How do I retrieve a call path with xref - erlang

I'm trying to retrieve the path between two function from the call graph of a set of modules using xref.
Consider the following functions calling each other:
x:a/1 -> y:b/1 -> y:c/1
x:d/1 -> y:e/1
using the query: closure E | a:Mod || b:Mod will give me tuples of the start- and end-points of the paths of any direct or indirect call from module a to module b. Thus for the above example:
[{{x,a,1}, {y,b,1}},
{{x,a,1}, {y,c,1}},
{{x,d,1}, {y,e,1}}]
This is the set of paths through the call graph that I am looking for, but I need the inner verticies as well. For the above example this would be:
[[{x,a,1}, {y,b,1}],
[{x,a,1}, {y,b,1}, {y,c,1}],
[{x,d,1}, {y,e,1}]]
I have tried various variations of the examples given in the XRef documentation. I do understand that the query language operates on sets of verticies and edges, but fail to grasp a number of selection mechanism.
I am using the xref command of rebar3 to work with the queries, all the relevant code is in the project that I call rebar from. I am actually trying to show how the tests are calling the functions in the module.
Side question: Is there any more gentle introduction to the xref query language?

Hopefully you can use this code snippet as a starting point:
q(X) ->
{ok, L} = xref:q(X, "closure E | x:Mod || y:Mod"),
l(X, L).
l(_, []) -> [];
l(X, [{F,T}|L]) ->
Q = io_lib:format("{~p, ~p} of E", [F, T]),
{ok, Path} = xref:q(X, lists:flatten(Q)),
[Path | l(X, L)].

Related

Erlang/Elixir guards and arity

Is there a way to see a function's guards without seeing the source code?
Given an example function (in Elixir):
def divide(x, y) when y != 0 do
x / y
end
How would one figure out that there is a guard on divide/2 without access to the source code, and how would one find info about that guard or what that guard expects for a pattern match?
I was watching a talk by Chris McCord (creator of Elixir's Phoenix Framework) from Ruby Conf 2014. During the talk Chris was describing guards and someone asked if there was a way to inspect a function that would show the function's guards.
This is the question from the talk:
https://www.youtube.com/watch?v=5kYmOyJjGDM&t=5188
The question is asked shortly after the video's t= time.
Currently it is not possible to introspect this information without looking at the source.
If there is debug info in the beam file a library can be created that parses it and get you what you require without looking into source code. Here is one example in Erlang how you can get the arities of a function.
1> GetArities =
fun(Module, FunName) ->
{ok,{_,[{abstract_code,{_,AC}}]}} = beam_lib:chunks(Module,[abstract_code]),
lists:foldl(
fun({function, _Line, Fun, Arity, _Clauses}, FunArities) when Fun == FunName ->
[Arity | FunArities];
(_, FunArities) ->
FunArities
end, [], AC)
end.
2> GetArities(fact,fact).
[1,0]
For a sample module named fact with 2 functions also named fact, you can get the above output.
Clauses in abstract code will have guards with atom op. Those can also be retrieved.

Head Mismatch in simple argument pattern matching

I have this code:
-module(info).
-export([map_functions/0]).
-author("me").
map_functions() ->
{Mod,_} = code:all_loaded(),
map_functions(Mod,#{});
map_functions([H|Tail],A) ->
B = H:mod_info(exports),
map_functions(Tail,A#{H => B});
map_functions([],A) -> A.
However whenever I compile it I get a head mismatch on line 10 which is the
map_funtions([H|Tail],A) ->
I'm sure this is a very basic error but I just cannot get my head around why this does not run. It is a correct pattern match syntax [H|Tail] and the three functions with the same name but different arities are separated by commas.
Your function definition should be
map_functions() ->
{Mod,_} = code:all_loaded(),
map_functions(Mod, #{}).
map_functions([], A) -> A;
map_functions([H|Tail], A) ->
B = H:mod_info(exports),
map_functions(Tail, A#{H => B}).
The name map_functions is the same, but the arity is not. In the Erlang world that means these are two entirely different functions: map_functions/0 and map_functions/2.
Also, note that I put the "base case" first in map_functions/2 (and made the first clause's return value stick out -- breaking that to two lines is more common, but whatever). This is for three reasons: clarity, getting in the habit of writing the base case first (so you don't accidentally write infinite loops), and very often it is necessary to do this so you don't accidentally mask your base case by matching every parameter in a higher-precedence clause.
Some extended discussion on this topic is here (addressing Elixir and Erlang): Specify arity using only or except when importing function on Elixir
Function with same name but different arity are different, they are separated by dots.
code:all_loaded returns a list, so the first function should be written:
map_functions() ->
Mods = code:all_loaded(),
map_functions(Mods, #{}).
The resulting list Mods is a list of tuples of the form {ModName,BeamLocation} so the second function should be written:
map_functions([], A) -> A;
map_functions([{ModName,_}|Tail], A) ->
B = ModName:module_info(exports),
map_functions(Tail, A#{ModName => B}).
Note that you should dig into erlang libraries and try to use more idiomatic forms of code, the whole function, using list comprehension, can be written:
map_functions() ->
maps:from_list([{X,X:module_info(exports)} || {X,_} <- code:all_loaded()]).

