[Bug libstdc++/12048] New: Problems with IOStreams

public inbox for gcc-bugs@sourceware.org
help / color / mirror / Atom feed

* [Bug libstdc++/12048] New: Problems with IOStreams
@ 2003-08-25  3:55 gcc-bugzilla at gcc dot gnu dot org
  2003-08-25  4:14 ` [Bug libstdc++/12048] [3.4 Regression] unget does not work pinskia at gcc dot gnu dot org
                   ` (6 more replies)
  0 siblings, 7 replies; 8+ messages in thread
From: gcc-bugzilla at gcc dot gnu dot org @ 2003-08-25  3:55 UTC (permalink / raw)
  To: gcc-bugs

PLEASE REPLY TO gcc-bugzilla@gcc.gnu.org ONLY, *NOT* gcc-bugs@gcc.gnu.org.

http://gcc.gnu.org/bugzilla/show_bug.cgi?id=12048

           Summary: Problems with IOStreams
           Product: gcc
           Version: 3.4
            Status: UNCONFIRMED
          Severity: normal
          Priority: P3
         Component: libstdc++
        AssignedTo: unassigned at gcc dot gnu dot org
        ReportedBy: poschmid at peem dot als dot lbl dot gov
                CC: gcc-bugs at gcc dot gnu dot org
 GCC build triplet: i686-pc-linux-gnu
  GCC host triplet: i686-pc-linux-gnu
GCC target triplet: i686-pc-linux-gnu

When I run the binary generated by compiling the source file t.C with gcc 3.4
I get an unexpected result. I believe it should print harriet 85 95, when
run. This is the output when the code is compiled by gcc 3.3. The example is
extracted from the file main2.cc from Chapter12 of the book Accelerated C++:
Practical Programming by Example by Andrew Koenig and Barbara E. Moo.

Environment:
System: Linux kiste 2.4.20-4GB #1 Fri Jul 11 07:33:18 UTC 2003 i686 unknown unknown GNU/Linux
Architecture: i686
SuSE 8.2
glibc 2.3.2	
host: i686-pc-linux-gnu
build: i686-pc-linux-gnu
target: i686-pc-linux-gnu
configured with: ../gcc/configure --enable-threads=posix --enable-languages=c,c++,f77,objc --enable-__cxa_atexit --enable-libstdcxx-debug

How-To-Repeat:
source code t.C
#include <iostream>
#include <algorithm>
#include <cstring>
#include <cstddef>
#include <memory>
#include <iterator>

using std::max;
using std::istream;
using std::istream_iterator;
using std::ostream;
using std::cin;
using std::cout;
using std::istream;

template <class T> class Vec {
public:
	typedef T* iterator;
	typedef const T* const_iterator;
	typedef size_t size_type;
	typedef T value_type;
	typedef T& reference;
	typedef const T& const_reference;

	Vec() { create(); }
	explicit Vec(size_type n, const T& t = T()) { create(n, t); }

	Vec(const Vec& v) { create(v.begin(), v.end()); }
	Vec& operator=(const Vec&);
	~Vec() { uncreate(); }

	T& operator[](size_type i) { return data[i]; }
	const T& operator[](size_type i) const { return data[i]; }

	void push_back(const T& t) {
		if (avail == limit)
			grow();
		unchecked_append(t);
	}

	size_type size() const { return avail - data; }

	iterator begin() { return data; }
	const_iterator begin() const { return data; }

	iterator end() { return avail; }
	const_iterator end() const { return avail; }
	void clear() { uncreate(); }
	bool empty() const { return data == avail; }

private:
	iterator data;	
	iterator avail;
	iterator limit;
	std::allocator<T> alloc;
	void create();
	void create(size_type, const T&);
	void create(const_iterator, const_iterator);
	void uncreate();
	void grow();
	void unchecked_append(const T&);
};

template <class T> void Vec<T>::create()
{
	data = avail = limit = 0;
}

template <class T> void Vec<T>::create(size_type n, const T& val)
{
	data = alloc.allocate(n);
	limit = avail = data + n;
	std::uninitialized_fill(data, limit, val);
}

template <class T>
void Vec<T>::create(const_iterator i, const_iterator j)
{
	data = alloc.allocate(j - i);
	limit = avail = std::uninitialized_copy(i, j, data);
}

