Re: "accessibility check failed" on Node

[Thomas Schmidt <TC.Schmidt@gmx.net>]

Hi all,

thank you for your tips

On 2013-06-27 08:24:52 +0000, Simon Wright said:

>  spent quite some time making a compilable example. It would have been
> kind of you to have done the same!
Sorry, next time I'll offer a complete compilable example.

> The call in
> 
>      position : constant NodeSets.Cursor :=
>        graph.nodes.Find (aNode.all'Access);
> 
> seemed a bit magical (a respected colleague said that he found himself
> using ".all.Access" as a band-aid for shutting up the compiler's
> complaints about type mismatches without bothering to understand
> them).
Exactly my way: "without bothering to understand them". But it solved 
my problem.

But thank you to your hints. I'll try
- to avoid anonymous types,
- unnecessary access types,
- declare access parameters to exclude null (if usefull).
- (I'm not really a friend of those Ada naming conventions using 
undersore between name components).
- I'm looking for some tutorial describing the most important 
differences between C++ and Ada.


I like Ada being a really type safe and straight forward language 
offering a lot aspects (like the task concept, …) I'm missing in C/C++. 
But as coming from C/C++ its sometimes difficult to really understand 
Adas concepts. So I had to learn that Adas in-parameter mode doesn't 
match C++s call by value. That's one way to avoid access parameter, I 
think. I'm not really familiar with Adas accessibility levels. And last 
but not least I'm currently on the way to understand the differences 
between extensible tagged types and class-wide types.


Some of you mentioned that I could use some publically accesible 
libraries to build up my neural network. That's ok, I'm not really a 
friend of reinventing the wheel. But my goals are not only those neural 
networks but also the Ada language. Otherwise I would use C++ (which is 
really a mess but I'm familiar with it) or use some publically 
available NN simulators. I think the best way to learn is in using 
"real" jobs than examples simplifying the world. It would be a great 
deal to write my own neural net simulator in Ada!


Thanks
Thomas