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Dataflow: Simplify revFlowThrough #18355

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Dataflow: Simplify revFlowThrough #18355

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29 changes: 9 additions & 20 deletions shared/dataflow/codeql/dataflow/internal/DataFlowImpl.qll
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Original file line number Diff line number Diff line change
Expand Up @@ -2261,10 +2261,7 @@ module MakeImpl<LocationSig Location, InputSig<Location> Lang> {
returnAp = apNone()
or
// flow through a callable
exists(DataFlowCall call, ParamNodeEx p, Ap innerReturnAp |
revFlowThrough(call, returnCtx, p, state, _, returnAp, ap, innerReturnAp) and
flowThroughIntoCall(call, node, p, ap, innerReturnAp)
)
revFlowThrough(_, returnCtx, state, returnAp, ap, node)
or
// flow out of a callable
exists(ReturnPosition pos |
Expand Down Expand Up @@ -2413,11 +2410,14 @@ module MakeImpl<LocationSig Location, InputSig<Location> Lang> {

pragma[nomagic]
private predicate revFlowThrough(
DataFlowCall call, ReturnCtx returnCtx, ParamNodeEx p, FlowState state,
ReturnPosition pos, ApOption returnAp, Ap ap, Ap innerReturnAp
DataFlowCall call, ReturnCtx returnCtx, FlowState state, ApOption returnAp, Ap ap,
ArgNodeEx arg
) {
revFlowParamToReturn(p, state, pos, innerReturnAp, ap) and
revFlowIsReturned(call, returnCtx, returnAp, pos, innerReturnAp)
exists(ParamNodeEx p, ReturnPosition pos, Ap innerReturnAp |
flowThroughIntoCall(call, arg, p, ap, innerReturnAp) and
revFlowParamToReturn(p, state, pos, innerReturnAp, ap) and
revFlowIsReturned(call, returnCtx, returnAp, pos, innerReturnAp)
Comment on lines +2417 to +2419
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This is disrupting a non-linear join, so it's very likely beneficial to push flowThroughIntoCall further into one of the recursive conjuncts in some way - as-is we're likely having some inefficiency with at least one of the two delta+prev combinations. Also, it would be nice to understand a bit deeper which columns are contributing to the blowup in which way.
We can safely push the projection flowThroughIntoCall(_, _, p, ap, innerReturnAp) into revFlowParamToReturn, which may be beneficial, as that's a pure filter on a pre-non-linear-join conjunct, but we cannot push in the other columns as that would amount to a join with the call-graph a bit too soon (revFlowIsReturned is exactly meant to constrain that part as much as possible).
OTOH, it may very well be good to push flowThroughIntoCall in its entirety into revFlowIsReturned as that already contains the call graph edge. If a project of flowThroughIntoCall to a pure filter in that case turns out yield a beneficial tuple reduction, then the join of revFlowOut and returnFlowsThrough (which occurs in a few places) ought to be revised as flowThroughIntoCall already contains a projected version of returnFlowsThrough.

)
}

/**
Expand Down Expand Up @@ -2543,22 +2543,11 @@ module MakeImpl<LocationSig Location, InputSig<Location> Lang> {
)
}

pragma[nomagic]
private predicate revFlowThroughArg(
DataFlowCall call, ArgNodeEx arg, FlowState state, ReturnCtx returnCtx, ApOption returnAp,
Ap ap
) {
exists(ParamNodeEx p, Ap innerReturnAp |
revFlowThrough(call, returnCtx, p, state, _, returnAp, ap, innerReturnAp) and
flowThroughIntoCall(call, arg, p, ap, innerReturnAp)
)
}

pragma[nomagic]
predicate callMayFlowThroughRev(DataFlowCall call) {
exists(ArgNodeEx arg, FlowState state, ReturnCtx returnCtx, ApOption returnAp, Ap ap |
revFlow(arg, state, returnCtx, returnAp, ap) and
revFlowThroughArg(call, arg, state, returnCtx, returnAp, ap)
revFlowThrough(call, returnCtx, state, returnAp, ap, arg)
)
}

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