public inbox for gcc-prs@sourceware.org
help / color / mirror / Atom feed
* Re: debug/1621: Debugging with complex numbers
@ 2002-12-05 12:09 bangerth
  0 siblings, 0 replies; 15+ messages in thread
From: bangerth @ 2002-12-05 12:09 UTC (permalink / raw)
  To: gcc-bugs, gcc-prs, jsm28, nobody

Synopsis: Debugging with complex numbers

State-Changed-From-To: open->feedback
State-Changed-By: bangerth
State-Changed-When: Thu Dec  5 12:09:13 2002
State-Changed-Why:
    Joseph, this report is now almost 2 years old, and versions
    3.0 and 3.1/2 have happened in between. Unfortunately, there
    are no testcases in the report, so I can't check the claims
    myself, but do you know whether the situation has or has
    not improved in the meantime?
    
    Thanks
      Wolfgang

http://gcc.gnu.org/cgi-bin/gnatsweb.pl?cmd=view%20audit-trail&database=gcc&pr=1621


^ permalink raw reply	[flat|nested] 15+ messages in thread

* Re: debug/1621: Debugging with complex numbers
@ 2002-12-28 10:59 jsm28
  0 siblings, 0 replies; 15+ messages in thread
From: jsm28 @ 2002-12-28 10:59 UTC (permalink / raw)
  To: gcc-bugs, gcc-prs, jsm28, nobody

Synopsis: Debugging with complex numbers

State-Changed-From-To: feedback->closed
State-Changed-By: jsm28
State-Changed-When: Sat Dec 28 10:59:23 2002
State-Changed-Why:
    This has now been fixed by Jim Wilson.

http://gcc.gnu.org/cgi-bin/gnatsweb.pl?cmd=view%20audit-trail&database=gcc&pr=1621


^ permalink raw reply	[flat|nested] 15+ messages in thread

* Re: debug/1621: Debugging with complex numbers
@ 2002-12-13 11:26 Joseph S. Myers
  0 siblings, 0 replies; 15+ messages in thread
From: Joseph S. Myers @ 2002-12-13 11:26 UTC (permalink / raw)
  To: nobody; +Cc: gcc-prs

The following reply was made to PR debug/1621; it has been noted by GNATS.

From: "Joseph S. Myers" <jsm28@cam.ac.uk>
To: Jim Wilson <wilson@redhat.com>
Cc: Wolfgang Bangerth <bangerth@ticam.utexas.edu>, 
    Daniel Jacobowitz <drow@mvista.com>,  <bangerth@dealii.org>, 
     <gcc-bugs@gcc.gnu.org>,  <gcc-gnats@gcc.gnu.org>
Subject: Re: debug/1621: Debugging with complex numbers
Date: Fri, 13 Dec 2002 19:17:13 +0000 (GMT)

 On 12 Dec 2002, Jim Wilson wrote:
 
 > Here is an attempt to fix the documentation problem.  Comments?
 
 This patch looks OK.
 
 -- 
 Joseph S. Myers
 jsm28@cam.ac.uk
 


^ permalink raw reply	[flat|nested] 15+ messages in thread

* Re: debug/1621: Debugging with complex numbers
@ 2002-12-13  9:32 wilson
  0 siblings, 0 replies; 15+ messages in thread
From: wilson @ 2002-12-13  9:32 UTC (permalink / raw)
  To: gcc-bugs, gcc-prs, jsm28, nobody

Synopsis: Debugging with complex numbers

State-Changed-From-To: analyzed->feedback
State-Changed-By: wilson
State-Changed-When: Fri Dec 13 09:32:42 2002
State-Changed-Why:
    I have checked in a dbxout.c patch to fix the stabs problem,
    and I have suggested a patch to fix the documentation problem.

http://gcc.gnu.org/cgi-bin/gnatsweb.pl?cmd=view%20audit-trail&database=gcc&pr=1621


^ permalink raw reply	[flat|nested] 15+ messages in thread

* Re: debug/1621: Debugging with complex numbers
@ 2002-12-12 14:16 Jim Wilson
  0 siblings, 0 replies; 15+ messages in thread
From: Jim Wilson @ 2002-12-12 14:16 UTC (permalink / raw)
  To: nobody; +Cc: gcc-prs

The following reply was made to PR debug/1621; it has been noted by GNATS.

From: Jim Wilson <wilson@redhat.com>
To: Daniel Jacobowitz <drow@mvista.com>
Cc: Wolfgang Bangerth <bangerth@ticam.utexas.edu>,
   "Joseph S. Myers" <jsm28@cam.ac.uk>, bangerth@dealii.org,
   gcc-bugs@gcc.gnu.org, gcc-gnats@gcc.gnu.org
Subject: Re: debug/1621: Debugging with complex numbers
Date: 12 Dec 2002 17:08:08 -0500

 >Didn't you generate some 'R' entires for REAL_TYPE in the previous
 >patch?
 
 I added code to handle REAL_TYPE in the new dbxout_fptype_value function, but
 I am not calling this function for REAL_TYPE.  I am only calling it for
 COMPLEX_TYPE.  I added a comment that mentions this to the revised patch that
 I am testing now.
 
 Jim


^ permalink raw reply	[flat|nested] 15+ messages in thread

* Re: debug/1621: Debugging with complex numbers
@ 2002-12-12 13:36 Jim Wilson
  0 siblings, 0 replies; 15+ messages in thread
From: Jim Wilson @ 2002-12-12 13:36 UTC (permalink / raw)
  To: nobody; +Cc: gcc-prs

The following reply was made to PR debug/1621; it has been noted by GNATS.