template <class T> void Vec<T>::uncreate()
{
	if (data) {
		iterator it = avail;
		while (it != data)
			alloc.destroy(--it);
		alloc.deallocate(data, limit - data);
	}
	data = limit = avail = 0;
}

template <class T> void Vec<T>::grow()
{
	size_type new_size = max(2 * (limit - data), ptrdiff_t(1));

	iterator new_data = alloc.allocate(new_size);
	iterator new_avail = std::uninitialized_copy(data, avail, new_data);

	uncreate();
	data = new_data;
	avail = new_avail;
	limit = data + new_size;
}

template <class T> void Vec<T>::unchecked_append(const T& val)
{
	alloc.construct(avail++, val);
}

template <class T>
Vec<T>& Vec<T>::operator=(const Vec& rhs)
{
	if (&rhs != this) {
		uncreate();
		create(rhs.begin(), rhs.end());
	}
	return *this;
}

class Str {
	friend std::istream& operator>>(std::istream&, Str&);
public:
	typedef Vec<char>::size_type size_type;

	Str() { }
	Str(size_type n, char c): data(n, c) { }

	char& operator[](size_type i) { return data[i]; }
	const char& operator[](size_type i) const { return data[i]; }
	size_type size() const { return data.size(); }

private:
	Vec<char> data;
};

ostream& operator<<(ostream& os, const Str& s)
{
	for (Str::size_type i = 0; i != s.size(); ++i)
		os << s[i];
	return os;
}

istream& operator>>(istream& is, Str& s)
{
	s.data.clear();
	char c;
	while (is.get(c) && isspace(c))
		;
	if (is) {
		do	s.data.push_back(c);     
		while (is.get(c) && !isspace(c));

		if (is)
			is.unget();
	}

	return is;
}

struct Student_info {
	Str name;
	double midterm, final;
};

istream& read(istream& is, Student_info& s)
{
	is >> s.name >> s.midterm >> s.final;
	cout << s.name << ' ' << s.midterm << ' ' << s.final;
	return is;
}

int main()
{
 	Student_info record;
 	read(cin, record);
}

g++ -v -W -Wall t.C -save-temps 
Reading specs from /usr/local/lib/gcc/i686-pc-linux-gnu/3.4/specs
Configured with: ../gcc/configure --enable-threads=posix --enable-languages=c,c++,f77,objc --enable-__cxa_atexit --enable-libstdcxx-debug
Thread model: posix
gcc version 3.4 20030820 (experimental)
 /usr/local/libexec/gcc/i686-pc-linux-gnu/3.4/cc1plus -E -quiet -v -D_GNU_SOURCE t.C -mtune=pentiumpro -W -Wall -o t.ii
ignoring nonexistent directory "NONE/include"
ignoring nonexistent directory "/usr/local/lib/gcc/i686-pc-linux-gnu/3.4/../../../../i686-pc-linux-gnu/include"
#include "..." search starts here:
#include <...> search starts here:
 /usr/local/lib/gcc/i686-pc-linux-gnu/3.4/../../../../include/c++/3.4
 /usr/local/lib/gcc/i686-pc-linux-gnu/3.4/../../../../include/c++/3.4/i686-pc-linux-gnu
 /usr/local/lib/gcc/i686-pc-linux-gnu/3.4/../../../../include/c++/3.4/backward
 /usr/local/include
 /usr/local/lib/gcc/i686-pc-linux-gnu/3.4/include
 /usr/include
End of search list.
 /usr/local/libexec/gcc/i686-pc-linux-gnu/3.4/cc1plus -fpreprocessed t.ii -quiet -dumpbase t.C -mtune=pentiumpro -auxbase t -W -Wall -version -o t.s
GNU C++ version 3.4 20030820 (experimental) (i686-pc-linux-gnu)
	compiled by GNU C version 3.4 20030820 (experimental).
GGC heuristics: --param ggc-min-expand=47 --param ggc-min-heapsize=31899
 as -V -Qy -o t.o t.s
GNU assembler version 2.13.90.0.18 (i486-suse-linux) using BFD version 2.13.90.0.18 20030121 (SuSE Linux)
 /usr/local/libexec/gcc/i686-pc-linux-gnu/3.4/collect2 --eh-frame-hdr -m elf_i386 -dynamic-linker /lib/ld-linux.so.2 /usr/lib/crt1.o /usr/lib/crti.o /usr/local/lib/gcc/i686-pc-linux-gnu/3.4/crtbegin.o -L/usr/local/lib/gcc/i686-pc-linux-gnu/3.4 -L/usr/local/lib/gcc/i686-pc-linux-gnu/3.4/../../.. t.o -lstdc++ -lm -lgcc_s -lgcc -lc -lgcc_s -lgcc /usr/local/lib/gcc/i686-pc-linux-gnu/3.4/crtend.o /usr/lib/crtn.o