Creating a valid function declaration from a complex tuple/list structure

Is there a generic way, given a complex object in Erlang, to come up with a valid function declaration for it besides eyeballing it? I'm maintaining some code previously written by someone who was a big fan of giant structures, and it's proving to be error prone doing it manually.
I don't need to iterate the whole thing, just grab the top level, per se.
For example, I'm working on this right now -
[[["SIP",47,"2",46,"0"],32,"407",32,"Proxy Authentication Required","\r\n"],
[{'Via',
[{'via-parm',
{'sent-protocol',"SIP","2.0","UDP"},
{'sent-by',"172.20.10.5","5060"},
[{'via-branch',"z9hG4bKb561e4f03a40c4439ba375b2ac3c9f91.0"}]}]},
{'Via',
[{'via-parm',
{'sent-protocol',"SIP","2.0","UDP"},
{'sent-by',"172.20.10.15","5060"},
[{'via-branch',"12dee0b2f48309f40b7857b9c73be9ac"}]}]},
{'From',
{'from-spec',
{'name-addr',
[[]],
{'SIP-URI',
[{userinfo,{user,"003018CFE4EF"},[]}],
{hostport,"172.20.10.11",[]},
{'uri-parameters',[]},
[]}},
[{tag,"b7226ffa86c46af7bf6e32969ad16940"}]}},
{'To',
{'name-addr',
[[]],
{'SIP-URI',
[{userinfo,{user,"3966"},[]}],
{hostport,"172.20.10.11",[]},
{'uri-parameters',[]},
[]}},
[{tag,"a830c764"}]},
{'Call-ID',"90df0e4968c9a4545a009b1adf268605#172.20.10.15"},
{'CSeq',1358286,"SUBSCRIBE"},
["date",'HCOLON',
["Mon",44,32,["13",32,"Jun",32,"2011"],32,["17",58,"03",58,"55"],32,"GMT"]],
{'Contact',
[[{'name-addr',
[[]],
{'SIP-URI',
[{userinfo,{user,"3ComCallProcessor"},[]}],
{hostport,"172.20.10.11",[]},
{'uri-parameters',[]},
[]}},
[]],
[]]},
["expires",'HCOLON',3600],
["user-agent",'HCOLON',
["3Com",[]],
[['LWS',["VCX",[]]],
['LWS',["7210",[]]],
['LWS',["IP",[]]],
['LWS',["CallProcessor",[['SLASH',"v10.0.8"]]]]]],
["proxy-authenticate",'HCOLON',
["Digest",'LWS',
["realm",'EQUAL',['SWS',34,"3Com",34]],
[['COMMA',["domain",'EQUAL',['SWS',34,"3Com",34]]],
['COMMA',
["nonce",'EQUAL',
['SWS',34,"btbvbsbzbBbAbwbybvbxbCbtbzbubqbubsbqbtbsbqbtbxbCbxbsbybs",
34]]],
['COMMA',["stale",'EQUAL',"FALSE"]],
['COMMA',["algorithm",'EQUAL',"MD5"]]]]],
{'Content-Length',0}],
"\r\n",
["\n"]]
Maybe https://github.com/etrepum/kvc
I noticed your clarifying comment. I'd prefer to add a comment myself, but don't have enough karma. Anyway, the trick I use for that is to experiment in the shell. I'll iterate a pattern against a sample data structure until I've found the simplest form. You can use the _ match-all variable. I use an erlang shell inside an emacs shell window.
First, bind a sample to a variable:
A = [{a,b},[{c,d}, {e,f}]].
Now set the original structure against the variable:
[{a,b},[{c,d},{e,f}]] = A.
If you hit enter, you'll see they match. Hit alt-p (forget what emacs calls alt, but it's alt on my keyboard) to bring back the previous line. Replace some tuple or list item with an underscore:
[_,[{c,d},{e,f}]].
Hit enter to make sure you did it right and they still match. This example is trivial, but for deeply nested, multiline structures it's trickier, so it's handy to be able to just quickly match to test. Sometimes you'll want to try to guess at whole huge swaths, like using an underscore to match a tuple list inside a tuple that's the third element of a list. If you place it right, you can match the whole thing at once, but it's easy to misread it.
Anyway, repeat to explore the essential shape of the structure and place real variables where you want to pull out values:
[_, [_, _]] = A.
[_, _] = A.
[_, MyTupleList] = A. %% let's grab this tuple list
[{MyAtom,b}, [{c,d}, MyTuple]] = A. %% or maybe we want this atom and tuple
That's how I efficiently dissect and pattern match complex data structures.