From: Jim Wilson <wilson@redhat.com>
To: "Joseph S. Myers" <jsm28@cam.ac.uk>
Cc: Wolfgang Bangerth <bangerth@ticam.utexas.edu>,
   Daniel Jacobowitz <drow@mvista.com>, bangerth@dealii.org,
   gcc-bugs@gcc.gnu.org, gcc-gnats@gcc.gnu.org
Subject: Re: debug/1621: Debugging with complex numbers
Date: 12 Dec 2002 16:30:10 -0500

 Here is an attempt to fix the documentation problem.  Comments?
 
 2002-12-12  Jim Wilson  <wilson@redhat.com>
 
 	* doc/extend.texi (Complex Numbers): Update info on debug info.
 
 Index: extend.texi
 ===================================================================
 RCS file: /cvs/gcc/gcc/gcc/doc/extend.texi,v
 retrieving revision 1.108
 diff -p -r1.108 extend.texi
 *** extend.texi	27 Nov 2002 06:32:13 -0000	1.108
 --- extend.texi	12 Dec 2002 20:46:44 -0000
 *************** provided as built-in functions by GCC@.
 *** 1224,1239 ****
   
   GCC can allocate complex automatic variables in a noncontiguous
   fashion; it's even possible for the real part to be in a register while
 ! the imaginary part is on the stack (or vice-versa).  None of the
 ! supported debugging info formats has a way to represent noncontiguous
 ! allocation like this, so GCC describes a noncontiguous complex
 ! variable as if it were two separate variables of noncomplex type.
   If the variable's actual name is @code{foo}, the two fictitious
   variables are named @code{foo$real} and @code{foo$imag}.  You can
   examine and set these two fictitious variables with your debugger.
 - 
 - A future version of GDB will know how to recognize such pairs and treat
 - them as a single variable with a complex type.
   
   @node Hex Floats
   @section Hex Floats
 --- 1224,1236 ----
   
   GCC can allocate complex automatic variables in a noncontiguous
   fashion; it's even possible for the real part to be in a register while
 ! the imaginary part is on the stack (or vice-versa).  Only the DWARF2
 ! debug info format can represent this, so use of DWARF2 is recommended.
 ! If you are using the stabs debug info format, GCC describes a noncontiguous
 ! complex variable as if it were two separate variables of noncomplex type.
   If the variable's actual name is @code{foo}, the two fictitious
   variables are named @code{foo$real} and @code{foo$imag}.  You can
   examine and set these two fictitious variables with your debugger.
   
   @node Hex Floats
   @section Hex Floats


^ permalink raw reply	[flat|nested] 15+ messages in thread

* Re: debug/1621: Debugging with complex numbers
@ 2002-12-12 11:56 Daniel Jacobowitz
  0 siblings, 0 replies; 15+ messages in thread
From: Daniel Jacobowitz @ 2002-12-12 11:56 UTC (permalink / raw)
  To: nobody; +Cc: gcc-prs

The following reply was made to PR debug/1621; it has been noted by GNATS.

From: Daniel Jacobowitz <drow@mvista.com>
To: Jim Wilson <wilson@redhat.com>
Cc: Wolfgang Bangerth <bangerth@ticam.utexas.edu>,
	"Joseph S. Myers" <jsm28@cam.ac.uk>, bangerth@dealii.org,
	gcc-bugs@gcc.gnu.org, gcc-gnats@gcc.gnu.org
Subject: Re: debug/1621: Debugging with complex numbers
Date: Thu, 12 Dec 2002 14:51:56 -0500

 On Thu, Dec 12, 2002 at 10:55:17AM -0500, Jim Wilson wrote:
 > >I recommend emitting just the generic NF_COMPLEX and NF_FLOATING (?)
 > >for any of the unknown types.
 > 
 > NF_COMPLEX is supposed to be IEEE single complex.  There is no generic
 > value for complex types.  However, I do see your point, since we have the
 > type size anyways, we don't really need to distinguish between the different
 > complex types for IEEE FP targets.
 > 
 > There is a problem if we want to distinguish between IEEE and non-IEEE FP,
 > in which case the type size is not enough.  For instance, most RISC targets
 > use a 128-bit IEEE double-extended type.  However, some powerpc targets use
 > a 128-bit non-IEEE IBM pair-of-doubles type.  We can distinguish between these
 > two only if we have a special NF_* value for the IBM pair-of-doubles type.
 > Or alternatively, gdb just has to know that some targets use a non-IEEE long
 > double type.  This is different problem from the one we are trying to fix
 > though, and can be postponed for now.
 
 Right.  GDB already has a different mechanism to handle this case, so
 I'm not terribly worried about the details of using stabs and IEEE long
 double on a non-IEEE platform in this circumstance.
 
 > >First of all, for floating point types we could just continue to use
 > >'r'.  It's not problematic in that case.  On the other hand consistency
 > >is nice.
 > 
 > My patch continues to use 'r' for floating point types for now.  I didn't
 > want to break backwards compatibility for other stabs targets.  'R' will
 > presumably only work on the Sun debugger and gdb.  It is OK to use 'R' for
 > complex because it is an GNU C extension to ISO C90, so users can't expect
 > old debuggers to handle it correctly.
 
 Didn't you generate some 'R' entires for REAL_TYPE in the previous
 patch?
 