cat single_grade
harriet 85 95 88 87 93 45 76 99
./a.out < single_grade
harriet -1.99759 4.86587e-270

gcc 3.3
/a.out < single_grade
harriet 85 95

preprocessed source file
Content-Type: APPLICATION/x-bzip2; name="t.ii.bz2"
Content-Transfer-Encoding: BASE64
Content-ID: <Pine.LNX.4.53.0308241743370.19564@kiste.local>
Content-Description: t.ii.bz2
Content-Disposition: attachment; filename="t.ii.bz2"
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--8323584-333546674-1061772217=:19564--


^ permalink raw reply	[flat|nested] 8+ messages in thread

* [Bug libstdc++/12048] [3.4 Regression] unget does not work
  2003-08-25  3:55 [Bug libstdc++/12048] New: Problems with IOStreams gcc-bugzilla at gcc dot gnu dot org
@ 2003-08-25  4:14 ` pinskia at gcc dot gnu dot org
  2003-08-26  7:05 ` rittle at latour dot rsch dot comm dot mot dot com
                   ` (5 subsequent siblings)
  6 siblings, 0 replies; 8+ messages in thread
From: pinskia at gcc dot gnu dot org @ 2003-08-25  4:14 UTC (permalink / raw)
  To: gcc-bugs

PLEASE REPLY TO gcc-bugzilla@gcc.gnu.org ONLY, *NOT* gcc-bugs@gcc.gnu.org.

http://gcc.gnu.org/bugzilla/show_bug.cgi?id=12048


pinskia at gcc dot gnu dot org changed:

           What    |Removed                     |Added
----------------------------------------------------------------------------
           Severity|normal                      |critical
             Status|UNCONFIRMED                 |NEW
     Ever Confirmed|                            |1
   Last reconfirmed|0000-00-00 00:00:00         |2003-08-25 04:14:11
               date|                            |
            Summary|Problems with IOStreams     |[3.4 Regression] unget does
                   |                            |not work
   Target Milestone|---                         |3.4


------- Additional Comments From pinskia at gcc dot gnu dot org  2003-08-25 04:14 -------
I can confirm this on the mainline (20030823), this worked in 3.3 so this is a regression.
Here is a reduced case as it looks like unget is not working:
#include <iostream>
int main()
{
char c,c1;
std::cin.get(c);
std::cin.unget();
std::cin.get(c1);
if(c1!=c)
abort();
}


^ permalink raw reply	[flat|nested] 8+ messages in thread

* [Bug libstdc++/12048] [3.4 Regression] unget does not work
  2003-08-25  3:55 [Bug libstdc++/12048] New: Problems with IOStreams gcc-bugzilla at gcc dot gnu dot org
  2003-08-25  4:14 ` [Bug libstdc++/12048] [3.4 Regression] unget does not work pinskia at gcc dot gnu dot org
@ 2003-08-26  7:05 ` rittle at latour dot rsch dot comm dot mot dot com
  2003-08-26  8:13 ` peturr02 at ru dot is
                   ` (4 subsequent siblings)
  6 siblings, 0 replies; 8+ messages in thread
From: rittle at latour dot rsch dot comm dot mot dot com @ 2003-08-26  7:05 UTC (permalink / raw)
  To: gcc-bugs

PLEASE REPLY TO gcc-bugzilla@gcc.gnu.org ONLY, *NOT* gcc-bugs@gcc.gnu.org.

http://gcc.gnu.org/bugzilla/show_bug.cgi?id=12048



------- Additional Comments From rittle at latour dot rsch dot comm dot mot dot com  2003-08-26 07:05 -------
Subject: Re:  [3.4 Regression] unget does not work

(Independently arrived at this, thus I concur with the rename
 and critical upgrade...)

