to deduce synchronization factors.
eg. convex hull, linear regression, broadcast Maximum Likelihood Estimator
+This module should return a set of synchronization factors for each trace
+pair. Some trace pairs may have no factors, their approxType should be set to
+ABSENT.
+
Instead of having one analyzeEvents() function that can receive any sort of
grouping of events, there are three prototypes: analyzeMessage(),
analyzeExchange() and analyzeBroadcast(). A module implements only the
3) we'll see which one of the two approaches works best and we can adapt
later.
-++ Data flow
-Data from traces flows "down" from processing to matching to analysis. Factors
-come back up.
-
++ Stage 4: Factor reduction
-This stage reduces the pair-wise synchronization factors to time correction
-factors for each trace. It is most useful when synchronizing more than two
-traces.
+This stage reduces the pair-wise synchronization factors obtained in step 3 to
+time correction factors for each trace. It is most useful when synchronizing
+more than two traces.
++ Evolution and adaptation
It is possible to change/add another sync chain and to add other modules. It