[polybori] 01/09: Get rid of some lintian warnings.

[Tobias Hansen]

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thansen pushed a commit to branch master
in repository polybori.

commit 120e607b88b0ce60380b12e429c157c26d2309be
Author: Tobias Hansen <tobias.han at gmx.de>
Date:   Sat Nov 2 22:22:33 2013 +0100

    Get rid of some lintian warnings.
---
 debian/control |   46 ++++++++++++++++++++++------------------------
 1 file changed, 22 insertions(+), 24 deletions(-)

diff --git a/debian/control b/debian/control
index 19ef48b..b053882 100644
--- a/debian/control
+++ b/debian/control
@@ -22,8 +22,8 @@ Build-Depends-Indep: doxygen,
                      texlive-latex-extra,
                      texlive-latex-recommended
 Standards-Version: 3.9.4
-Vcs-Browser: http://git.debian.org/?p=debian-science/packages/polybori.git
-Vcs-Git: git://git.debian.org/git/debian-science/packages/polybori.git
+Vcs-Browser: http://anonscm.debian.org/gitweb/?p=debian-science/packages/polybori.git
+Vcs-Git: git://anonscm.debian.org/debian-science/packages/polybori.git
 Homepage: http://polybori.sourceforge.net/
 X-Python-Version: >= 2.6
 
