What continous adjustment methods are firms using for futures backtesting?

There are several methods available between data vendors and associated software programs to adjust futures contract data for historical simulations.

Some of the methods are:

1) Back or forward Adjust by iterative level shifting of historical data at rollover points.

2) Back or forward Adjust by iteratively using ratio of historical series to current series.

3) Using next contract with highest volume instead of front contract as the next contract to be joined.

Some of the problems associated with different methods can be

1) negative price series

2) inconsistency in rollover dates (one person may use first notice day e.g. commodities, another might use 20 days prior to settlement, another 7 etc..)

3) adjustment methods vary by instrument.

4) There could be true price gaps between the rollover period that have been filtered out by the method of adjustment.

The list is nowhere near exhaustive* Could anyone elaborate on what methods you or your firm are actually using to systematically adjust a broad portfolio of futures contracts (for simulations) in practice? Also, what pros and cons are there to using your method vs. some of the other methods that exist? Any references to expand on your method are also appreciated.

*There are some papers e.g. here and here and blogs that discuss pros and cons, but I'm more interested in best practices and approaches by large portfolio managers.