#include <iostream>
#include <testsuite_hooks.h>

// Derived from libstdc++/12048 by LJR.  Exercise for the reader to
// figure out how to get this interactive test into our dejagnu...
// Rewriting the test to use an opened fstream displays no failure...

int main()
{
  bool test = true;
  char c1;
  char c2;
  std::cin.get(c1);
  std::cin.unget();
  std::cin.get(c2);
  VERIFY (c1 == c2);
}


^ permalink raw reply	[flat|nested] 8+ messages in thread

* [Bug libstdc++/12048] [3.4 Regression] unget does not work
  2003-08-25  3:55 [Bug libstdc++/12048] New: Problems with IOStreams gcc-bugzilla at gcc dot gnu dot org
  2003-08-25  4:14 ` [Bug libstdc++/12048] [3.4 Regression] unget does not work pinskia at gcc dot gnu dot org
  2003-08-26  7:05 ` rittle at latour dot rsch dot comm dot mot dot com
@ 2003-08-26  8:13 ` peturr02 at ru dot is
  2003-08-26 10:05 ` peturr02 at ru dot is
                   ` (3 subsequent siblings)
  6 siblings, 0 replies; 8+ messages in thread
From: peturr02 at ru dot is @ 2003-08-26  8:13 UTC (permalink / raw)
  To: gcc-bugs

PLEASE REPLY TO gcc-bugzilla@gcc.gnu.org ONLY, *NOT* gcc-bugs@gcc.gnu.org.

http://gcc.gnu.org/bugzilla/show_bug.cgi?id=12048



------- Additional Comments From peturr02 at ru dot is  2003-08-26 08:13 -------
This is a result of my patch:

http://gcc.gnu.org/ml/libstdc++/2003-05/msg00013.html
http://gcc.gnu.org/ml/libstdc++/2003-05/msg00040.html


^ permalink raw reply	[flat|nested] 8+ messages in thread

* [Bug libstdc++/12048] [3.4 Regression] unget does not work
  2003-08-25  3:55 [Bug libstdc++/12048] New: Problems with IOStreams gcc-bugzilla at gcc dot gnu dot org
                   ` (2 preceding siblings ...)
  2003-08-26  8:13 ` peturr02 at ru dot is
@ 2003-08-26 10:05 ` peturr02 at ru dot is
  2003-09-03 14:54 ` cvs-commit at gcc dot gnu dot org
                   ` (2 subsequent siblings)
  6 siblings, 0 replies; 8+ messages in thread
From: peturr02 at ru dot is @ 2003-08-26 10:05 UTC (permalink / raw)
  To: gcc-bugs

PLEASE REPLY TO gcc-bugzilla@gcc.gnu.org ONLY, *NOT* gcc-bugs@gcc.gnu.org.

http://gcc.gnu.org/bugzilla/show_bug.cgi?id=12048



------- Additional Comments From peturr02 at ru dot is  2003-08-26 10:05 -------
> // Derived from libstdc++/12048 by LJR.  Exercise for the reader to
> // figure out how to get this interactive test into our dejagnu...

The easiest way is to reopen stdin using either freopen or open + dup2.

> // Rewriting the test to use an opened fstream displays no failure...

That's not surprising, since cin is unrelated to fstream.


^ permalink raw reply	[flat|nested] 8+ messages in thread

* [Bug libstdc++/12048] [3.4 Regression] unget does not work
  2003-08-25  3:55 [Bug libstdc++/12048] New: Problems with IOStreams gcc-bugzilla at gcc dot gnu dot org
                   ` (3 preceding siblings ...)
  2003-08-26 10:05 ` peturr02 at ru dot is
@ 2003-09-03 14:54 ` cvs-commit at gcc dot gnu dot org
  2003-09-03 14:57 ` cvs-commit at gcc dot gnu dot org
  2003-09-03 16:23 ` pinskia at gcc dot gnu dot org
  6 siblings, 0 replies; 8+ messages in thread
From: cvs-commit at gcc dot gnu dot org @ 2003-09-03 14:54 UTC (permalink / raw)
  To: gcc-bugs

