I am learning Grammatical Evolution, but one thing that I can't seem to grasp is how to use the strings that are evolved from grammar into solving an actual problem. Is it converted into a neural network or converted into an equation, or something else? How does it receive inputs and print out outputs?
Grammatical Evolution (GE) makes distinction between genotype and phenotype (genotype–phenotype distinction), which means an evolved genotype is not a solution by itself, but it maps to a solution.
Mutations and crossover are performed over genotypes, but to evaluate the fitness a genotype should be first transformed into a phenotype. In Grammatical Evolution this means generation of a string conforming to the chosen grammar. This solution string then should be executed, and the result of the execution evaluated to estimate the fitness of the solution.
How to actually execute the generated solution?
It highly depends on the implementation of a GE system.
If it generates solutions in some real programming language, they should be compiled and/or executed with the corresponding toolchain, ran with some test input, and the output evaluated to estimate the fitness.
If a GE system is able to execute a solution internally, no external toolchain is involved. It might be convenient to generate a syntax tree-like structure according to the grammar (instead of unstructured text), because it's quite easy to execute such a structure.
How to execute a syntax tree?
There exist an entire class of so called tree walk interpreters — not super performant, but reasonably simple in implementation. Usually such an interpreter first parses a source text and builds a syntax tree, then executes it; but in a GE system it is possible to directly generate a syntax tree, so no parsing is involved.
I can suggest "A tree-walk interpreter" chapter of a freely available book "Crafting interpreters" as a good example of constructing such an interpreter.
I'm porting over a grammar from flex/bison, and mostly seem to have everything up and running (in particular, my token stream seems fine, and my parser grammar is compiling and running), but seem to be running into problems of runaway stack/memory usage even with very small/moderate sized inputs to my grammar. What is the preferred construct for chaining together an unbounded sequence of the same nonterminal? In my Bison grammar I had production rules of the form:
statements: statement | statement statements
words: | word words
In ANTLR, if I maintain the same rule setup, this seems to perform admirably on small inputs (on the order of 4kB), but leads to stack overflow on larger inputs (on the order of 100kB). In both cases the automated parse tree produced is also rather ungainly.
I experimented with changing these production rules to have an explicitly additive (rather than recursive form):
statements: statement+
words: word*
However this seems to have lead to absolutely horrific blowup in memory usage (upwards of 1GB) on even very small inputs, and the parser has not yet managed to return a parse tree after 20 minutes of letting it run.
Any pointers would be appreciated.
Your rewritten statements are the optimal ANTLR 4 form of the two rules you described (highest performing and minimum memory usage). Here is some general feedback regarding the issues you describe.
I developed some very advanced diagnostic code for numerous potential performance problems. Much of this code is included in TestPerformance, but it is geared towards expert users and requires a rather deep understanding of ANTLR 4's new ALL(*) algorithm to interpret the results.
Terence and I are interested in turning the above into a tool that users can make use of. I may be able to help (run and interpret the test) if you provide a complete grammar and example inputs, so that I can use that grammar and input pair as part of evaluating the usability of a tool further down the road that automates the analysis.
Make sure you are using the two-stage parsing strategy from the book. In many cases, this will vastly improve the parsing performance for correct inputs (incorrect inputs would not be faster).
We don't like to use more memory than necessary, but you should be aware that we are working under a very different definition of "excessive" - e.g. we run our testing applications with -Xmx4g to -Xmx12g, depending on the test.
Okay, so I've gotten it working, in the following manner. My YACC grammar had the following constructions:
lines: lines | line lines;
words: | word words;
However, this did not make the recursive parsing happy, so I rewrote it as:
lines: line+;
words: word*;
Which is in line with #280Z28's feedback (and my original guess). This hung the parser, which is why I posted the question in the first place, but the debugging procedure outlined in my comments to #280Z28's answer showed that in fact it was only the lines parsing which was causing the problem (words) was fine. On a whim, I tried the following rewrite:
lines : stmt (EOL stmt)+ EOL*;
(where line had originally been defined as:
line : stmt (EOL | EOF);
)
This seems to be working quite well, even for large inputs. However it is entirely unclear to me WHY this is the Right Thing To Do(tm), or why it makes a difference compared to the revision which prompted this question. Any feedback on this matter would still be appreciated.
