diff --git a/src/continuation/Palc.jl b/src/continuation/Palc.jl
index 83dee854..719b0e05 100644
--- a/src/continuation/Palc.jl
+++ b/src/continuation/Palc.jl
@@ -361,25 +361,6 @@ function gettangent!(state::AbstractContinuationState,
 end
 
 
-####################################################################################################
-function arcLengthScaling(θ, alg, τ::M, verbosity) where {M <: BorderedArray}
-    # the arclength scaling algorithm is based on Salinger, Andrew G, Nawaf M Bou-Rabee,
-    # Elizabeth A Burroughs, Roger P Pawlowski, Richard B Lehoucq, Louis Romero, and Edward D
-    # Wilkes. “LOCA 1.0 Library of Continuation Algorithms: Theory and Implementation Manual,
-    # ” March 1, 2002. https://doi.org/10.2172/800778.
-    thetanew = θ
-    g = abs(τ.p * θ)
-    (verbosity > 0) && print("Theta changes from $(θ) to ")
-    if (g > alg.gMax)
-        thetanew = alg.gGoal / τ.p * sqrt( abs(1.0 - g^2) / abs(1.0 - τ.p^2) )
-        if (thetanew < alg.thetaMin)
-          thetanew = alg.thetaMin;
-        end
-    end
-    (verbosity > 0) && print("$(thetanew)\n")
-    return thetanew
-end
-
 ####################################################################################################
 """
 This is the classical Newton-Krylov solver for `F(x, p) = 0` together
diff --git a/test/simple_continuation.jl b/test/simple_continuation.jl
index 3c3f6043..9260195a 100644
--- a/test/simple_continuation.jl
+++ b/test/simple_continuation.jl
@@ -52,7 +52,7 @@ BK.isinplace(prob)
 BK.getvectortype(prob)
 show(prob)
 
-br0 = @time continuation(prob, PALC(doArcLengthScaling = true), opts; callback_newton = BK.cbMaxNormAndΔp(10,10)) #(17.98 k allocations: 1.155 MiB)
+br0 = @time continuation(prob, PALC(), opts; callback_newton = BK.cbMaxNormAndΔp(10,10)) #(17.98 k allocations: 1.155 MiB)
 BK.getfirstusertype(br0)
 BK.propertynames(br0)
 BK.compute_eigenvalues(opts)
@@ -111,7 +111,6 @@ BK.getparams(br1)
 
 @set! prob.recordFromSolution = (x,p) -> norm(x,2)
 br2 = continuation(prob, PALC(), opts)
-BK.arcLengthScaling(0.5, PALC(), BorderedArray(rand(2), 0.1), true)
 
 # test for different norms
 br3 = continuation(prob, PALC(), opts, normC = norminf)