However, I don't know what you're doing. I'd be inclined to have a wrapper function that uses KVC to pull out exactly what you need and then distributes to helper functions from there for each type of structure.
If I understand you correctly you want to pattern match some large datastructures of unknown formatting.
Example:
Input: {a, b} {a,b,c,d} {a,[],{},{b,c}}
function({A, B}) -> do_something;
function({A, B, C, D}) when is_atom(B) -> do_something_else;
function({A, B, C, D}) when is_list(B) -> more_doing.
The generic answer is of course that it is undecidable from just data to know how to categorize that data.
First you should probably be aware of iolists. They are created by functions such as io_lib:format/2 and in many other places in the code.
One example is that
[["SIP",47,"2",46,"0"],32,"407",32,"Proxy Authentication Required","\r\n"]
will print as
SIP/2.0 407 Proxy Authentication Required
So, I'd start with flattening all those lists, using a function such as
flatten_io(List) when is_list(List) ->
Flat = lists:map(fun flatten_io/1, List),
maybe_flatten(Flat);
flatten_io(Tuple) when is_tuple(Tuple) ->
list_to_tuple([flatten_io(Element) || Element <- tuple_to_list(Tuple)];
flatten_io(Other) -> Other.
maybe_flatten(L) when is_list(L) ->
case lists:all(fun(Ch) when Ch > 0 andalso Ch < 256 -> true;
(List) when is_list(List) ->
lists:all(fun(X) -> X > 0 andalso X < 256 end, List);
(_) -> false
end, L) of
true -> lists:flatten(L);
false -> L
end.
(Caveat: completely untested and quite inefficient. Will also crash for inproper lists, but you shouldn't have those in your data structures anyway.)
On second thought, I can't help you. Any data structure that uses the atom 'COMMA' for a comma in a string should be taken out and shot.
You should be able to flatten those things as well and start to get a view of what you are looking at.
I know that this is not a complete answer. Hope it helps.
Its hard to recommend something for handling this.
Transforming all the structures in a more sane and also more minimal format looks like its worth it. This depends mainly on the similarities in these structures.
Rather than having a special function for each of the 100 there must be some automatic reformatting that can be done, maybe even put the parts in records.
Once you have records its much easier to write functions for it since you don't need to know the actual number of elements in the record. More important: your code won't break when the number of elements changes.
To summarize: make a barrier between your code and the insanity of these structures by somehow sanitizing them by the most generic code possible. It will be probably a mix of generic reformatting with structure speicific stuff.
As an example already visible in this struct: the 'name-addr' tuples look like they have a uniform structure. So you can recurse over your structures (over all elements of tuples and lists) and match for "things" that have a common structure like 'name-addr' and replace these with nice records.
In order to help you eyeballing you can write yourself helper functions along this example:
eyeball(List) when is_list(List) ->
io:format("List with length ~b\n", [length(List)]);
eyeball(Tuple) when is_tuple(Tuple) ->
io:format("Tuple with ~b elements\n", [tuple_size(Tuple)]).
So you would get output like this:
2> eyeball({a,b,c}).
Tuple with 3 elements
ok
3> eyeball([a,b,c]).
List with length 3
ok
expansion of this in a useful tool for your use is left as an exercise. You could handle multiple levels by recursing over the elements and indenting the output.
Use pattern matching and functions that work on lists to extract only what you need.
Look at http://www.erlang.org/doc/man/lists.html:
keyfind, keyreplace, L = [H|T], ...

