anchor.diff:                       [state_get(instance, State), AvgType, OldValue, NewValue]),
                _HasConverged = calc_change(OldValue, NewValue) < AvgChangeEpsilon
            end
  -         || {OldLoadModule, NewLoadModule} <- lists:zip(OldLoad, NewLoad),
  +         || {OldLoadModule, NewLoadModule} <- lists:zip(OldLoadList, NewLoadList),
               AvgType                        <- [avg, avg2]
           ],
   
  -    LoadConverged = lists:foldl(fun(Mod, Acc) -> Acc andalso Mod end,
  -                                true, LoadModulesConverged),
  +    LoadConverged = lists:all(fun(X) -> X end, LoadModulesConverged),
   
       HaveConverged1 = RingConverged andalso LoadConverged,
       log:log(debug, "Averages have converged: ~w", [HaveConverged1]),
  
positive.code: 
  
  -spec update_convergence_count(OldData::data(), NewData::data(), State::state()) -> true.
  update_convergence_count(OldData = {OldLoad, OldRing}, NewData = {NewLoad, NewRing}, State) ->
  
      % check whether all average based values changed less than epsilon percent
      AvgChangeEpsilon = convergence_epsilon(),
  
      %% Ring convergence
      Fun = fun(AvgType, Acc) ->
              {OldAvg, OldWeight} = data_get(AvgType, OldRing),
              {NewAvg, NewWeight} = data_get(AvgType, NewRing),
              OldValue = calc_current_estimate(OldAvg, OldWeight),
              NewValue = calc_current_estimate(NewAvg, NewWeight),
              log:log(debug, "[ ~w ] ~w: OldValue: ~w, New Value: ~w",
                  [state_get(instance, State), AvgType, OldValue, NewValue]),
              HasConverged = calc_change(OldValue, NewValue) < AvgChangeEpsilon,
              Acc andalso HasConverged
      end,
      RingConverged = lists:foldl(Fun, true, [size_inv, avg_kr]),
  
      %% Load convergence
      LoadModulesConverged =
  
negative.code:                                        data_get(histo, OldLoadModule), data_get(histo, NewLoadModule)),
  
                % check that all the buckets of histogram have changed less than epsilon percent
                Fun1 = fun({OldAvg, NewAvg}) ->
                               OldEstimate = calc_current_estimate(OldAvg),
                               NewEstimate = calc_current_estimate(NewAvg),
                               _HasConverged = calc_change(OldEstimate, NewEstimate) < AvgChangeEpsilon
                       end,
                _HaveConverged2 = lists:all(Fun1, CompList)
            end
            || {OldLoadModule, NewLoadModule} <- lists:zip(OldLoadList, NewLoadList)
          ],
  
      HaveConverged2 = lists:all(fun(X) -> X end, HistoModulesConverged),
      log:log(debug, "Histogram has converged: ~w", [HaveConverged2]),
  
      HaveConverged = HaveConverged1 andalso HaveConverged2,
  