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Memory SSA form and sparse value-flows constructed interprocedurally for an example modified from Figure 2 with its four swap instructions moved into a separate function, called swap. 8 and 13 correspond to the FUNENTRY and FUNEXIT of swap.

Memory SSA form and sparse value-flows constructed interprocedurally for an example modified from Figure 2 with its four swap instructions moved into a separate function, called swap. 8 and 13 correspond to the FUNENTRY and FUNEXIT of swap.

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Fig. 2: A swap example and its partial SSA form. 
Fig. 3: Memory SSA form and sparse value-flows constructed...
Fig. 4: Memory SSA form and sparse value-flows constructed...
Fig. 9: Resolving ptpx 11 , zyq " tc, du with a weak update. 
+4 Fig. 10: Resolving ptpx 5 , zyq " ta, bu in a value-flow cycle.
Demand-Driven Pointer Analysis with Strong Updates via Value-Flow Refinement
Article
Full-text available
  • Jan 2017
We present a new demand-driven flow- and context-sensitive pointer analysis with strong updates for C programs, called SUPA, that enables computing points-to information via value-flow refinement, in environments with small time and memory budgets such as IDEs. We formulate SUPA by solving a graph reachability problem on an inter-procedural value-f...
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Context 1
... addition, appropriate χ and µ operators are also added for the FUNENTRY and FUNEXIT instructions of these callees in order to mimic passing parameters and returning results for address-taken variables. Figure 4(a) gives an example modified from Figure 3(a) by moving the four swap in- structions into a function, swap. For read side-effects, µpaq and µpcq are added before callsite 7 to represent the potential uses of a and c in swap. ...
Context 2
... that the versions i and j of an SSA variable a in different functions may be different. For example, Figure 4(c) illustrates the four inter-procedural value-flows Figure 3, as Andersen's flow-and context-insensitive pointer analysis is fast but imprecise. However, this representation allows imprecise points-to information to be refined by performing sparse whole-program flow-sensitive pointer analysis as in prior work [Hardekopf and Lin 2011;Nagaraj and Govindarajan 2013;Sui et al. 2016a;Ye et al. 2014b]. ...
Context 3
... the pre-analysis (for com- puting the sparse value-flow graph of the program) is sound, then the def-use chains built for all the address-taken variables are over-approximate. According to its inference rules in Figure 4, SUPA performs essentially a flow-sensitive analysis on-demand, by re- stricting the propagation of points-to information along the precomputed def-use chains, and falls back to the sound points-to information computed by the pre-analysis when running out of its given budgets. Thus, SUPA is sound if the pre-analysis is sound. ...
Context 4
... Figure 14(a) shows the average analysis time per query for all the pro- grams under a given budget, with about 0.18 seconds when B " 10000 and about 2.76 seconds when B " 200000. Both axes are logarithmic. ...

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