PLEASE REPLY TO gcc-bugzilla@gcc.gnu.org ONLY, *NOT* gcc-bugs@gcc.gnu.org.

http://gcc.gnu.org/bugzilla/show_bug.cgi?id=12048



------- Additional Comments From cvs-commit at gcc dot gnu dot org  2003-09-03 14:54 -------
Subject: Bug 12048

CVSROOT:	/cvs/gcc
Module name:	gcc
Changes by:	bkoz@gcc.gnu.org	2003-09-03 14:54:04

Modified files:
	libstdc++-v3   : ChangeLog 
	libstdc++-v3/docs/html/27_io: howto.html 
	libstdc++-v3/include/ext: stdio_sync_filebuf.h 
	libstdc++-v3/testsuite/ext: stdio_sync_filebuf_char.cc 
	                            stdio_sync_filebuf_wchar_t.cc 

Log message:
	2003-09-03  Petur Runolfsson  <peturr02@ru.is>
	
	PR libstdc++/12048
	* include/ext/stdio_sync_filebuf.h
	(stdio_sync_filebuf::_M_unget_buf): Declare it.
	(stdio_sync_filebuf::stdio_sync_filebuf): Initialize _M_unget_buf.
	(stdio_sync_filebuf::uflow): Store the returned character in
	_M_unget_buf.
	(stdio_sync_filebuf::pbackfail): If argument is eof(), pass
	_M_unget_buf to syncungetc(). Set _M_unget_buf to eof().
	(stdio_sync_filebuf<char>::xsgetn): Store last read character in
	_M_unget_buf, if any, else eof().
	(stdio_sync_filebuf<wchar_t>::xsgetn: Store last read character in
	_M_unget_buf, if any, else eof().
	* testsuite/27_io/objects/char/12048.cc: Rename to...
	* testsuite/27_io/objects/char/12048-1.cc: ...this.
	* testsuite/27_io/objects/char/12048-2.cc: New test.
	* testsuite/27_io/objects/char/12048-3.cc: New test.
	* testsuite/27_io/objects/char/12048-4.cc: New test.
	* testsuite/27_io/objects/char/12048-5.cc: New test. XFAIL.
	* testsuite/27_io/objects/wchar_t/12048-1.cc: New test.
	* testsuite/27_io/objects/wchar_t/12048-2.cc: New test.
	* testsuite/27_io/objects/wchar_t/12048-3.cc: New test.
	* testsuite/27_io/objects/wchar_t/12048-4.cc: New test.
	* testsuite/27_io/objects/wchar_t/12048-5.cc: New test. XFAIL.
	* testsuite/ext/stdio_sync_filebuf_char.cc
	(test02, test03, test04, test05): New tests.
	* testsuite/ext/stdio_sync_filebuf_wchar_t.cc
	(test02, test03, test04, test05): New tests.
	
	2003-09-03  Petur Runolfsson  <peturr02@ru.is>
	
	* docs/html/27_io/howto.html: setbuf(0, 0) has no effect on
	stringbuf or strstreambuf. Fix typos.

Patches:
http://gcc.gnu.org/cgi-bin/cvsweb.cgi/gcc/libstdc++-v3/ChangeLog.diff?cvsroot=gcc&r1=1.1948&r2=1.1949
http://gcc.gnu.org/cgi-bin/cvsweb.cgi/gcc/libstdc++-v3/docs/html/27_io/howto.html.diff?cvsroot=gcc&r1=1.26&r2=1.27
http://gcc.gnu.org/cgi-bin/cvsweb.cgi/gcc/libstdc++-v3/include/ext/stdio_sync_filebuf.h.diff?cvsroot=gcc&r1=1.3&r2=1.4
http://gcc.gnu.org/cgi-bin/cvsweb.cgi/gcc/libstdc++-v3/testsuite/ext/stdio_sync_filebuf_char.cc.diff?cvsroot=gcc&r1=1.1&r2=1.2
http://gcc.gnu.org/cgi-bin/cvsweb.cgi/gcc/libstdc++-v3/testsuite/ext/stdio_sync_filebuf_wchar_t.cc.diff?cvsroot=gcc&r1=1.1&r2=1.2


