On Thu, 1 Mar 2018, Allan, Bruce W wrote:
> > -----Original Message-----
> > From: Julia Lawall [mailto:[email protected]]
> > Sent: Thursday, March 01, 2018 11:46 AM
> > To: Allan, Bruce W <[email protected]>
> > Cc: [email protected]
> > Subject: Re: [Cocci] transform needing a calculation from a Python script
> >
> >
> >
> > On Thu, 1 Mar 2018, Allan, Bruce W wrote:
> >
> > >
> > > We have a macro that takes a right-justified contiguous set of bits and
> > > shifts it left to create a bitmask:
> > >
> > >
> > >
> > > #define FOO(m, s) (m) << (s)
> > >
> > >
> > >
> > > where m is in hex and s is an integer. I’d like to transform occurrences
> > > of
> > > it to the Linux kernel’s GENMASK(high, low) macro (which creates a
> > > contiguous bitmask starting at bit position low and ending at position
> > > high), but am having problems trying to figure out how to do that.
> > >
> > >
> > >
> > > For example, I’d like to transform:
> > >
> > > #define BITMASK_A FOO(0x3F, 4)
> > > /* 0x3F0 */
> > >
> > > to
> > >
> > > #define BITMASK_A GENMASK(9, 4) /*
> > > 0x3F0 */
> > >
> > >
> > >
> > > The value s in FOO() is the same as the value low in GENMASK(), but the
> > > value high in GENMASK() must be calculated from the values m and s in
> > > FOO(). One calculation would be to use the hamming weight (hweight) such
> > as
> > > hweight(m) + s – 1. My Python-foo is non-existent but I have found online
> > > an example for calculating the hamming weight with the Python script ‘def
> > > hweight(n): return bin(n).count("1")’. Is it possible to use this (or
> > > another) Python script in a Coccinelle script to do this transform, and if
> > > so, what would that look like? If the transform cannot use Python, is
> > > there
> > > another suggestion?
> >
> > I think that you can follow the model of the following code
> > (demos/pythontococci.cocci). Let me know if it is not clear.
>
> Sorry, no, it is not clear to me how this works.
The first rule matches whatever you want to change and established some
metavariables that contain information you will want to give to python.
The second rule declares some new variables y and z, as well as inheriting
information from the first rule. This is where you call your python code,
and you assign the new variables to whatever you will need to compute your
result. The last rule uses the information obtained from the first and
second rules to make the transformation. It declares the metavariables
inherited from python as identifiers, but they can contain any
more complex expression as well.
julia
>
> >
> > julia
> >
> > @a@
> > identifier x;
> > @@
> >
> > foo(x);
> >
> > @script:python b@
> > x << a.x;
> > y;
> > z;
> > @@
> >
> > print y
> > coccinelle.y = x
> > coccinelle.z = "something"
> > print y
> >
> > @c@
> > identifier b.y;
> > identifier b.z;
> > identifier a.x;
> > @@
> >
> > - bar();
> > + matched_bar(y,z,x);
>_______________________________________________
Cocci mailing list
[email protected]
https://systeme.lip6.fr/mailman/listinfo/cocci
