--- a/doc/interpreter/errors.txi
+++ b/doc/interpreter/errors.txi
@@ -285,7 +285,7 @@
 @group
 function rand42
   old_state = rand ("state");
-  restore_state = onCleanup (@@() rand ("state", old_state);
+  restore_state = onCleanup (@@() rand ("state", old_state));
   rand ("state", 42);
   @dots{}
 endfunction  # rand generator state restored by onCleanup

--- a/doc/interpreter/install.txi
+++ b/doc/interpreter/install.txi
@@ -846,7 +846,7 @@
 
 @noindent
 in the kernel configuration files (typically found in the directory
-@file{/sys/i386/conf}.  After making this change, you'll need to rebuild
+@file{/sys/i386/conf}).  After making this change, you'll need to rebuild
 the kernel, install it, and reboot.
 
 @item

--- a/doc/interpreter/sparse.txi
+++ b/doc/interpreter/sparse.txi
@@ -793,8 +793,8 @@
 
 @item If the matrix is not square, or any of the previous solvers flags
 a singular or near singular matrix, find a minimum norm solution using
-@sc{cxsparse}@footnote{The @sc{cholmod}, @sc{umfpack} and @sc{cxsparse} packages were
-written by Tim Davis and are available at
+@sc{cxsparse}@footnote{The @sc{cholmod}, @sc{umfpack} and @sc{cxsparse}
+packages were written by Tim Davis and are available at
 @url{http://www.cise.ufl.edu/research/sparse/}}.
 @end enumerate
 
@@ -997,7 +997,7 @@
 as constant on each simplex (represented by the vector @code{conductivity}).
 Based on the finite element geometry, we first calculate a system (or
 stiffness) matrix for each simplex (represented as 3-by-3 elements on the
-diagonal of the element-wise system matrix @code{SE}.  Based on @code{SE} 
+diagonal of the element-wise system matrix @code{SE}).  Based on @code{SE} 
 and a N-by-DE connectivity matrix @code{C}, representing the connections 
 between simplices and vertices, the global connectivity matrix @code{S} is
 calculated.

--- a/doc/interpreter/vectorize.txi
+++ b/doc/interpreter/vectorize.txi
@@ -697,7 +697,7 @@
 for i = 1:length (A)
   ## this will be two columns, the first is the difference and
   ## the second the mean of the two elements used for the diff.
-  B(i,:) = [A(i+1)-A(i), (A(i+1) + A(i))/2)];
+  B(i,:) = [A(i+1)-A(i), (A(i+1) + A(i))/2];
 endfor
 @end group
 @end example

--- a/libinterp/corefcn/data.cc
+++ b/libinterp/corefcn/data.cc
@@ -120,7 +120,7 @@
 \n\
 @example\n\
 @group\n\
-all ([2, 3; 1, 0]))\n\
+all ([2, 3; 1, 0])\n\
     @result{} [ 1, 0 ]\n\
 @end group\n\
 @end example\n\
@@ -4607,7 +4607,7 @@
 @equiv{}\n\
 eye (2, 2)\n\
 @equiv{}\n\
-eye (size ([1, 2; 3, 4])\n\
+eye (size ([1, 2; 3, 4]))\n\
 @end group\n\
 @end example\n\
 \n\

--- a/libinterp/corefcn/rand.cc
+++ b/libinterp/corefcn/rand.cc
@@ -577,7 +577,7 @@
 Reference: G. Marsaglia and W.W. Tsang,\n\
 @cite{Ziggurat Method for Generating Random Variables},\n\
 J. Statistical Software, vol 5, 2000,\n\
-@url{http://www.jstatsoft.org/v05/i08/})\n\
+@url{http://www.jstatsoft.org/v05/i08/}\n\
 \n\
 @seealso{rand, rande, randg, randp}\n\
 @end deftypefn")
@@ -648,7 +648,7 @@
 Reference: G. Marsaglia and W.W. Tsang,\n\
 @cite{Ziggurat Method for Generating Random Variables},\n\
 J. Statistical Software, vol 5, 2000,\n\
-@url{http://www.jstatsoft.org/v05/i08/})\n\
+@url{http://www.jstatsoft.org/v05/i08/}\n\
 \n\
 @seealso{rand, randn, randg, randp}\n\
 @end deftypefn")