 > I will modify my patch to use NF_COMPLEX and NF_SINGLE as generic FP type
 > descriptors and add appropriate comments about what we are doing in order
 > to fix GCC PR debug/1621.
 
 Thank you!
 
 -- 
 Daniel Jacobowitz
 MontaVista Software                         Debian GNU/Linux Developer


^ permalink raw reply	[flat|nested] 15+ messages in thread

* Re: debug/1621: Debugging with complex numbers
@ 2002-12-12  7:56 Jim Wilson
  0 siblings, 0 replies; 15+ messages in thread
From: Jim Wilson @ 2002-12-12  7:56 UTC (permalink / raw)
  To: nobody; +Cc: gcc-prs

The following reply was made to PR debug/1621; it has been noted by GNATS.

From: Jim Wilson <wilson@redhat.com>
To: Daniel Jacobowitz <drow@mvista.com>
Cc: Wolfgang Bangerth <bangerth@ticam.utexas.edu>,
   "Joseph S. Myers" <jsm28@cam.ac.uk>, bangerth@dealii.org,
   gcc-bugs@gcc.gnu.org, gcc-gnats@gcc.gnu.org
Subject: Re: debug/1621: Debugging with complex numbers
Date: 12 Dec 2002 10:55:17 -0500

 >I recommend emitting just the generic NF_COMPLEX and NF_FLOATING (?)
 >for any of the unknown types.
 
 NF_COMPLEX is supposed to be IEEE single complex.  There is no generic
 value for complex types.  However, I do see your point, since we have the
 type size anyways, we don't really need to distinguish between the different
 complex types for IEEE FP targets.
 
 There is a problem if we want to distinguish between IEEE and non-IEEE FP,
 in which case the type size is not enough.  For instance, most RISC targets
 use a 128-bit IEEE double-extended type.  However, some powerpc targets use
 a 128-bit non-IEEE IBM pair-of-doubles type.  We can distinguish between these
 two only if we have a special NF_* value for the IBM pair-of-doubles type.
 Or alternatively, gdb just has to know that some targets use a non-IEEE long
 double type.  This is different problem from the one we are trying to fix
 though, and can be postponed for now.
 
 >First of all, for floating point types we could just continue to use
 >'r'.  It's not problematic in that case.  On the other hand consistency
 >is nice.
 
 My patch continues to use 'r' for floating point types for now.  I didn't
 want to break backwards compatibility for other stabs targets.  'R' will
 presumably only work on the Sun debugger and gdb.  It is OK to use 'R' for
 complex because it is an GNU C extension to ISO C90, so users can't expect
 old debuggers to handle it correctly.
 
 I will modify my patch to use NF_COMPLEX and NF_SINGLE as generic FP type
 descriptors and add appropriate comments about what we are doing in order
 to fix GCC PR debug/1621.
 
 Jim


^ permalink raw reply	[flat|nested] 15+ messages in thread

* Re: debug/1621: Debugging with complex numbers
@ 2002-12-11 17:26 Daniel Jacobowitz
  0 siblings, 0 replies; 15+ messages in thread
From: Daniel Jacobowitz @ 2002-12-11 17:26 UTC (permalink / raw)
  To: nobody; +Cc: gcc-prs

The following reply was made to PR debug/1621; it has been noted by GNATS.

From: Daniel Jacobowitz <drow@mvista.com>
To: Jim Wilson <wilson@redhat.com>
Cc: Wolfgang Bangerth <bangerth@ticam.utexas.edu>,
	"Joseph S. Myers" <jsm28@cam.ac.uk>, bangerth@dealii.org,
	gcc-bugs@gcc.gnu.org, gcc-gnats@gcc.gnu.org
Subject: Re: debug/1621: Debugging with complex numbers
Date: Wed, 11 Dec 2002 20:22:45 -0500

 On Wed, Dec 11, 2002 at 07:05:47PM -0500, Jim Wilson wrote:
 > About the $imag, $real stuff in the gcc/doc/extend.texi file...
 > The part about "None of the supported debug info formats..." is obsolete.
 > DWARF2 location descriptions can handle this easily, and this is already
 > supported in dwarf2out.c.  Perhaps also DWARF, but I don't care enough to look
 > it up.  The stabs hack of emitting two foo$imag and foo$real symbols is ugly
 > and should be discouraged.  I don't think it makes any sense to teach gdb
 > about this hack.  We should instead encourage use of DWARF2, which we are
 > already doing.
 
 I agree.
 
 > I tried writing a patch to make gcc use the Solaris 'R' stab letter extension.
 > 
 > This brings up a number of questions.  Sun only defined 3 float and 3 complex
 > float types.  However, we have 7 float types and 6 complex float types.  (They
 > should be the same, but that is a different problem.)  Do we extend the
 > Solaris extension to meet our needs?  Or fall back on the problematic 'r'
 > letter when we can't use 'R'?  Extending 'R' might make us incompatible with
 > Sun if in the future Sun extends it too, so trying to discuss it with Sun is
 > a good idea.  Or perhaps invent our own similar extension that won't conflict
 > with Sun?
 
 First of all, for floating point types we could just continue to use
 'r'.  It's not problematic in that case.  On the other hand consistency
 is nice.
 
 I recommend emitting just the generic NF_COMPLEX and NF_FLOATING (?)
 for any of the unknown types.  GDB only uses the type to determine if
 it is a floating or complex type, so that will suffice.
 