I'm working on a slot-machine mini-game application. The rules for what constitutes a winning prize are rather complex (n of a kind, n of any kind, specific sequences), and to make matters even more complicated, this code should work for a slot-machine with (n >= 3) reels.
So, after some thought, I believe defining a context-free language is the most efficient and extensible way to go. This way I could define the grammar in an XML file.
So my question is, given a string of symbols S, how do I go about testing if S is in a given Context-Free Language? Would I simply exhaust rules until I'm out of valid rules/symbols, or is there a known algorithm that could help. Thanks.
Also, a language like this seems non-regular, am I correct? I've never been good at proofs, so I've avoided trying.
Any comments on my approach would be appreciated as well.
Thanks.
"...given a string of symbols S, how do I go about testing if S is in
a given Context-Free Language?"
If a string w is in L(G); the process of finding a sequence of production rules of G by which w is derived is call parsing. So, you have to create a parse tree to search for some derivation. To do this you perform an exhaustive Breadth-First-Search. There is a serious issue that arises: The searching process may never terminate. To prevent endless searches you have to transform the grammer into what is known as normal form.
"Also, a language like this seems non-regular, am I correct?"
Not necessarily. Every regular language is context-free (because it can be described by a CTG), but not every context-free language is regular.
General cases of context free grammers are hard to evaluate.
However, there are methods to parse grammers in subsets of the context free grammers.
For example: SLR and LL grammers are often used by compilers to parse programming languages, which are also context free languages. To use these, your grammer must be in one of these "families" (remember - there are infinite number of grammers for each context free language).
Some practical tools you might want to use that are generally used for compilers are JavaCC in java and bison in C++.
(If I remember correctly, Bison is SLR parser and JavaCC is LL Parser, but I could be wrong)
P.S.
For a specific slot machine, with n slots and k symbols - the language is definetly regular, since there are at most kn "words" in it, and every finite language is regular. Things obviously get compilcated if you are looking for a grammer for all slot machines.
Your best bet is to actually code this with a proper programming language. A CFG is overkill, because it can be extremely hard to code some, as you say, "rather complex" rules. For example, grammars are poorly suited to talking about the number of things.
For example, how would you code "the number of cherries is > the number of any other object" in such a language? How would the person you're giving the program to do so? CFGs cannot easily express such concepts, and regular expressions cannot sanely do so by any stretch.
The answer is that grammars are not right for this task, unless the slot machines is trying to make English sentences.
You also have to consider what happens when TWO or more "prize sequences" match! Assuming you want to give out the highest prize, you need an ordered list of recognizers. This is not to say you can't code your recognizers with (for example) regular expressions in addition to arbitrary functions. I'm just saying that general CFG parsing is overkill, because what CFGs get you over regular languages (i.e. regular expressions) is the ability to consider parse trees of arbitrary depth (like nested parentheses of level N or more), which is probably not what you care about.
This is not to say that you don't, for example, want to allow regular expressions. You can make that job easy by using a parser generator to recognize regexes involving cherries bananas and pears, see http://en.wikipedia.org/wiki/Comparison_of_parser_generators, which you can then embed, though you might want to simply roll your own recursive descent parser (assuming again you don't care about CFGs, especially if your tokens are bounded length).
