Are there any tools which diff hierarchies?
IE, consider the following hierarchy:
A has child B.
B has child C.
which is compared to:
A has child B.
A has child C.
I would like a tool that shows that C has moved from a child of B to a child of A. Do any such utilities exist? If there are no specific tools, I'm not opposed to writing my own, so what are some good algorithms which are applicable to this problem?
A great general resource for diffing hierarchies (not specifically XML, HTML, etc) is the Hierarchical-Diff github project based on a bit of Dartmouth research. They have a pretty extensive list of related work ranging from XML diffing, to configuration file diffing to HTML diffing.
In general, actually performing diffs/patches on tree structures is a fairly well-solved problem, but displaying those diffs in a manner that makes sense to humans is still the wild west. That's double true when your data structure already has some semantic meaning like with HTML.
You might consider our SmartDifferencer tools.
These tools compare computer source code files in a diff-like way. Unlike diff, which is line oriented, these tools see changes according to code structure (variable name, expression, statement, block, function, class, etc.) as plausible edits ("move, insert, delete, replace, copy, rename"), producing answers that makes sense to programmers.
These computer source codes have exactly the "hierarchy" structure you are suggesting; the various constructs nest. Specifically to your topic, typically code blocks can nest inside code blocks. The SmartDifferencer tools use target-language accurate parsers to "deconstruct" the source text into these hierarchical entities. We have a Smart Differencer for XML in which you can obviously write nested tags.
The answer isn't reported as "Nth child of M has moved" although it is actually computed that way, by operating on the parse trees produced by the parsers. Rather it is reported as "code fragment of type at line x col y to line a col b has moved/..."
The answer my good sir is: Depth-first search, also known as Depth-first traversal. You might find some use of the Visitor pattern.
You can't swing a dead cat without hitting some sort of implementation for this when dealing with comparing XML trees. Take a gander at diffxml for an example.
Related
In The Pragmatic Programmer:
Normally, you can simply hide a third-party product behind a
well-defined, abstract interface. In fact , we've always been able to
do so on any project we've worked on. But suppose you couldn't isolate
it that cleanly. What if you had to sprinkle certain statements
liberally throughout the code? Put that requirement in metadata, and
use some automatic mechanism, such as Aspects (see page 39 ) or Perl,
to insert the necessary statements into the code itself.
Here the author is referring to Aspect Oriented Programming and Perl as tools that support "automatic mechanisms" for inserting metadata.
In my mind I envision some type of run-time injection of code. How does Perl allow for "automatic mechanisms" for inserting metadata?
Skip ahead to the section on Code Generators. The author provides a number of examples of processing input files to generate code, including this one:
Another example of melding environments using code generators happens when different programming languages are used in the same application. In order to communicate, each code base will need some information in commondata structures, message formats, and field names, for example. Rather than duplicate this information, use a code generator. Sometimes you can parse the information out of the source files of one language and use it to generate code in a second language. Often, though, it is simpler to express it in a simpler, language-neutral representation and generate the code for both languages, as shown in Figure 3.4 on the following page. Also see the answer to Exercise 13 on page 286 for an example of how to separate the parsing of the flat file representation from code generation.
The answer to Exercise 13 is a set of Perl programs used to generate C and Pascal data structures from a common input file.
What was the original reason for MATLAB's one (primary) function = one file, and why is it still so, after so many years of development?
What are the advantages of this approach, compared to its disadvantages (people put too many things in functions and scripts, when they should obviously be separated ... resulting in loss of code clarity)?
Matlab's schema of loading one class/function per file seems to match Java's choice in this matter. I am betting that there were other technical reasons for speeding up the parser in when it was introduced the 1980's. This schema was chosen by Java to discourage extremely large files with everything stuffed inside, which has been the primary argument for any language I've seen using one-file class symantics.
However, forcing one class per file semantics doesn't stop mega files -- KPIB is a perfect example of a complicated, horrifically long function/class file (though a quite useful maga file). So the one class file system is a way of trying to make the user aware about code abstraction more than a functionally useful mechanism.
A positive result of the one function/class file system of Matlab is that it's very easy to know what functions are available at a quick glance of a project directory. Additionally many of the names had to be made descriptive enough to differentiate them from other files, so naming as a minor form of documentation is present as a side effect.
In the end I don't think there are strong arguments for or against one file classes as it's usually just a minor semantically change to go from onw to the other (unless your code is in a horribly unorganized state... in which case you should be shamed into fixing it).
EDIT!
I fixed the bad reference to Matlab adopting Java's one class file system -- after more research it appears that both developers adopted this style independently (or rather didn't specify that the other language influenced their decision). This is especially true since Matlab didn't bundle Java until 2000.