 -- 
 Daniel Jacobowitz
 MontaVista Software                         Debian GNU/Linux Developer


^ permalink raw reply	[flat|nested] 15+ messages in thread

* Re: debug/1621: Debugging with complex numbers
@ 2002-12-11 16:16 Jim Wilson
  0 siblings, 0 replies; 15+ messages in thread
From: Jim Wilson @ 2002-12-11 16:16 UTC (permalink / raw)
  To: nobody; +Cc: gcc-prs

The following reply was made to PR debug/1621; it has been noted by GNATS.

From: Jim Wilson <wilson@redhat.com>
To: Daniel Jacobowitz <drow@mvista.com>
Cc: Wolfgang Bangerth <bangerth@ticam.utexas.edu>,
   "Joseph S. Myers" <jsm28@cam.ac.uk>, bangerth@dealii.org,
   gcc-bugs@gcc.gnu.org, gcc-gnats@gcc.gnu.org
Subject: Re: debug/1621: Debugging with complex numbers
Date: 11 Dec 2002 19:05:47 -0500

 About the $imag, $real stuff in the gcc/doc/extend.texi file...
 The part about "None of the supported debug info formats..." is obsolete.
 DWARF2 location descriptions can handle this easily, and this is already
 supported in dwarf2out.c.  Perhaps also DWARF, but I don't care enough to look
 it up.  The stabs hack of emitting two foo$imag and foo$real symbols is ugly
 and should be discouraged.  I don't think it makes any sense to teach gdb
 about this hack.  We should instead encourage use of DWARF2, which we are
 already doing.
 
 I tried writing a patch to make gcc use the Solaris 'R' stab letter extension.
 
 This brings up a number of questions.  Sun only defined 3 float and 3 complex
 float types.  However, we have 7 float types and 6 complex float types.  (They
 should be the same, but that is a different problem.)  Do we extend the
 Solaris extension to meet our needs?  Or fall back on the problematic 'r'
 letter when we can't use 'R'?  Extending 'R' might make us incompatible with
 Sun if in the future Sun extends it too, so trying to discuss it with Sun is
 a good idea.  Or perhaps invent our own similar extension that won't conflict
 with Sun?
 
 Also, there is the issue of IEEE versus non-IEEE types.  These types as
 defined are supposed to be for IEEE FP types only.  We support a number of
 non-IEEE fp types.  Do we use the same type number for both?  Or do we add
 even more type numbers for non-IEEE types?
 
 Here is a provisional gcc patch that makes Joseph Myers 4 tests work.
 
 The IEEE vs non-IEEE problem can be ignored for now.  However, the issue of
 handling non-standard float types can't be, because as written the patch
 will abort for targets using non-standard float types.
 
 2002-12-11  Jim Wilson  <wilson@redhat.com>
 
 	* dbxout.c (dbxout_fptype_value): New.
 	(dbxout_type, case COMPLEX_TYPE): Call it.  Use 'R' instead of 'r'.
 
 Index: dbxout.c
 ===================================================================
 RCS file: /cvs/gcc/gcc/gcc/dbxout.c,v
 retrieving revision 1.129
 diff -p -r1.129 dbxout.c
 *** dbxout.c	8 Nov 2002 23:12:24 -0000	1.129
 --- dbxout.c	12 Dec 2002 00:01:20 -0000
 *************** static void dbxout_finish		PARAMS ((cons
 *** 294,299 ****
 --- 294,300 ----
   static void dbxout_start_source_file	PARAMS ((unsigned, const char *));
   static void dbxout_end_source_file	PARAMS ((unsigned));
   static void dbxout_typedefs		PARAMS ((tree));
 + static void dbxout_fptype_value		PARAMS ((tree));
   static void dbxout_type_index		PARAMS ((tree));
   #if DBX_CONTIN_LENGTH > 0
   static void dbxout_continue		PARAMS ((void));
 *************** dbxout_finish (filename)
 *** 689,694 ****
 --- 690,738 ----
   #endif /* DBX_OUTPUT_MAIN_SOURCE_FILE_END */
   }
   
 + /* Output floating point type values used by the 'R' stab letter.
 +    These numbers come from include/aout/stab_gnu.h in binutils/gdb.  */
 + 
 + /* ??? These are supposed to be IEEE types, but we don't check for that.
 +    We could perhaps add additional numbers for non-IEEE types if we need
 +    them.  */
 + 
 + static void
 + dbxout_fptype_value (type)
 +      tree type;
 + {
 +   char value = '0';
 +   enum machine_mode mode = TYPE_MODE (type);
 + 
 +   if (TREE_CODE (type) == REAL_TYPE)
 +     {
 +       if (mode == SFmode)
 + 	value = '1';
 +       else if (mode == DFmode)
 + 	value = '2';
 +       else if (mode == TFmode || mode == XFmode)
 + 	value = '6';
 +       else
 + 	abort ();
 +     }
 +   else if (TREE_CODE (type) == COMPLEX_TYPE)
 +     {
 +       if (mode == SCmode)
 + 	value = '3';
 +       else if (mode == DCmode)
 + 	value = '4';
 +       else if (mode == TCmode || mode == XCmode)
 + 	value = '5';
 +       else
 + 	abort ();
 +     }
 +   else
 +     abort ();
 + 
 +   putc (value, asmfile);
 +   CHARS (1);
 + }
 + 
   /* Output the index of a type.  */
   
   static void
 *************** dbxout_type (type, full)
 *** 1362,1370 ****
   
         if (TREE_CODE (TREE_TYPE (type)) == REAL_TYPE)
   	{
 ! 	  fprintf (asmfile, "r");
   	  CHARS (1);
 ! 	  dbxout_type_index (type);
   	  putc (';', asmfile);
   	  CHARS (1);
   	  print_wide_int (2 * int_size_in_bytes (TREE_TYPE (type)));
 --- 1406,1414 ----
   
         if (TREE_CODE (TREE_TYPE (type)) == REAL_TYPE)
   	{
 ! 	  putc ('R', asmfile);
   	  CHARS (1);
 ! 	  dbxout_fptype_value (type);
   	  putc (';', asmfile);
   	  CHARS (1);
   	  print_wide_int (2 * int_size_in_bytes (TREE_TYPE (type)));