^ permalink raw reply	[flat|nested] 8+ messages in thread

* [Bug libstdc++/12048] [3.4 Regression] unget does not work
  2003-08-25  3:55 [Bug libstdc++/12048] New: Problems with IOStreams gcc-bugzilla at gcc dot gnu dot org
                   ` (4 preceding siblings ...)
  2003-09-03 14:54 ` cvs-commit at gcc dot gnu dot org
@ 2003-09-03 14:57 ` cvs-commit at gcc dot gnu dot org
  2003-09-03 16:23 ` pinskia at gcc dot gnu dot org
  6 siblings, 0 replies; 8+ messages in thread
From: cvs-commit at gcc dot gnu dot org @ 2003-09-03 14:57 UTC (permalink / raw)
  To: gcc-bugs

PLEASE REPLY TO gcc-bugzilla@gcc.gnu.org ONLY, *NOT* gcc-bugs@gcc.gnu.org.

http://gcc.gnu.org/bugzilla/show_bug.cgi?id=12048



------- Additional Comments From cvs-commit at gcc dot gnu dot org  2003-09-03 14:57 -------
Subject: Bug 12048

CVSROOT:	/cvs/gcc
Module name:	gcc
Changes by:	bkoz@gcc.gnu.org	2003-09-03 14:57:05

Added files:
	libstdc++-v3/testsuite/27_io/objects/char: 12048-1.cc 12048-2.cc 
	                                           12048-3.cc 12048-4.cc 
	                                           12048-5.cc 
	libstdc++-v3/testsuite/27_io/objects/wchar_t: 12048-1.cc 
	                                              12048-2.cc 
	                                              12048-3.cc 
	                                              12048-4.cc 
	                                              12048-5.cc 
Removed files:
	libstdc++-v3/testsuite/27_io/objects/char: 12048.cc 

Log message:
	2003-09-03  Petur Runolfsson  <peturr02@ru.is>
	
	PR libstdc++/12048
	* include/ext/stdio_sync_filebuf.h
	(stdio_sync_filebuf::_M_unget_buf): Declare it.
	(stdio_sync_filebuf::stdio_sync_filebuf): Initialize _M_unget_buf.
	(stdio_sync_filebuf::uflow): Store the returned character in
	_M_unget_buf.
	(stdio_sync_filebuf::pbackfail): If argument is eof(), pass
	_M_unget_buf to syncungetc(). Set _M_unget_buf to eof().
	(stdio_sync_filebuf<char>::xsgetn): Store last read character in
	_M_unget_buf, if any, else eof().
	(stdio_sync_filebuf<wchar_t>::xsgetn: Store last read character in
	_M_unget_buf, if any, else eof().
	* testsuite/27_io/objects/char/12048.cc: Rename to...
	* testsuite/27_io/objects/char/12048-1.cc: ...this.
	* testsuite/27_io/objects/char/12048-2.cc: New test.
	* testsuite/27_io/objects/char/12048-3.cc: New test.
	* testsuite/27_io/objects/char/12048-4.cc: New test.
	* testsuite/27_io/objects/char/12048-5.cc: New test. XFAIL.
	* testsuite/27_io/objects/wchar_t/12048-1.cc: New test.
	* testsuite/27_io/objects/wchar_t/12048-2.cc: New test.
	* testsuite/27_io/objects/wchar_t/12048-3.cc: New test.
	* testsuite/27_io/objects/wchar_t/12048-4.cc: New test.
	* testsuite/27_io/objects/wchar_t/12048-5.cc: New test. XFAIL.
	* testsuite/ext/stdio_sync_filebuf_char.cc
	(test02, test03, test04, test05): New tests.
	* testsuite/ext/stdio_sync_filebuf_wchar_t.cc
	(test02, test03, test04, test05): New tests.

