• Re-implemented the join operation for JaCoP spaces, which was using unjustifiably large amounts of RAM to achieve undue speed-ups. This change results in the following performance impacts when using JaCoP:
  • Max-Sum has become about 2x slower on graph coloring problems and 50% slower on large meeting scheduling instances (see graphs below); 
  • P-DPOP's runtime performance has been significantly degraded, but it is now able to scale to larger problem instances before running out of RAM (see graphs below). 
• Fixed several bugs in the JaCoP interface (after a report by Ajdin Sumic). These bug fixes result in the following performance impacts when using JaCoP:
  • Max-Sum has become 30% faster on loose random Max-DisCSP instances (see graphs below); 
  • SynchBB has become 20%-30% faster on larger problem instances (see graphs below); 
  • AFB has become 20% faster on graph coloring problems and up to 50% on large meeting scheduling problems (see graphs below); 
  • MGM and MGM-2 have become 10% faster on meeting scheduling (see graphs below).
• Introduced a new Python plotPerInstance() function to produce graphs in which the performance is reported against each problem instance, in algorithm-specific increasing order (improvement request by Ajdin Sumic). 

• The name of the temporary results file can now be passed as an optional parameter to the Python run() and runFromRepo() functions (improvement request by Ajdin Sumic).
• FRODO now comes with sample XCSP problem instances in the folder experiments/repository to illustrate the intensional constraints listed in the user manual (improvement request by Ajdin Sumic).
• Improved the auto-sizing of logarithmic y axes in the Python plot() function.
• Fixed a bug in the JaCoP XCSP parser triggered on Diff2 global constraints. 

Read more: Releasing FRODO Version 2.19.1 (bug fixes, performance, graphs)