^ permalink raw reply	[flat|nested] 15+ messages in thread

* Re: debug/1621: Debugging with complex numbers
@ 2002-12-09 12:24 bangerth
  0 siblings, 0 replies; 15+ messages in thread
From: bangerth @ 2002-12-09 12:24 UTC (permalink / raw)
  To: gcc-bugs, gcc-prs, jsm28, nobody

Synopsis: Debugging with complex numbers

State-Changed-From-To: feedback->analyzed
State-Changed-By: bangerth
State-Changed-When: Mon Dec  9 12:24:16 2002
State-Changed-Why:
    Still not fixed.

http://gcc.gnu.org/cgi-bin/gnatsweb.pl?cmd=view%20audit-trail&database=gcc&pr=1621


^ permalink raw reply	[flat|nested] 15+ messages in thread

* Re: debug/1621: Debugging with complex numbers
@ 2002-12-07 17:26 Daniel Jacobowitz
  0 siblings, 0 replies; 15+ messages in thread
From: Daniel Jacobowitz @ 2002-12-07 17:26 UTC (permalink / raw)
  To: nobody; +Cc: gcc-prs

The following reply was made to PR debug/1621; it has been noted by GNATS.

From: Daniel Jacobowitz <drow@mvista.com>
To: Wolfgang Bangerth <bangerth@ticam.utexas.edu>
Cc: "Joseph S. Myers" <jsm28@cam.ac.uk>, bangerth@dealii.org,
	gcc-bugs@gcc.gnu.org, gcc-gnats@gcc.gnu.org
Subject: Re: debug/1621: Debugging with complex numbers
Date: Sat, 7 Dec 2002 20:21:24 -0500

 On Thu, Dec 05, 2002 at 06:09:46PM -0600, Wolfgang Bangerth wrote:
 > 
 > 
 > > >     Joseph, this report is now almost 2 years old, and versions
 > > >     3.0 and 3.1/2 have happened in between. Unfortunately, there
 > > >     are no testcases in the report, so I can't check the claims
 > > >     myself, but do you know whether the situation has or has
 > > >     not improved in the meantime?
 > > 
 > > The testcase is at the URL given in the report 
 > > <http://gcc.gnu.org/ml/gcc/2000-12/msg00536.html>:
 > 
 > Oh, sorry, I seem to have overlooked this. 
 > 
 > 
 > >         static __complex__ double x = 2.0 + 3.0i;
 > >         int main(void)
 > >         {
 > >           return 0;
 > >         }
 > > 
 > > (gdb) p x
 > > $1 = Invalid C/C++ type code 20 in symbol table.
 > > (gdb) p x$real
 > > No symbol "x$real" in current context.
 > > (gdb) p x$imag
 > > No symbol "x$imag" in current context.
 > 
 > This is also the behavior I get, using 3.3CVS and gdb5.1.1. For some 
 > reason, I cannot get gdb CVS compiled, so can't check whether it works 
 > now. The gdb error message indicates that gcc is doing something but gdb 
 > isn't understanding it.
 > 
 > Daniel, I'm CC:ing you since you wrote the latest mail I could find on the 
 > gdb mailing lists that is about complex value support 
 >   http://sources.redhat.com/ml/gdb/2002-01/msg00359.html
 > 
 > In this you state that you had been fixing some problems. Do you know 
 > anything about gdb's present support for complex values?
 
 GDB is fine; GCC is broken.  You'll find that in recent GCC and GDB
 DWARF-2 will work fine.  Stabs will fail; the debugging output from GCC
 is inconsistent.
 
 Someone should probably fix it to use the Sun notation for such
 variables (i.e. "R" instead of "r", IIRC).
 
 -- 
 Daniel Jacobowitz
 MontaVista Software                         Debian GNU/Linux Developer


^ permalink raw reply	[flat|nested] 15+ messages in thread

* Re: debug/1621: Debugging with complex numbers
@ 2002-12-05 16:16 Wolfgang Bangerth
  0 siblings, 0 replies; 15+ messages in thread
From: Wolfgang Bangerth @ 2002-12-05 16:16 UTC (permalink / raw)
  To: nobody; +Cc: gcc-prs

The following reply was made to PR debug/1621; it has been noted by GNATS.

From: Wolfgang Bangerth <bangerth@ticam.utexas.edu>
To: "Joseph S. Myers" <jsm28@cam.ac.uk>
Cc: bangerth@dealii.org, <gcc-bugs@gcc.gnu.org>, <gcc-gnats@gcc.gnu.org>,
   <drow@mvista.com>
Subject: Re: debug/1621: Debugging with complex numbers
Date: Thu, 5 Dec 2002 18:09:46 -0600 (CST)

 > >     Joseph, this report is now almost 2 years old, and versions
 > >     3.0 and 3.1/2 have happened in between. Unfortunately, there
 > >     are no testcases in the report, so I can't check the claims
 > >     myself, but do you know whether the situation has or has
 > >     not improved in the meantime?
 > 
 > The testcase is at the URL given in the report 
 > <http://gcc.gnu.org/ml/gcc/2000-12/msg00536.html>:
 
 Oh, sorry, I seem to have overlooked this. 
 