Querying mnesia Fragmentated Tables using QLC returns wrong results

am josh in Uganda. i created a mnesia fragmented table (64 fragments), and managed to populate it upto 9948723 records. Each fragment was a disc_copies type, with two replicas.
Now, using qlc (query list comprehension), was too slow in searching for a record, and was returning inaccurate results.
I found out that this overhead is that qlc uses the select function of mnesia which traverses the entire table in order to match records. i tried something else below.
-define(ACCESS_MOD,mnesia_frag).
-define(DEFAULT_CONTEXT,transaction).
-define(NULL,'_').
-record(address,{tel,zip_code,email}).
-record(person,{name,sex,age,address = #address{}}).
match()-> Z = fun(Spec) -> mnesia:match_object(Spec) end,Z.
match_object(Pattern)->
Match = match(),
mnesia:activity(?DEFAULT_CONTEXT,Match,[Pattern],?ACCESS_MOD).
Trying this functionality gave me good results. But i found that i have to dynamically build patterns for every search that may be made in my stored procedures.
i decided to go through the havoc of doing this, so i wrote functions which will dynamically build wild patterns for my records depending on which parameter is to be searched.
%% This below gives me the default pattern for all searches ::= {person,'_','_','_'}
pattern(Record_name)->
N = length(my_record_info(Record_name)) + 1,
erlang:setelement(1,erlang:make_tuple(N,?NULL),Record_name).
%% this finds the position of the provided value and places it in that
%% position while keeping '_' in the other positions.
%% The caller function can use this function recursively until
%% it has built the full search pattern of interest
pattern({Field,Value},Pattern_sofar)->
N = position(Field,my_record_info(element(1,Pattern_sofar))),
case N of
-1 -> Pattern_sofar;
Int when Int >= 1 -> erlang:setelement(N + 1,Pattern_sofar,Value);
_ -> Pattern_sofar
end.
my_record_info(Record_name)->
case Record_name of
staff_dynamic -> record_info(fields,staff_dynamic);
person -> record_info(fields,person);
_ -> []
end.
%% These below,help locate the position of an element in a list
%% returned by "-record_info(fields,person)"
position(_,[]) -> -1;
position(Value,List)->
find(lists:member(Value,List),Value,List,1).
find(false,_,_,_) -> -1;
find(true,V,[V|_],N)-> N;
find(true,V,[_|X],N)->
find(V,X,N + 1).
find(V,[V|_],N)-> N;
find(V,[_|X],N) -> find(V,X,N + 1).
This was working very well though it was computationally intensive.
It could still work even after changing the record definition since at compile time, it gets the new record info
The problem is that when i initiate even 25 processes on a 3.0 GHz pentium 4 processor running WinXP, It hangs and takes a long time to return results.
If am to use qlc in these fragments, to get accurate results, i have to specify which fragment to search in like this.
find_person_by_tel(Tel)->
select(qlc:q([ X || X <- mnesia:table(Frag), (X#person.address)#address.tel == Tel])).
select(Q)->
case ?transact(fun() -> qlc:e(Q) end) of
{atomic,Val} -> Val;
{aborted,_} = Error -> report_mnesia_event(Error)
end.
Qlc was returning [], when i search for something yet when i use match_object/1 i get accurate results. I found that using match_expressions can help.
mnesia:table(Tab,Props).
where Props is a data structure that defines the match expression, the chunk size of return values e.t.c
I got a problem when i tried building match expressions dynamically.
Function mnesia:read/1 or mnesia:read/2 requires that you have the primary key
Now am asking myself, how can i efficiently use QLC to search for records in a large fragmented table? Please help.
I know that using tuple representation of records makes code hard to upgrade. This is why
i hate using mnesia:select/1, mnesia:match_object/1 and i want to stick to QLC. QLC is giving me wrong results in my queries from a mnesia table of 64 fragments even on the same node.
Has anyone ever used QLC to query a fragmented table?, please help
Do you invoke the qlc in the activity context?
tfn_match(Id) ->
Search = #person{address=#address{tel=Id, _ = '_'}, _ = '_'},
trans(fun() -> mnesia:match_object(Search) end).
tfn_qlc(Id) ->
Q = qlc:q([ X || X <- mnesia:table(person), (X#person.address)#address.tel == Id]),
trans(fun() -> qlc:e(Q) end).
trans(Fun) ->
try Res = mnesia:activity(transaction, Fun, mnesia_frag),
{atomic, Res}
catch exit:Error ->
{aborted, Error}
end.