For example, here is how I might implement it in pseudocode (ideally you'd use a statically typechecked language with good list manipulation, which I can't think of off the top of my head):
rules = []
function Rule(name, code) {
this.name = name
this.code = code
rules.push(this) # adds them in order
}
##########################
Rule("All the same", regex(.*))
Rule("No two-in-a-row", function(list, counts) {
not regex(.{2}).match(list)
})
Rule("More cherries than anything else", function(list, counts) {
counts[cherries]>counts[x] for all x in counts
or
sorted(counts.items())[0]==cherries
or
counts.greatest()==cherries
})
for token in [cherry, banana, ...]:
Rule("At least 50% "+token, function(list, counts){
counts[token] >= list.length/2
})
Like lots of you guys on SO, I often write in several languages. And when it comes to planning stuff, (or even answering some SO questions), I actually think and write in some unspecified hybrid language. Although I used to be taught to do this using flow diagrams or UML-like diagrams, in retrospect, I find "my" pseudocode language has components of C, Python, Java, bash, Matlab, perl, Basic. I seem to unconsciously select the idiom best suited to expressing the concept/algorithm.
Common idioms might include Java-like braces for scope, pythonic list comprehensions or indentation, C++like inheritance, C#-style lambdas, matlab-like slices and matrix operations.
I noticed that it's actually quite easy for people to recognise exactly what I'm triying to do, and quite easy for people to intelligently translate into other languages. Of course, that step involves considering the corner cases, and the moments where each language behaves idiosyncratically.
But in reality, most of these languages share a subset of keywords and library functions which generally behave identically - maths functions, type names, while/for/if etc. Clearly I'd have to exclude many 'odd' languages like lisp, APL derivatives, but...
So my questions are,
Does code already exist that recognises the programming language of a text file? (Surely this must be a less complicated task than eclipse's syntax trees or than google translate's language guessing feature, right?) In fact, does the SO syntax highlighter do anything like this?
Is it theoretically possible to create a single interpreter or compiler that recognises what language idiom you're using at any moment and (maybe "intelligently") executes or translates to a runnable form. And flags the corner cases where my syntax is ambiguous with regards to behaviour. Immediate difficulties I see include: knowing when to switch between indentation-dependent and brace-dependent modes, recognising funny operators (like *pointer vs *kwargs) and knowing when to use list vs array-like representations.
Is there any language or interpreter in existence, that can manage this kind of flexible interpreting?
Have I missed an obvious obstacle to this being possible?
edit
Thanks all for your answers and ideas. I am planning to write a constraint-based heuristic translator that could, potentially, "solve" code for the intended meaning and translate into real python code. It will notice keywords from many common languages, and will use syntactic clues to disambiguate the human's intentions - like spacing, brackets, optional helper words like let or then, context of how variables are previously used etc, plus knowledge of common conventions (like capital names, i for iteration, and some simplistic limited understanding of naming of variables/methods e.g containing the word get, asynchronous, count, last, previous, my etc). In real pseudocode, variable naming is as informative as the operations themselves!
Using these clues it will create assumptions as to the implementation of each operation (like 0/1 based indexing, when should exceptions be caught or ignored, what variables ought to be const/global/local, where to start and end execution, and what bits should be in separate threads, notice when numerical units match / need converting). Each assumption will have a given certainty - and the program will list the assumptions on each statement, as it coaxes what you write into something executable!
For each assumption, you can 'clarify' your code if you don't like the initial interpretation. The libraries issue is very interesting. My translator, like some IDE's, will read all definitions available from all modules, use some statistics about which classes/methods are used most frequently and in what contexts, and just guess! (adding a note to the program to say why it guessed as such...) I guess it should attempt to execute everything, and warn you about what it doesn't like. It should allow anything, but let you know what the several alternative interpretations are, if you're being ambiguous.
It will certainly be some time before it can manage such unusual examples like #Albin Sunnanbo's ImportantCustomer example. But I'll let you know how I get on!
I think that is quite useless for everything but toy examples and strict mathematical algorithms. For everything else the language is not just the language. There are lots of standard libraries and whole environments around the languages. I think I write almost as many lines of library calls as I write "actual code".
In C# you have .NET Framework, in C++ you have STL, in Java you have some Java libraries, etc.
