point is the confusion created what kind of operation it will do.
This is happening because javascript is not a type safe language. Its allowing to set one type of data to the other type without restrictions.
<script>
var num = 5; // numeric
var str = "5"; // string
var z = num + str; // arthimetic or concat ????
alert(z); // displays “55”
</script>
C# is a type safe language. It does not allow one data type to be assigned to other data type. The below code does not allow “+” operator on different data types.
Concept:
To be very simple Type Safe like the meanings, it makes sure that type of the variable should be safe like
no wrong data type e.g. can't save or initialized a variable of string type with integer
Out of bound indexes are not accessible
Allow only the specific memory location
so it is all about the safety of the types of your storage in terms of variables.
Type-safe means that programmatically, the type of data for a variable, return value, or argument must fit within a certain criteria.
In practice, this means that 7 (an integer type) is different from "7" (a quoted character of string type).
PHP, Javascript and other dynamic scripting languages are usually weakly-typed, in that they will convert a (string) "7" to an (integer) 7 if you try to add "7" + 3, although sometimes you have to do this explicitly (and Javascript uses the "+" character for concatenation).
C/C++/Java will not understand that, or will concatenate the result into "73" instead. Type-safety prevents these types of bugs in code by making the type requirement explicit.
Type-safety is very useful. The solution to the above "7" + 3 would be to type cast (int) "7" + 3 (equals 10).
Try this explanation on...
TypeSafe means that variables are statically checked for appropriate assignment at compile time. For example, consder a string or an integer. These two different data types cannot be cross-assigned (ie, you can't assign an integer to a string nor can you assign a string to an integer).
For non-typesafe behavior, consider this:
object x = 89;
int y;
if you attempt to do this:
y = x;
the compiler throws an error that says it can't convert a System.Object to an Integer. You need to do that explicitly. One way would be:
y = Convert.ToInt32( x );
The assignment above is not typesafe. A typesafe assignement is where the types can directly be assigned to each other.
Non typesafe collections abound in ASP.NET (eg, the application, session, and viewstate collections). The good news about these collections is that (minimizing multiple server state management considerations) you can put pretty much any data type in any of the three collections. The bad news: because these collections aren't typesafe, you'll need to cast the values appropriately when you fetch them back out.
For example:
Session[ "x" ] = 34;
works fine. But to assign the integer value back, you'll need to:
int i = Convert.ToInt32( Session[ "x" ] );
Read about generics for ways that facility helps you easily implement typesafe collections.
C# is a typesafe language but watch for articles about C# 4.0; interesting dynamic possibilities loom (is it a good thing that C# is essentially getting Option Strict: Off... we'll see).
Type-Safe is code that accesses only the memory locations it is authorized to access, and only in well-defined, allowable ways.
Type-safe code cannot perform an operation on an object that is invalid for that object. The C# and VB.NET language compilers always produce type-safe code, which is verified to be type-safe during JIT compilation.
Type-safe means that the set of values that may be assigned to a program variable must fit well-defined and testable criteria. Type-safe variables lead to more robust programs because the algorithms that manipulate the variables can trust that the variable will only take one of a well-defined set of values. Keeping this trust ensures the integrity and quality of the data and the program.
For many variables, the set of values that may be assigned to a variable is defined at the time the program is written. For example, a variable called "colour" may be allowed to take on the values "red", "green", or "blue" and never any other values. For other variables those criteria may change at run-time. For example, a variable called "colour" may only be allowed to take on values in the "name" column of a "Colours" table in a relational database, where "red, "green", and "blue", are three values for "name" in the "Colours" table, but some other part of the computer program may be able to add to that list while the program is running, and the variable can take on the new values after they are added to the Colours table.
Many type-safe languages give the illusion of "type-safety" by insisting on strictly defining types for variables and only allowing a variable to be assigned values of the same "type". There are a couple of problems with this approach. For example, a program may have a variable "yearOfBirth" which is the year a person was born, and it is tempting to type-cast it as a short integer. However, it is not a short integer. This year, it is a number that is less than 2009 and greater than -10000. However, this set grows by 1 every year as the program runs. Making this a "short int" is not adequate. What is needed to make this variable type-safe is a run-time validation function that ensures that the number is always greater than -10000 and less than the next calendar year. There is no compiler that can enforce such criteria because these criteria are always unique characteristics of the problem domain.
Languages that use dynamic typing (or duck-typing, or manifest typing) such as Perl, Python, Ruby, SQLite, and Lua don't have the notion of typed variables. This forces the programmer to write a run-time validation routine for every variable to ensure that it is correct, or endure the consequences of unexplained run-time exceptions. In my experience, programmers in statically typed languages such as C, C++, Java, and C# are often lulled into thinking that statically defined types is all they need to do to get the benefits of type-safety. This is simply not true for many useful computer programs, and it is hard to predict if it is true for any particular computer program.
The long & the short.... Do you want type-safety? If so, then write run-time functions to ensure that when a variable is assigned a value, it conforms to well-defined criteria. The down-side is that it makes domain analysis really difficult for most computer programs because you have to explicitly define the criteria for each program variable.
Type Safety
In modern C++, type safety is very important. Type safety means that you use the types correctly and, therefore, avoid unsafe casts and unions. Every object in C++ is used according to its type and an object needs to be initialized before its use.
Safe Initialization: {}
The compiler protects from information loss during type conversion. For example,
int a{7}; The initialization is OK
int b{7.5} Compiler shows ERROR because of information loss.\
Unsafe Initialization: = or ()
The compiler doesn't protect from information loss during type conversion.
int a = 7 The initialization is OK
int a = 7.5 The initialization is OK, but information loss occurs. The actual value of a will become 7.0
int c(7) The initialization is OK
int c(7.5) The initialization is OK, but information loss occurs. The actual value of a will become 7.0