--- a/libinterp/dldfcn/amd.cc
+++ b/libinterp/dldfcn/amd.cc
@@ -67,8 +67,8 @@
 @table @asis\n\
 @item @var{opts}.dense\n\
 Determines what @code{amd} considers to be a dense row or column of the\n\
-input matrix.  Rows or columns with more than @code{max(16, (dense *\n\
-sqrt (@var{n})} entries, where @var{n} is the order of the matrix @var{S},\n\
+input matrix.  Rows or columns with more than @code{max (16, (dense *\n\
+sqrt (@var{n})))} entries, where @var{n} is the order of the matrix @var{S},\n\
 are ignored by @code{amd} during the calculation of the permutation\n\
 The value of dense must be a positive scalar and its default value is 10.0\n\
 \n\

--- a/libinterp/dldfcn/ccolamd.cc
+++ b/libinterp/dldfcn/ccolamd.cc
@@ -100,10 +100,9 @@
 @var{cmember} is an optional vector of length @math{n}.  It defines the\n\
 constraints on the column ordering.  If @code{@var{cmember}(j) = @var{c}},\n\
 then column @var{j} is in constraint set @var{c} (@var{c} must be in the\n\
-range 1 to\n\
-n).  In the output permutation @var{p}, all columns in set 1 appear\n\
-first, followed by all columns in set 2, and so on.  @code{@var{cmember} =\n\
-ones (1,n)} if not present or empty.\n\
+range 1 to n).  In the output permutation @var{p}, all columns in set 1\n\
+appear first, followed by all columns in set 2, and so on.\n\
+@code{@var{cmember} = ones (1,n)} if not present or empty.\n\
 @code{ccolamd (@var{S}, [], 1 : n)} returns @code{1 : n}\n\
 \n\
 @code{@var{p} = ccolamd (@var{S})} is about the same as\n\

--- a/liboctave/numeric/DASPK-opts.in
+++ b/liboctave/numeric/DASPK-opts.in
@@ -209,7 +209,7 @@
 A vector of the same length as the state vector.  A nonzero element
 indicates that the corresponding element of the state vector is an
 algebraic variable (i.e., its derivative does not appear explicitly
-in the equation set.
+in the equation set).
 
 This option is required by the
 @qcode{\"compute consistent initial condition\"} and

--- a/scripts/general/cplxpair.m
+++ b/scripts/general/cplxpair.m
@@ -23,7 +23,7 @@
 ## Sort the numbers @var{z} into complex conjugate pairs ordered by
 ## increasing real part.  Place the negative imaginary complex number
 ## first within each pair.  Place all the real numbers (those with
-## @code{abs (imag (@var{z}) / @var{z}) < @var{tol})}) after the
+## @code{abs (imag (@var{z}) / @var{z}) < @var{tol}}) after the
 ## complex pairs.
 ##
 ## If @var{tol} is unspecified the default value is 100*@code{eps}.

--- a/scripts/java/javamem.m
+++ b/scripts/java/javamem.m
@@ -36,7 +36,7 @@
 ## determined by the environment variable @w{@env{OCTAVE_JAVA_DIR}}.
 ## If unset, the directory where @file{javaaddpath.m} resides is used instead
 ## (typically
-## @file{@w{@env{OCTAVE_HOME}}/share/octave/@w{@env{OCTAVE_VERSION}}/m/java/}
+## @file{@w{@env{OCTAVE_HOME}}/share/octave/@w{@env{OCTAVE_VERSION}}/m/java/}).
 ##
 ## @file{java.opts} is a plain text file with one option per line.  The
 ## default initial memory size and default maximum memory size (which