The difference between those libraries are too big to be just syntactic nuances.
<subjective>
There has been attempts at unifying language constructs of different languages to a "unified syntax". That was called 4GL language and never really took of.
</subjective>
As a side note I have seen a code example about a page long that was valid as c#, Java and Java script code. That can serve as an example of where it is impossible to determine the actual language used.
Edit:
Besides, the whole purpose of pseudocode is that it does not need to compile in any way. The reason you write pseudocode is to create a "sketch", however sloppy you like.
foreach c in ImportantCustomers{== OrderValue >=$1M}
SendMailInviteToSpecialEvent(c)
Now tell me what language it is and write an interpreter for that.
To detect what programming language is used: Detecting programming language from a snippet
I think it should be possible. The approach in 1. could be leveraged to do this, I think. I would try to do it iteratively: detect the syntax used in the first line/clause of code, "compile" it to intermediate form based on that detection, along with any important syntax (e.g. begin/end wrappers). Then the next line/clause etc. Basically write a parser that attempts to recognize each "chunk". Ambiguity could be flagged by the same algorithm.
I doubt that this has been done ... seems like the cognitive load of learning to write e.g. python-compatible pseudocode would be much easier than trying to debug the cases where your interpreter fails.
a. I think the biggest problem is that most pseudocode is invalid in any language. For example, I might completely skip object initialization in a block of pseudocode because for a human reader it is almost always straightforward to infer. But for your case it might be completely invalid in the language syntax of choice, and it might be impossible to automatically determine e.g. the class of the object (it might not even exist). Etc.
b. I think the best you can hope for is an interpreter that "works" (subject to 4a) for your pseudocode only, no-one else's.
Note that I don't think that 4a,4b are necessarily obstacles to it being possible. I just think it won't be useful for any practical purpose.
Recognizing what language a program is in is really not that big a deal. Recognizing the language of a snippet is more difficult, and recognizing snippets that aren't clearly delimited (what do you do if four lines are Python and the next one is C or Java?) is going to be really difficult.
Assuming you got the lines assigned to the right language, doing any sort of compilation would require specialized compilers for all languages that would cooperate. This is a tremendous job in itself.
Moreover, when you write pseudo-code you aren't worrying about the syntax. (If you are, you're doing it wrong.) You'll wind up with code that simply can't be compiled because it's incomplete or even contradictory.
And, assuming you overcame all these obstacles, how certain would you be that the pseudo-code was being interpreted the way you were thinking?
What you would have would be a new computer language, that you would have to write correct programs in. It would be a sprawling and ambiguous language, very difficult to work with properly. It would require great care in its use. It would be almost exactly what you don't want in pseudo-code. The value of pseudo-code is that you can quickly sketch out your algorithms, without worrying about the details. That would be completely lost.
If you want an easy-to-write language, learn one. Python is a good choice. Use pseudo-code for sketching out how processing is supposed to occur, not as a compilable language.
An interesting approach would be a "type-as-you-go" pseudocode interpreter. That is, you would set the language to be used up front, and then it would attempt to convert the pseudo code to real code, in real time, as you typed. An interactive facility could be used to clarify ambiguous stuff and allow corrections. Part of the mechanism could be a library of code which the converter tried to match. Over time, it could learn and adapt its translation based on the habits of a particular user.
People who program all the time will probably prefer to just use the language in most cases. However, I could see the above being a great boon to learners, "non-programmer programmers" such as scientists, and for use in brainstorming sessions with programmers of various languages and skill levels.
-Neil
Programs interpreting human input need to be given the option of saying "I don't know." The language PL/I is a famous example of a system designed to find a reasonable interpretation of anything resembling a computer program that could cause havoc when it guessed wrong: see http://horningtales.blogspot.com/2006/10/my-first-pli-program.html
Note that in the later language C++, when it resolves possible ambiguities it limits the scope of the type coercions it tries, and that it will flag an error if there is not a unique best interpretation.