I don't think there any advantage. But you can put as many functions as you need in a single file.
For example:
classdef UTILS
methods (Static)
function help
% prints help for all functions
disp(char(methods(mfilename, '-full')));
end
function func_01()
end
function func_02()
end
% ...more functions
end
end
I find it very neat.
>> UTILS.help
obj UTILS
Static func_01
Static func_02
Static help
>> UTILS.func_01()
I am in the process of writing a toy compiler in scala. The target language itself looks like scala but is an open field for experiment.
After several large refactorings I can't find a good way to model my abstract syntax tree. I would like to use the facilities of scala's pattern matching, the problem is that the tree carries moving information (like types, symbols) along the compilation process.
I can see a couple of solutions, none of which I like :
case classes with mutable fields (I believe the scala compiler does this) : the problem is that those fields are not present a each stage of the compilation and thus have to be nulled (or Option'd) and it becomes really heavy to debug/write code. Moreover, if for exemple, I find a node with null type after the typing phase I have a really hard time finding the cause of the bug.
huge trait/case class hierarchy : something like Node, NodeWithSymbol, NodeWithType, ... Seems like a pain to write AND work with
something completly hand crafted with extractors
I'm also not sure if it is good practice to go with a fully immutable AST, especially in scala where there is no implicit sharing (because the compiler is not aware of immutability) and it could hurt performances to copy the tree all the time.
Can you think of an elegant pattern to model my tree using scala's powerful type system ?
TL;DR I prefer to keep the AST immutable and carry things like type information in a separate structure, e.g. a Map, that can be referred by IDs stored in the AST. But there is no perfect answer.
You're by no means the first to struggle with this question. Let me list some options:
1) Mutable structures that get updated at each phase. All the up and downsides you mention.
2) Traits/cake pattern. Feasible, but expensive (there's no sharing) and kinda ugly.
3) A new tree type at each phase. In some ways this is the theoretically cleanest. Each phase can deal only with a structure produced for it by the previous phase. Plus the same approach carries all the way from front end to back end. For instance, you may "desugar" at some point and having a new tree type means that downstream phase(s) don't have to even consider the possibility of node types that are eliminated by desugaring. Also, low level optimizations usually need IRs that are significantly lower level than the original AST. But this is also a lot of code since almost everything has to be recreated at each step. This approach can also be slow since there can be almost no data sharing between phases.
4) Label every node in the AST with an ID and use that ID to reference information in other data structures (maps and vectors and such) that hold information computed for each phase. In many ways this is my favorite. It retains immutability, maximizes sharing and minimizes the "excess" code you have to write. But you still have to deal with the potential for "missing" information that can be tricky to debug. It's also not as fast as the mutable option, though faster than any option that requires producing a new tree at each phase.
I recently started writing a toy verifier for a small language, and I am using the Kiama library for the parser, resolver and type checker phases.
Kiama is a Scala library for language processing. It enables convenient analysis and transformation of structured data. The programming styles supported by the library are based on well-known formal language processing paradigms, including attribute grammars, tree rewriting, abstract state machines, and pretty printing.
I'll try to summarise my (fairly limited) experience:
[+] Kiama comes with several examples, and the main contributor usually responds quickly to questions asked on the mailing list
[+] The attribute grammar paradigm allows for a nice separation into "immutable components" of the nodes, e.g., names and subnodes, and "mutable components", e.g., type information
[+] The library comes with a versatile rewriting system which - so far - covered all my use cases
[+] The library, e.g., the pretty printer, make nice examples of DSLs and of various functional patterns/approaches/ideas
[-] The learning curve it definitely steep, even with examples and the mailing list at hand
[-] Implementing the resolving phase in a "purely function" style (cf. my question) seems tricky, but a hybrid approach (which I haven't tried yet) seems to be possible
[-] The attribute grammar paradigm and the resulting separation of concerns doesn't make it obvious how to document the properties nodes have in the end (cf. my question)
[-] Rumour has it, that the attribute grammar paradigm does not yield the fastest implementations
Summarising my summary, I enjoy using Kiama a lot and I strongly recommend that you give it a try, or at least have a look at the examples.
(PS. I am not affiliated with Kiama)
Whenever I see the term source filter I am left wondering as to what it refers to.
Aside from a formal definition, I think an example would also be helpful to drive the message home.
A source filter is a module that modifies some other code before it is evaluated. Therefore the code that is executed is not what the programmer sees when it is written. You can read more about source filters (in the Perl context) at perldoc perlfilter. Some examples are Smart::Comments which allows the programmer to leave debugging commands in comments in the code and employ them only if desired, another is PDL::NiceSlice which is sugar for slicing PDL objects.