 
 >         static __complex__ double x = 2.0 + 3.0i;
 >         int main(void)
 >         {
 >           return 0;
 >         }
 > 
 > (gdb) p x
 > $1 = Invalid C/C++ type code 20 in symbol table.
 > (gdb) p x$real
 > No symbol "x$real" in current context.
 > (gdb) p x$imag
 > No symbol "x$imag" in current context.
 
 This is also the behavior I get, using 3.3CVS and gdb5.1.1. For some 
 reason, I cannot get gdb CVS compiled, so can't check whether it works 
 now. The gdb error message indicates that gcc is doing something but gdb 
 isn't understanding it.
 
 Daniel, I'm CC:ing you since you wrote the latest mail I could find on the 
 gdb mailing lists that is about complex value support 
   http://sources.redhat.com/ml/gdb/2002-01/msg00359.html
 
 In this you state that you had been fixing some problems. Do you know 
 anything about gdb's present support for complex values?
 
 
 > Some of the problem, if still there, may be a GDB problem, some may be a
 > GCC problem.  But as long as the manual is making claims about what GDB
 > will do in future, the presence of such claims in the manual is a GCC
 > problem unless there's some reason to suppose them to be accurate.
 
 Agreed.
 
 Regards
   Wolfgang
 
 -------------------------------------------------------------------------
 Wolfgang Bangerth              email:           bangerth@ticam.utexas.edu
                                www: http://www.ticam.utexas.edu/~bangerth
 
 


^ permalink raw reply	[flat|nested] 15+ messages in thread

* Re: debug/1621: Debugging with complex numbers
@ 2002-12-05 15:26 Joseph S. Myers
  0 siblings, 0 replies; 15+ messages in thread
From: Joseph S. Myers @ 2002-12-05 15:26 UTC (permalink / raw)
  To: nobody; +Cc: gcc-prs

The following reply was made to PR debug/1621; it has been noted by GNATS.

From: "Joseph S. Myers" <jsm28@cam.ac.uk>
To: <bangerth@dealii.org>,  <gcc-bugs@gcc.gnu.org>,  <gcc-gnats@gcc.gnu.org>
Cc:  
Subject: Re: debug/1621: Debugging with complex numbers
Date: Thu, 5 Dec 2002 23:24:36 +0000 (GMT)

 On 5 Dec 2002 bangerth@dealii.org wrote:
 
 >     Joseph, this report is now almost 2 years old, and versions
 >     3.0 and 3.1/2 have happened in between. Unfortunately, there
 >     are no testcases in the report, so I can't check the claims
 >     myself, but do you know whether the situation has or has
 >     not improved in the meantime?
 
 The testcase is at the URL given in the report 
 <http://gcc.gnu.org/ml/gcc/2000-12/msg00536.html>:
 
         static __complex__ double x = 2.0 + 3.0i;
         int main(void)
         {
           return 0;
         }
 
 (gdb) p x
 $1 = Invalid C/C++ type code 20 in symbol table.
 (gdb) p x$real
 No symbol "x$real" in current context.
 (gdb) p x$imag
 No symbol "x$imag" in current context.
 (gdb) quit
 
 You'll also want to try a testcase with automatic variables:
 
 	int main(void)
 	{
 	  __complex__double x = 2.0 + 3.0i;
 	  return 0;
 	}
 
 Both testcases should be tried with both stabs and DWARF2 debugging.  The 
 key part is that accessing the variable as a whole from GDB ought to work; 
 if that works in all four cases, then the manual need no longer refer to 
 "A future version of GDB", just say that GDB can handle debugging complex 
 numbers (possibly keeping the description of what's done with stabs as 
 information about the internals rather than the user interface).
 
 Some of the problem, if still there, may be a GDB problem, some may be a
 GCC problem.  But as long as the manual is making claims about what GDB
 will do in future, the presence of such claims in the manual is a GCC
 problem unless there's some reason to suppose them to be accurate.
 
 (DWARF3 has support for complex floating point numbers, but not complex
 integers which aren't in C99.  I don't really care about debugging for
 complex integers in any case, which have other known problems (division of
 complex integers doesn't work sensibly in GCC).)
 
 -- 
 Joseph S. Myers
 jsm28@cam.ac.uk
 


^ permalink raw reply	[flat|nested] 15+ messages in thread

* debug/1621: Debugging with complex numbers
@ 2001-04-01  0:00 Joseph Myers
  0 siblings, 0 replies; 15+ messages in thread
From: Joseph Myers @ 2001-04-01  0:00 UTC (permalink / raw)
  To: gcc-gnats; +Cc: jsm28

>Number:         1621
>Category:       debug
>Synopsis:       Debugging with complex numbers
>Confidential:   no
>Severity:       non-critical
>Priority:       medium
>Responsible:    unassigned
>State:          open
>Class:          sw-bug
>Submitter-Id:   net
>Arrival-Date:   Thu Jan 11 11:06:01 PST 2001
>Closed-Date:
>Last-Modified:
>Originator:     Joseph S. Myers
>Release:        2.97 20010110 (experimental)
>Organization:
none
>Environment:
System: Linux decomino 2.2.18 #1 Sun Jan 7 21:04:55 UTC 2001 i686 unknown
Architecture: i686

	
host: i686-pc-linux-gnu
build: i686-pc-linux-gnu
target: i686-pc-linux-gnu
configured with: ../gcc-cvs/configure --prefix=/opt/gcc/snapshot --disable-shared --enable-threads=posix --with-system-zlib
>Description:

Debugging with complex numbers is fairly broken.  Some coordination
with GDB may be needed.