I have a feeling that the answer to 2. is NO. All I need to prove it false is a code snippet that can be interpreted in more than one way by a competent programmer.
Does code already exist that
recognises the programming language
of a text file?
Yes, the Unix file command.
(Surely this must be a less
complicated task than eclipse's syntax
trees or than google translate's
language guessing feature, right?) In
fact, does the SO syntax highlighter
do anything like this?
As far as I can tell, SO has a one-size-fits-all syntax highlighter that tries to combine the keywords and comment syntax of every major language. Sometimes it gets it wrong:
def median(seq):
"""Returns the median of a list."""
seq_sorted = sorted(seq)
if len(seq) & 1:
# For an odd-length list, return the middle item
return seq_sorted[len(seq) // 2]
else:
# For an even-length list, return the mean of the 2 middle items
return (seq_sorted[len(seq) // 2 - 1] + seq_sorted[len(seq) // 2]) / 2
Note that SO's highlighter assumes that // starts a C++-style comment, but in Python it's the integer division operator.
This is going to be a major problem if you try to combine multiple languages into one. What do you do if the same token has different meanings in different languages? Similar situations are:
Is ^ exponentiation like in BASIC, or bitwise XOR like in C?
Is || logical OR like in C, or string concatenation like in SQL?
What is 1 + "2"? Is the number converted to a string (giving "12"), or is the string converted to a number (giving 3)?
Is there any language or interpreter
in existence, that can manage this
kind of flexible interpreting?
On another forum, I heard a story of a compiler (IIRC, for FORTRAN) that would compile any program regardless of syntax errors. If you had the line
= Y + Z
The compiler would recognize that a variable was missing and automatically convert the statement to X = Y + Z, regardless of whether you had an X in your program or not.
This programmer had a convention of starting comment blocks with a line of hyphens, like this:
C ----------------------------------------
But one day, they forgot the leading C, and the compiler choked trying to add dozens of variables between what it thought was subtraction operators.
"Flexible parsing" is not always a good thing.
To create a "pseudocode interpreter," it might be necessary to design a programming language that allows user-defined extensions to its syntax. There already are several programming languages with this feature, such as Coq, Seed7, Agda, and Lever. A particularly interesting example is the Inform programming language, since its syntax is essentially "structured English."
The Coq programming language allows "syntax extensions", so the language can be extended to parse new operators:
Notation "A /\ B" := (and A B).
Similarly, the Seed7 programming language can be extended to parse "pseudocode" using "structured syntax definitions." The while loop in Seed7 is defined in this way:
syntax expr: .while.().do.().end.while is -> 25;
Alternatively, it might be possible to "train" a statistical machine translation system to translate pseudocode into a real programming language, though this would require a large corpus of parallel texts.
I am reading a file that is filled
with hex numbers. I have to identify a
particular pattern, say "aaad" (without quotes) from
it. Every time I see the pattern, I
generate some data to some other file.
This would be a very common case in designing programs - parsing and looking for a particular pattern.
I have designed it as a Finite State Machine and structured structured it in C using switch-case to change states. This was the first implementation that occured to me.
DESIGN: Are there some better designs possible?
IMPLEMENTATION: Do you see some problems with using a switch case as I mentioned?
A hand-rolled FSM can work well for simple situations, but they tend to get unwieldy as the number of states and inputs grows.
There is probably no reason to change what you have already designed/implemented, but if you are interested in general-purpose text parsing techniques, you should probably look at things like regular expressions, Flex, Bison, and ANTLR.
For embarrassingly simple cases couple of if's or switch'es are sufficient.
For parsing a string on POSIX systems, man regex (3). For fully featured parsing of whole files (e.g. complex configs) use Lex/Flex and Yacc/Bison.
When writing in C++, look at Boost Regex for the simpler case and Boost Spirit for more complex one. Flex & Bison work with C++ too.