Edit:
For more information on usage (should you wish to brave the beast), read the documentation for Filter::Simple which is a typical way to create filters.
Alternatively there is a new and different way to muck about with the source: Devel::Declare lets you interact with Perl's own parser, letting you do many of the same type of thing as a source filter, but without the source filter. This can be "safer" in some respect, yet it has a more limited scope.
A source filter is a form of module which affects the way in which a file use-ing it will be parsed. They are commonly used to simulate syntactical features which Perl does not have natively -- for instance, the Switch source filter was often used to simulate switch statements before Perl's given { } construction was available.
Source filters work by taking the text of the module as input, performing some processing on it, and outputting the filtered source code. For a simple example of how a source filter is implemented, as well as more details, see the perldoc page for perlfilter.
They are pre-processors. They change the source code before it reaches the Perl compiler. You can do scary things with them, in effect implementing your own language, with all the effects this has on readability (for others), robustness (writing parsers is hard) and maintainability (debugging gets tricky when your idea of what the source code is differs from what compiler and runtime think it is).
This is a general design question not relating to any language. I'm a bit torn between going for minimum code or optimum organization.
I'll use my current project as an example. I have a bunch of tabs on a form that perform different functions. Lets say Tab 1 reads in a file with a specific layout, tab 2 exports a file to a specific location, etc. The problem I'm running into now is that I need these tabs to do something slightly different based on the contents of a variable. If it contains a 1 I may need to use Layout A and perform some extra concatenation, if it contains a 2 I may need to use Layout B and do no concatenation but add two integer fields, etc. There could be 10+ codes that I will be looking at.
Is it more preferable to create an individual path for each code early on, or attempt to create a single path that branches out only when absolutely required.
Creating an individual path for each code would allow my code to be extremely easy to follow at a glance, which in turn will help me out later on down the road when debugging or making changes. The downside to this is that I will increase the amount of code written by calling some of the same functions in multiple places (for example, steps 3, 5, and 9 for every single code may be exactly the same.
Creating a single path that would branch out only when required will be a bit messier and more difficult to follow at a glance, but I would create less code by placing conditionals only at steps that are unique.
I realize that this may be a case-by-case decision, but in general, if you were handed a previously built program to work on, which would you prefer?
Edit: I've drawn some simple images to help express it. Codes 1/2/3 are the variables and the lines under them represent the paths they would take. All of these steps need to be performed in a linear chronological fashion, so there would be a function to essentially just call other functions in the proper order.
Different Paths
Single Path
Creating a single path that would
branch out only when required will be
a bit messier and more difficult to
follow at a glance, but I would create
less code by placing conditionals only
at steps that are unique.
Im not buying this statement. There is a level of finesse when deciding when to write new functions. Functions should be as simple and reusable as possible (but no simpler). The correct answer is almost never 'one big file that does a lot of branching'.
Less LOC (lines of code) should not be the goal. Readability and maintainability should be the goal. When you create functions, the names should be self documenting. If you have a large block of code, it is good to do something like
function doSomethingComplicated() {
stepOne();
stepTwo();
// and so on
}
where the function names are self documenting. Not only will the code be more readable, you will make it easier to unit test each segment of the code in isolation.
For the case where you will have a lot of methods that call the same exact methods, you can use good OO design and design patterns to minimize the number of functions that do the same thing. This is in reference to your statement "The downside to this is that I will increase the amount of code written by calling some of the same functions in multiple places (for example, steps 3, 5, and 9 for every single code may be exactly the same."
The biggest danger in starting with one big block of code is that it will never actually get refactored into smaller units. Just start down the right path to begin with....
EDIT --
for your picture, I would create a base-class with all of the common methods that are used. The base class would be abstract, with an abstract method. Subclasses would implement the abstract method and use the common functions they need. Of course, replace 'abstract' with whatever your language of choice provides.
You should always err on the side of generalization, with the only exception being early prototyping (where throughput of generating working stuff is majorly impacted by designing correct abstractions/generalizations). having said that, you should NEVER leave that mess of non-generalized cloned branches past the early prototype stage, as it leads to messy hard to maintain code (if you are doing almost the same thing 3 different times, and need to change that thing, you're almost sure to forget to change 1 out of 3).
Again it's hard to specifically answer such an open ended question, but I believe you don't have to sacrifice one for the other.
OOP techniques solves this issue by allowing you to encapsulate the reusable portions of your code and generate child classes to handle object specific behaviors.
Personally I think you might (if possible by your API) create inherited forms, create them on fly on master form (with tabs), pass agruments and embed in tab container.
When to inherit form and when to decide to use arguments (code) to show/hide/add/remove functionality is up to you, yet master form should contain only decisions and argument passing and embeddable forms just plain functionality - this way you can separate organisation from implementation.