>How-To-Repeat:

See <URL: http://gcc.gnu.org/ml/gcc/2000-12/msg00536.html >.

>Fix:

At the very least, GCC should not make claims about future versions of
GDB and leave such claims in the manual for years without some
coordination to make the claims become true.  Properly, full support
for debugging with complex numbers should be coordinated with GDB -
GCC should emit correct stabs/DWARF-2 information, and document the
required GDB version, and GDB should understand the information.
>Release-Note:
>Audit-Trail:
>Unformatted:
>From paul@dawa.demon.co.uk Sun Apr 01 00:00:00 2001
From: Paul Flinders <paul@dawa.demon.co.uk>
To: tromey@gcc.gnu.org
Cc: gcc-prs@gcc.gnu.org
Subject: Re: libgcj/1906
Date: Sun, 01 Apr 2001 00:00:00 -0000
Message-id: <20010208215601.32661.qmail@sourceware.cygnus.com>
X-SW-Source: 2001-q1/msg01080.html
Content-length: 672

The following reply was made to PR libgcj/1906; it has been noted by GNATS.

From: Paul Flinders <paul@dawa.demon.co.uk>
To: tromey@gcc.gnu.org
Cc: gcc-gnats@gcc.gnu.org, nobody@gcc.gnu.org
Subject: Re: libgcj/1906
Date: Thu, 8 Feb 2001 21:54:53 +0000 (GMT)

 tromey@gcc.gnu.org writes:
  > Synopsis: difference between gcj and jdk for MessageFormat
  > 
  > Responsible-Changed-From-To: unassigned->tromey
  > Responsible-Changed-By: tromey
  > Responsible-Changed-When: Wed Feb  7 14:41:14 2001
  > Responsible-Changed-Why:
  >     I'm working on this.
  > 
  > http://gcc.gnu.org/cgi-bin/gnatsweb.pl?cmd=view&pr=1906&database=gcc
 
 Current CVS version of gcj seems OK
>From a.sanders@mcc.ac.uk Sun Apr 01 00:00:00 2001
From: a.sanders@mcc.ac.uk
To: gcc-gnats@gcc.gnu.org
Subject: c++/1680: Internal compiler error.
Date: Sun, 01 Apr 2001 00:00:00 -0000
Message-id: <20010117122420.11440.qmail@sourceware.cygnus.com>
X-SW-Source: 2001-q1/msg00410.html
Content-length: 204585

>Number:         1680
>Category:       c++
>Synopsis:       Internal compiler error.
>Confidential:   no
>Severity:       serious
>Priority:       medium
>Responsible:    unassigned
>State:          open
>Class:          sw-bug
>Submitter-Id:   net
>Arrival-Date:   Wed Jan 17 04:25:59 PST 2001
>Closed-Date:
>Last-Modified:
>Originator:     Ashley Sanders
>Release:        unknown-1.0
>Organization:
>Environment:

>Description:
$ g++ -v
Reading specs from /usr/local/lib/gcc-lib/sparc-sun-solaris2.6/2.95.1/specs
gcc version 2.95.1 19990816 (release)

$ g++ -ansi -Wall -g -DNO_OSI -D_REENTRANT -I. -I/home/copdev/include/stlport -I/home/copdev/include -I/usr/openwin/share/include   -c -o to-record.o to-record.cc
In file included from /home/copdev/include/boost/re_detail/regex_config.hpp:51,
                 from /home/copdev/include/boost/cregex.hpp:27,
                 from /home/copdev/include/boost/regex.hpp:31,
                 from to-record.cc:16:
/home/copdev/include/boost/smart_ptr.hpp:232: Internal compiler error.
/home/copdev/include/boost/smart_ptr.hpp:232: Please submit a full bug report.
/home/copdev/include/boost/smart_ptr.hpp:232: See <URL: http://www.gnu.org/software/gcc/faq.html#bugreport > for instructions.

using stlport 4.0 and boost 1.20.1
www.stlport.org, www.boost.org
>How-To-Repeat:

>Fix:

>Release-Note:
>Audit-Trail:
>Unformatted:
----gnatsweb-attachment----
Content-Type: application/octet-stream; name="to-record.ii.gz"
Content-Transfer-Encoding: base64
Content-Disposition: attachment; filename="to-record.ii.gz"
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>From nathan@gcc.gnu.org Sun Apr 01 00:00:00 2001
From: nathan@gcc.gnu.org
To: nathan@gcc.gnu.org
Cc: gcc-prs@gcc.gnu.org
Subject: Re: c++/1588
Date: Sun, 01 Apr 2001 00:00:00 -0000
Message-id: <20010111113602.16745.qmail@sourceware.cygnus.com>
X-SW-Source: 2001-q1/msg00195.html
Content-length: 594

The following reply was made to PR c++/1588; it has been noted by GNATS.