--- a/scripts/optimization/glpk.m
+++ b/scripts/optimization/glpk.m
@@ -123,7 +123,7 @@
 ##
 ## @item @qcode{"D"}
 ## An inequality constraint with both upper and lower bounds
-## (@code{A(i,:)*x >= -b(i)} @emph{and} (@code{A(i,:)*x <= b(i)}).
+## (@code{A(i,:)*x >= -b(i)}) @emph{and} (@code{A(i,:)*x <= b(i)}).
 ## @end table
 ##
 ## @item vartype

--- a/scripts/plot/draw/area.m
+++ b/scripts/plot/draw/area.m
@@ -49,7 +49,7 @@
 ## @example
 ## @group
 ## t = linspace (0, 2*pi, 100)';
-## y = [sin(t).^2, cos(t).^2)];
+## y = [sin(t).^2, cos(t).^2];
 ## area (t, y);
 ## legend ("sin^2", "cos^2", "location", "NorthEastOutside");
 ## @end group

--- a/scripts/plot/draw/peaks.m
+++ b/scripts/plot/draw/peaks.m
@@ -27,7 +27,7 @@
 ## The function has the form
 ##
 ## @tex
-## $$f(x,y) = 3 (1 - x) ^ 2 e ^ {\left(-x^2 - (y+1)^2\right)} - 10 \left({x \over 5} - x^3 - y^5)\right) - {1 \over 3} e^{\left(-(x+1)^2 - y^2\right)}$$
+## $$f(x,y) = 3 (1 - x) ^ 2 e ^ {\left(-x^2 - (y+1)^2\right)} - 10 \left({x \over 5} - x^3 - y^5\right) - {1 \over 3} e^{\left(-(x+1)^2 - y^2\right)}$$
 ## @end tex
 ## @ifnottex
 ## @verbatim

--- a/scripts/plot/util/hgload.m
+++ b/scripts/plot/util/hgload.m
@@ -17,7 +17,7 @@
 ## <http://www.gnu.org/licenses/>.
 
 ## -*- texinfo -*-
-## @deftypefn  {Function File} {@var{h} =} hgload (@var{filename})
+## @deftypefn {Function File} {@var{h} =} hgload (@var{filename})
 ## Load the graphics object in @var{filename} into the graphics handle @var{h}.
 ##
 ## If @var{filename} has no extension, Octave will try to find the file with

--- a/scripts/plot/util/hgsave.m
+++ b/scripts/plot/util/hgsave.m
@@ -17,9 +17,9 @@
 ## <http://www.gnu.org/licenses/>.
 
 ## -*- texinfo -*-
-## @deftypefn  {Function File} hgsave (@var{filename})
-## @deftypefnx {Function File} hgsave (@var{h}, @var{filename})
-## @deftypefnx {Function File} hgsave (@var{h}, @var{filename}, @var{fmt})
+## @deftypefn  {Function File} {} hgsave (@var{filename})
+## @deftypefnx {Function File} {} hgsave (@var{h}, @var{filename})
+## @deftypefnx {Function File} {} hgsave (@var{h}, @var{filename}, @var{fmt})
 ## Save the graphics handle @var{h} to the file @var{filename} in the format
 ## @var{fmt}.
 ##

--- a/scripts/statistics/tests/hotelling_test_2.m
+++ b/scripts/statistics/tests/hotelling_test_2.m
@@ -26,7 +26,7 @@
 ## Hotelling's two-sample @math{T^2} is returned in @var{tsq}.  Under the null,
 ## @tex
 ## $$
-## {n_x+n_y-p-1) T^2 \over p(n_x+n_y-2)}
+## {(n_x+n_y-p-1) T^2 \over p(n_x+n_y-2)}
 ## $$
 ## @end tex
 ## @ifnottex