Erlang and run-time record limitations

I'm developing an Erlang system and having reoccurring problems with the fact that records are compile-time pre-processor macros (almost), and that they cant be manipulated at runtime...
basically, I'm working with a property pattern, where properties are added at run-time to objects on the front-end (AS3). Ideally, I would reflect this with a list on the Erlang side, since its a fundamental data type, but then using records in QCL [to query ETS tables] would not be possible since to use them I have to specifically say which record property I want to query over... I have at least 15 columns in the larges table, so listing them all in one huge switch statement (case X of) is just plain ugly.
does anyone have any ideas how to elegantly solve this? maybe some built-in functions for creating tuples with appropriate signatures for use in pattern matching (for QLC)?
thanks
It sounds like you want to be able to do something like get_record_field(Field, SomeRecord) where Field is determined at runtime by user interface code say.
You're right in that you can't do this in standard erlang as records and the record_info function are expanded and eliminated at compile time.
There are a couple of solutions that I've used or looked at. My solution is as follows: (the example gives runtime access to the #dns_rec and #dns_rr records from inet_dns.hrl)
%% Retrieves the value stored in the record Rec in field Field.
info(Field, Rec) ->
Fields = fields(Rec),
info(Field, Fields, tl(tuple_to_list(Rec))).
info(_Field, _Fields, []) -> erlang:error(bad_record);
info(_Field, [], _Rec) -> erlang:error(bad_field);
info(Field, [Field | _], [Val | _]) -> Val;
info(Field, [_Other | Fields], [_Val | Values]) -> info(Field, Fields, Values).
%% The fields function provides the list of field positions
%% for all the kinds of record you want to be able to query
%% at runtime. You'll need to modify this to use your own records.
fields(#dns_rec{}) -> fields(dns_rec);
fields(dns_rec) -> record_info(fields, dns_rec);
fields(#dns_rr{}) -> fields(dns_rr);
fields(dns_rr) -> record_info(fields, dns_rr).
%% Turns a record into a proplist suitable for use with the proplists module.
to_proplist(R) ->
Keys = fields(R),
Values = tl(tuple_to_list(R)),
lists:zip(Keys,Values).
A version of this that compiles is available here: rec_test.erl
You can also extend this dynamic field lookup to dynamic generation of matchspecs for use with ets:select/2 or mnesia:select/2 as shown below:
%% Generates a matchspec that does something like this
%% QLC psuedocode: [ V || #RecordKind{MatchField=V} <- mnesia:table(RecordKind) ]
match(MatchField, RecordKind) ->
MatchTuple = match_tuple(MatchField, RecordKind),
{MatchTuple, [], ['$1']}.
%% Generates a matchspec that does something like this
%% QLC psuedocode: [ T || T <- mnesia:table(RecordKind),
%% T#RecordKind.Field =:= MatchValue]
match(MatchField, MatchValue, RecordKind) ->
MatchTuple = match_tuple(MatchField, RecordKind),
{MatchTuple, [{'=:=', '$1', MatchValue}], ['$$']}.
%% Generates a matchspec that does something like this
%% QLC psuedocode: [ T#RecordKind.ReturnField
%% || T <- mnesia:table(RecordKind),
%% T#RecordKind.MatchField =:= MatchValue]
match(MatchField, MatchValue, RecordKind, ReturnField)
when MatchField =/= ReturnField ->
MatchTuple = list_to_tuple([RecordKind
| [if F =:= MatchField -> '$1'; F =:= ReturnField -> '$2'; true -> '_' end
|| F <- fields(RecordKind)]]),
{MatchTuple, [{'=:=', '$1', MatchValue}], ['$2']}.
match_tuple(MatchField, RecordKind) ->
list_to_tuple([RecordKind
| [if F =:= MatchField -> '$1'; true -> '_' end
|| F <- fields(RecordKind)]]).
Ulf Wiger has also written a parse_transform, Exprecs, that more or less does this for you automagically. I've never tried it, but Ulf's code is usually very good.
I solve this problem (in development) by use the parse transform tools to read the .hrl files and generate helper functions.
I wrote a tutorial on it at Trap Exit.
We use it all the time to generate match specs. The beauty is that you don't need to know anything about the current state of the record at development time.
However once you are in production things change! If your record is the basis of a table (as opposed to the definition of a field in a table) then changing an underlying record is more difficult (to put it mildly!).
I'm not sure I fully understand your Problem but I have moved from records to proplists in most cases. They are much more flexible and much slower. Using (d)ets I usually use a few record fields for coarse selection and then check the proplists on the remaining records for detailed selection.

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