diff --git a/.travis.yml b/.travis.yml
index 3dafe8c..c6d246d 100644
--- a/.travis.yml
+++ b/.travis.yml
@@ -16,4 +16,4 @@ git:
 #  - if [[ -a .git/shallow ]]; then git fetch --unshallow; fi
 #  - julia -e 'Pkg.clone(pwd()); Pkg.build("DualNumbers"); Pkg.test("DualNumbers"; coverage=true)'
 after_success:
-  - julia -e 'cd(Pkg.dir("DualNumbers")); Pkg.add("Coverage"); using Coverage; Coveralls.submit(Coveralls.process_folder())'
+  - julia -e 'using Pkg; Pkg.add("Coverage"); using Coverage; Coveralls.submit(Coveralls.process_folder())'
diff --git a/src/dual.jl b/src/dual.jl
index 3b6e70a..653e559 100644
--- a/src/dual.jl
+++ b/src/dual.jl
@@ -31,6 +31,9 @@ Base.widen(::Type{Dual{T}}) where {T} = Dual{widen(T)}
 value(z::Dual) = z.value
 epsilon(z::Dual) = z.epsilon
 
+value(x::Number) = x
+epsilon(x::Number) = zero(typeof(x))
+
 dual(x::ReComp, y::ReComp) = Dual(x, y)
 dual(x::ReComp) = Dual(x)
 dual(z::Dual) = z
@@ -264,7 +267,7 @@ Base.:^(z::Dual, n::Number) = Dual(value(z)^n, epsilon(z)*n*value(z)^(n-1))
 NaNMath.pow(z::Dual, n::Number) = Dual(NaNMath.pow(value(z),n), epsilon(z)*n*NaNMath.pow(value(z),n-1))
 NaNMath.pow(z::Number, w::Dual) = Dual(NaNMath.pow(z,value(w)), epsilon(w)*NaNMath.pow(z,value(w))*log(z))
 
-inv(z::Dual) = dual(inv(value(z)),-epsilon(z)/value(z)^2)
+Base.inv(z::Dual) = dual(inv(value(z)),-epsilon(z)/value(z)^2)
 
 # force use of NaNMath functions in derivative calculations
 function to_nanmath(x::Expr)
@@ -313,6 +316,8 @@ end
 Base.exp(z::Dual) = (expval = exp(value(z)); Dual(expval, epsilon(z)*expval))
 Base.cis(z::Dual) = (cisval = cis(value(z)); Dual(cisval, im*epsilon(z)*cisval))
 
+Base.exp10(x::Dual) = (y = exp10(value(x)); Dual(y, y * log(10) * epsilon(x)))
+
 ## TODO: should be generated in Calculus
 Base.sinpi(z::Dual) = Dual(sinpi(value(z)),epsilon(z)*cospi(value(z))*π)
 Base.cospi(z::Dual) = Dual(cospi(value(z)),-epsilon(z)*sinpi(value(z))*π)
diff --git a/test/automatic_differentiation_test.jl b/test/automatic_differentiation_test.jl
index 8013891..92c1e0a 100644
--- a/test/automatic_differentiation_test.jl
+++ b/test/automatic_differentiation_test.jl
@@ -162,3 +162,12 @@ flipsign(-1.0,Dual(1.0,1.0)) == -1.0
 # test SpecialFunctions
 @test erf(dual(1.0,1.0)) == dual(erf(1.0), 2exp(-1.0^2)/sqrt(π))
 @test gamma(dual(1.,1)) == dual(gamma(1.0),polygamma(0,1.0))
+
+
+let x = exp10(Dual(2, 0.01))
+    @test value(x) ≈ 100.0
+    @test epsilon(x) ≈ log(10)
+end
+
+@test value(3) == 3
+@test epsilon(44.0) ≈ 0.0