From: nathan@gcc.gnu.org
To: Hugues.Talbot@cmis.CSIRO.AU, gcc-gnats@gcc.gnu.org, nathan@gcc.gnu.org,
  nobody@gcc.gnu.org
Cc:  
Subject: Re: c++/1588
Date: 11 Jan 2001 11:34:43 -0000

 Synopsis: 2.95.2 (and later) Internal compiler error on template instantiation
 
 Responsible-Changed-From-To: unassigned->nathan
 Responsible-Changed-By: nathan
 Responsible-Changed-When: Thu Jan 11 03:34:43 2001
 Responsible-Changed-Why:
     patch in progress
 
 http://gcc.gnu.org/cgi-bin/gnatsweb.pl?cmd=view&pr=1588&database=gcc
>From kelley.cook@home.com Sun Apr 01 00:00:00 2001
From: kelley.cook@home.com
To: gcc-gnats@gcc.gnu.org
Subject: c++/1687: Extreme compile time regression from 2.95.2
Date: Sun, 01 Apr 2001 00:00:00 -0000
Message-id: <20010117200012.25234.qmail@sourceware.cygnus.com>
X-SW-Source: 2001-q1/msg00423.html
Content-length: 3727

>Number:         1687
>Category:       c++
>Synopsis:       Extreme compile time regression from 2.95.2
>Confidential:   no
>Severity:       non-critical
>Priority:       medium
>Responsible:    unassigned
>State:          open
>Class:          sw-bug
>Submitter-Id:   net
>Arrival-Date:   Wed Jan 17 12:06:00 PST 2001
>Closed-Date:
>Last-Modified:
>Originator:     Kelley Cook
>Release:        gcc version 2.97 20010115 (experimental)
>Organization:
>Environment:
CYGWIN_NT-5.0 KELLEY 1.1.7(0.31/3/2) 2000-12-25 12:39 i686 unknown
>Description:
This simple program takes has been compiling for well over a day when optimization is enabled.  This is on a 500Mhz PIII.

The same file compilied with optimization under C instead of C++ compiles in under a second.  Ditto for either C or C++ under GCC 2.95.2.

A 16-bit version of the same program, was semi-corrected earlier, but only in the non-optimized version.  See http://gcc.gnu.org/ml/gcc-bugs/2000-08/msg00684.html

That original test case still takes about 1 minute when compiled with -O.  Since a little checking shows that the time approximately doubles with each bit added, I am spectulating that this would take 6 weeks to compile.  A 64 bit version would take a half-billion years.
>How-To-Repeat:
gcc -O mux32.cc
>Fix:

>Release-Note:
>Audit-Trail:
>Unformatted:
----gnatsweb-attachment----
Content-Type: unknown; name="mux32.cc"
Content-Transfer-Encoding: base64
Content-Disposition: attachment; filename="mux32.cc"
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>From schreib@stoch.fmi.uni-passau.de Sun Apr 01 00:00:00 2001
From: schreib@stoch.fmi.uni-passau.de
To: gcc-gnats@gcc.gnu.org
Subject: c++/2057: bug in global "const" array
Date: Sun, 01 Apr 2001 00:00:00 -0000
Message-id: <20010222080500.15064.qmail@sourceware.cygnus.com>
X-SW-Source: 2001-q1/msg01580.html
Content-length: 921

>Number:         2057
>Category:       c++
>Synopsis:       bug in global "const" array
>Confidential:   no
>Severity:       critical
>Priority:       medium
>Responsible:    unassigned
>State:          open
>Class:          wrong-code
>Submitter-Id:   net
>Arrival-Date:   Thu Feb 22 00:06:01 PST 2001
>Closed-Date:
>Last-Modified:
>Originator:     schreib@stoch.fmi.uni-passau.de
>Release:        gcc version 2.95.2 19991024 (release)
>Organization:
>Environment:
SuSE 6.4/Linux kernel 2.2.14
>Description:
Programm:
#include <iostream>
Output of the program below:
A=1
B=0

Output of program if we remove "const" before "B":
A=1
B=1
>How-To-Repeat:
#include <iostream>
const int A[1] = { 1 };
// const or not const ?
const
int B[1][1] = { { A[0] } };

int main()
{
  std::cout << "A=" << A[0] << std::endl;
  std::cout << "B=" << B[0][0] << std::endl;
  return(0);
}
>Fix:

>Release-Note:
>Audit-Trail:
>Unformatted:


^ permalink raw reply	[flat|nested] 15+ messages in thread

end of thread, other threads:[~2002-12-28 18:59 UTC | newest]

Thread overview: 15+ messages (download: mbox.gz / follow: Atom feed)
-- links below jump to the message on this page --
2002-12-05 12:09 debug/1621: Debugging with complex numbers bangerth
  -- strict thread matches above, loose matches on Subject: below --
2002-12-28 10:59 jsm28
2002-12-13 11:26 Joseph S. Myers
2002-12-13  9:32 wilson
2002-12-12 14:16 Jim Wilson
2002-12-12 13:36 Jim Wilson
2002-12-12 11:56 Daniel Jacobowitz
2002-12-12  7:56 Jim Wilson
2002-12-11 17:26 Daniel Jacobowitz
2002-12-11 16:16 Jim Wilson
2002-12-09 12:24 bangerth
2002-12-07 17:26 Daniel Jacobowitz
2002-12-05 16:16 Wolfgang Bangerth
2002-12-05 15:26 Joseph S. Myers
2001-04-01  0:00 Joseph Myers

This is a public inbox, see mirroring instructions
for how to clone and mirror all data and code used for this inbox;
as well as URLs for read-only IMAP folder(s) and NNTP newsgroup(s).