diff --git a/base/linalg/lu.jl b/base/linalg/lu.jl
index 6bc8a06177865..31f0995ecab94 100644
--- a/base/linalg/lu.jl
+++ b/base/linalg/lu.jl
@@ -289,7 +289,7 @@ end
 
 function At_ldiv_B!{T}(A::LU{T,Tridiagonal{T}}, B::AbstractVecOrMat)
     n = size(A,1)
-    n == size(B,1) || throw(DimentionsMismatch(""))
+    n == size(B,1) || throw(DimensionMismatch(""))
     nrhs = size(B,2)
     dl = A.factors.dl
     d = A.factors.d
@@ -322,7 +322,7 @@ end
 # Ac_ldiv_B!{T<:Real}(A::LU{T,Tridiagonal{T}}, B::AbstractVecOrMat) = At_ldiv_B!(A,B)
 function Ac_ldiv_B!{T}(A::LU{T,Tridiagonal{T}}, B::AbstractVecOrMat)
     n = size(A,1)
-    n == size(B,1) || throw(DimentionsMismatch(""))
+    n == size(B,1) || throw(DimensionMismatch(""))
     nrhs = size(B,2)
     dl = A.factors.dl
     d = A.factors.d
diff --git a/test/linalg/lu.jl b/test/linalg/lu.jl
index 829f621c3e0f7..3b0dc837799ab 100644
--- a/test/linalg/lu.jl
+++ b/test/linalg/lu.jl
@@ -16,13 +16,23 @@ areal = randn(n,n)/2
 aimg  = randn(n,n)/2
 breal = randn(n,2)/2
 bimg  = randn(n,2)/2
+creal = randn(n)/2
+cimg  = randn(n)/2
+dureal = randn(n-1)/2
+duimg  = randn(n-1)/2
+dlreal = randn(n-1)/2
+dlimg  = randn(n-1)/2
+dreal = randn(n)/2
+dimg  = randn(n)/2
 
 for eltya in (Float32, Float64, Complex64, Complex128, BigFloat, Int)
     a = eltya == Int ? rand(1:7, n, n) : convert(Matrix{eltya}, eltya <: Complex ? complex(areal, aimg) : areal)
+    d = eltya == Int ? Tridiagonal(rand(1:7, n-1), rand(1:7, n), rand(1:7, n-1)) : convert(Tridiagonal{eltya}, eltya <: Complex ? Tridiagonal(complex(dlreal, dlimg), complex(dreal, dimg), complex(dureal, duimg)) : Tridiagonal(dlreal, dreal, dureal))
     ε = εa = eps(abs(float(one(eltya))))
 
     for eltyb in (Float32, Float64, Complex64, Complex128, Int)
         b = eltyb == Int ? rand(1:5, n, 2) : convert(Matrix{eltyb}, eltyb <: Complex ? complex(breal, bimg) : breal)
+        c = eltyb == Int ? rand(1:5, n) : convert(Vector{eltyb}, eltyb <: Complex ? complex(creal, cimg) : creal)
         εb = eps(abs(float(one(eltyb))))
         ε = max(εa,εb)
 
@@ -36,8 +46,27 @@ debug && println("(Automatic) Square LU decomposition")
         @test norm(a*(lua\b) - b, 1) < ε*κ*n*2 # Two because the right hand side has two columns
         @test norm(a'*(lua'\b) - b, 1) < ε*κ*n*2 # Two because the right hand side has two columns
         @test norm(a'*(lua'\a') - a', 1) < ε*κ*n^2
+        @test norm(a*(lua\c) - c, 1) < ε*κ*n # c is a vector
+        @test norm(a'*(lua'\c) - c, 1) < ε*κ*n # c is a vector
+        if eltya <: Real && eltyb <: Real
+            @test norm(a.'*(lua.'\b) - b,1) < ε*κ*n*2 # Two because the right hand side has two columns
+            @test norm(a.'*(lua.'\c) - c,1) < ε*κ*n
+        end
         @test_approx_eq full(lua) a
 
+debug && println("Tridiagonal LU")
+        κd    = cond(full(d),1)
+        lud   = lufact(d)
+        @test norm(d*(lud\b) - b, 1) < ε*κd*n*2 # Two because the right hand side has two columns
+        if eltya <: Real
+            @test norm((lud.'\b) - full(d.')\b, 1) < ε*κd*n*2 # Two because the right hand side has two columns
+        end
+        if eltya <: Complex
+            @test norm((lud'\b) - full(d')\b, 1) < ε*κd*n*2 # Two because the right hand side has two columns
+        end
+        f = zeros(eltyb, n+1)
+        @test_throws DimensionMismatch lud\f
+
 debug && println("Thin LU")
         lua   = @inferred lufact(a[:,1:n1])
         @test_approx_eq lua[:L]*lua[:U] lua[:P]*a[:,1:n1]