Patches:
http://gcc.gnu.org/cgi-bin/cvsweb.cgi/gcc/libstdc++-v3/testsuite/27_io/objects/char/12048-1.cc.diff?cvsroot=gcc&r1=NONE&r2=1.1
http://gcc.gnu.org/cgi-bin/cvsweb.cgi/gcc/libstdc++-v3/testsuite/27_io/objects/char/12048-2.cc.diff?cvsroot=gcc&r1=NONE&r2=1.1
http://gcc.gnu.org/cgi-bin/cvsweb.cgi/gcc/libstdc++-v3/testsuite/27_io/objects/char/12048-3.cc.diff?cvsroot=gcc&r1=NONE&r2=1.1
http://gcc.gnu.org/cgi-bin/cvsweb.cgi/gcc/libstdc++-v3/testsuite/27_io/objects/char/12048-4.cc.diff?cvsroot=gcc&r1=NONE&r2=1.1
http://gcc.gnu.org/cgi-bin/cvsweb.cgi/gcc/libstdc++-v3/testsuite/27_io/objects/char/12048-5.cc.diff?cvsroot=gcc&r1=NONE&r2=1.1
http://gcc.gnu.org/cgi-bin/cvsweb.cgi/gcc/libstdc++-v3/testsuite/27_io/objects/char/12048.cc.diff?cvsroot=gcc&r1=1.1&r2=NONE
http://gcc.gnu.org/cgi-bin/cvsweb.cgi/gcc/libstdc++-v3/testsuite/27_io/objects/wchar_t/12048-1.cc.diff?cvsroot=gcc&r1=NONE&r2=1.1
http://gcc.gnu.org/cgi-bin/cvsweb.cgi/gcc/libstdc++-v3/testsuite/27_io/objects/wchar_t/12048-2.cc.diff?cvsroot=gcc&r1=NONE&r2=1.1
http://gcc.gnu.org/cgi-bin/cvsweb.cgi/gcc/libstdc++-v3/testsuite/27_io/objects/wchar_t/12048-3.cc.diff?cvsroot=gcc&r1=NONE&r2=1.1
http://gcc.gnu.org/cgi-bin/cvsweb.cgi/gcc/libstdc++-v3/testsuite/27_io/objects/wchar_t/12048-4.cc.diff?cvsroot=gcc&r1=NONE&r2=1.1
http://gcc.gnu.org/cgi-bin/cvsweb.cgi/gcc/libstdc++-v3/testsuite/27_io/objects/wchar_t/12048-5.cc.diff?cvsroot=gcc&r1=NONE&r2=1.1


^ permalink raw reply	[flat|nested] 8+ messages in thread

* [Bug libstdc++/12048] [3.4 Regression] unget does not work
  2003-08-25  3:55 [Bug libstdc++/12048] New: Problems with IOStreams gcc-bugzilla at gcc dot gnu dot org
                   ` (5 preceding siblings ...)
  2003-09-03 14:57 ` cvs-commit at gcc dot gnu dot org
@ 2003-09-03 16:23 ` pinskia at gcc dot gnu dot org
  6 siblings, 0 replies; 8+ messages in thread
From: pinskia at gcc dot gnu dot org @ 2003-09-03 16:23 UTC (permalink / raw)
  To: gcc-bugs

PLEASE REPLY TO gcc-bugzilla@gcc.gnu.org ONLY, *NOT* gcc-bugs@gcc.gnu.org.

http://gcc.gnu.org/bugzilla/show_bug.cgi?id=12048


pinskia at gcc dot gnu dot org changed:

           What    |Removed                     |Added
----------------------------------------------------------------------------
             Status|NEW                         |RESOLVED
         Resolution|                            |FIXED


------- Additional Comments From pinskia at gcc dot gnu dot org  2003-09-03 16:23 -------
Fixed by the patch applied.


^ permalink raw reply	[flat|nested] 8+ messages in thread

end of thread, other threads:[~2003-09-03 16:23 UTC | newest]

Thread overview: 8+ messages (download: mbox.gz / follow: Atom feed)
-- links below jump to the message on this page --
2003-08-25  3:55 [Bug libstdc++/12048] New: Problems with IOStreams gcc-bugzilla at gcc dot gnu dot org
2003-08-25  4:14 ` [Bug libstdc++/12048] [3.4 Regression] unget does not work pinskia at gcc dot gnu dot org
2003-08-26  7:05 ` rittle at latour dot rsch dot comm dot mot dot com
2003-08-26  8:13 ` peturr02 at ru dot is
2003-08-26 10:05 ` peturr02 at ru dot is
2003-09-03 14:54 ` cvs-commit at gcc dot gnu dot org
2003-09-03 14:57 ` cvs-commit at gcc dot gnu dot org
2003-09-03 16:23 ` pinskia at gcc dot gnu dot org

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).