@@ -42,8 +42,8 @@ Description: polynomials over Boolean Rings, Python module
  well as for the underlying polynomial rings and subsets of the
  powerset of the Boolean variables. As a unique approach, binary
  decision diagrams are used as internal storage type for polynomial
- structures. On top of this C++-library we provide a Python
- interface. This allows parsing of complex polynomial systems, as well
+ structures. On top of this C++-library a Python interface
+ is provided. This allows parsing of complex polynomial systems, as well
  as sophisticated and extendable strategies for Groebner base
  computation. PolyBoRi features a powerful reference implementation
  for Groebner basis computation.
@@ -64,8 +64,8 @@ Description: polynomials over Boolean Rings, Python module
  well as for the underlying polynomial rings and subsets of the
  powerset of the Boolean variables. As a unique approach, binary
  decision diagrams are used as internal storage type for polynomial
- structures. On top of this C++-library we provide a Python
- interface. This allows parsing of complex polynomial systems, as well
+ structures. On top of this C++-library a Python interface
+ is provided. This allows parsing of complex polynomial systems, as well
  as sophisticated and extendable strategies for Groebner base
  computation. PolyBoRi features a powerful reference implementation
  for Groebner basis computation.
@@ -86,8 +86,8 @@ Description: polynomials over Boolean Rings, Python module
  well as for the underlying polynomial rings and subsets of the
  powerset of the Boolean variables. As a unique approach, binary
  decision diagrams are used as internal storage type for polynomial
- structures. On top of this C++-library we provide a Python
- interface. This allows parsing of complex polynomial systems, as well
+ structures. On top of this C++-library a Python interface
+ is provided. This allows parsing of complex polynomial systems, as well
  as sophisticated and extendable strategies for Groebner base
  computation. PolyBoRi features a powerful reference implementation
  for Groebner basis computation.
@@ -105,8 +105,8 @@ Description: polynomials over Boolean Rings, core development files
  well as for the underlying polynomial rings and subsets of the
  powerset of the Boolean variables. As a unique approach, binary
  decision diagrams are used as internal storage type for polynomial
- structures. On top of this C++-library we provide a Python
- interface. This allows parsing of complex polynomial systems, as well
+ structures. On top of this C++-library a Python interface
+ is provided. This allows parsing of complex polynomial systems, as well
  as sophisticated and extendable strategies for Groebner base
  computation. PolyBoRi features a powerful reference implementation
  for Groebner basis computation.
@@ -127,8 +127,8 @@ Description: polynomials over Boolean Rings, shared library
  well as for the underlying polynomial rings and subsets of the
  powerset of the Boolean variables. As a unique approach, binary
  decision diagrams are used as internal storage type for polynomial
- structures. On top of this C++-library we provide a Python
- interface. This allows parsing of complex polynomial systems, as well
+ structures. On top of this C++-library a Python interface
+ is provided. This allows parsing of complex polynomial systems, as well
  as sophisticated and extendable strategies for Groebner base
  computation. PolyBoRi features a powerful reference implementation
  for Groebner basis computation.
@@ -139,7 +139,6 @@ Package: libpolybori-0.8-3-dbg
 Architecture: any
 Multi-Arch: same
 Section: debug
-Priority: extra
 Depends: ${misc:Depends},
          libpolybori-0.8-3 (= ${binary:Version})
 Description: debug symbols for libpolybori-0.8-3 
@@ -148,8 +147,8 @@ Description: debug symbols for libpolybori-0.8-3
  well as for the underlying polynomial rings and subsets of the
  powerset of the Boolean variables. As a unique approach, binary
  decision diagrams are used as internal storage type for polynomial
- structures. On top of this C++-library we provide a Python
- interface. This allows parsing of complex polynomial systems, as well
+ structures. On top of this C++-library a Python interface
+ is provided. This allows parsing of complex polynomial systems, as well
  as sophisticated and extendable strategies for Groebner base
  computation. PolyBoRi features a powerful reference implementation
  for Groebner basis computation.
@@ -169,8 +168,8 @@ Description: developers's files for libpolybori-groebner-0.8-3
  well as for the underlying polynomial rings and subsets of the
  powerset of the Boolean variables. As a unique approach, binary
  decision diagrams are used as internal storage type for polynomial
- structures. On top of this C++-library we provide a Python
- interface. This allows parsing of complex polynomial systems, as well
+ structures. On top of this C++-library a Python interface
+ is provided. This allows parsing of complex polynomial systems, as well
  as sophisticated and extendable strategies for Groebner base
  computation. PolyBoRi features a powerful reference implementation
  for Groebner basis computation.
@@ -194,8 +193,8 @@ Description: computer algebra routines of PolyBoRi
  well as for the underlying polynomial rings and subsets of the
  powerset of the Boolean variables. As a unique approach, binary
  decision diagrams are used as internal storage type for polynomial
- structures. On top of this C++-library we provide a Python
- interface. This allows parsing of complex polynomial systems, as well
+ structures. On top of this C++-library a Python interface
+ is provided. This allows parsing of complex polynomial systems, as well
  as sophisticated and extendable strategies for Groebner base
  computation. PolyBoRi features a powerful reference implementation
  for Groebner basis computation.
@@ -206,7 +205,6 @@ Package: libpolybori-groebner-0.8-3-dbg
 Architecture: any
 Multi-Arch: same
 Section: debug
-Priority: extra
 Depends: ${misc:Depends},
          libpolybori-groebner-0.8-3 (= ${binary:Version})
 Description: debug symbols for libpolybori-groebner-0.8-3
@@ -215,8 +213,8 @@ Description: debug symbols for libpolybori-groebner-0.8-3
  well as for the underlying polynomial rings and subsets of the
  powerset of the Boolean variables. As a unique approach, binary
  decision diagrams are used as internal storage type for polynomial
- structures. On top of this C++-library we provide a Python
- interface. This allows parsing of complex polynomial systems, as well
+ structures. On top of this C++-library a Python interface
+ is provided. This allows parsing of complex polynomial systems, as well
  as sophisticated and extendable strategies for Groebner base
  computation. PolyBoRi features a powerful reference implementation
  for Groebner basis computation.
@@ -236,8 +234,8 @@ Description: polynomials over Boolean Rings, shared library
  well as for the underlying polynomial rings and subsets of the
  powerset of the Boolean variables. As a unique approach, binary
  decision diagrams are used as internal storage type for polynomial
- structures. On top of this C++-library we provide a Python
- interface. This allows parsing of complex polynomial systems, as well
+ structures. On top of this C++-library a Python interface
+ is provided. This allows parsing of complex polynomial systems, as well
  as sophisticated and extendable strategies for Groebner base
  computation. PolyBoRi features a powerful reference implementation
  for Groebner basis computation.

-- 
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