Comments (1)
One particularly interesting method is by using so-called "Logical lattices", outlined in Combining Abstract Interpreters. A logical lattice is one where the order is implication, with the base set being the set of finite conjunctions over some theory. They further show a method to combine multiple lattices (c.f. #42 ) which results in an extremely precise lattice (more precise than the reduced product), assuming some suitable conditions (convexity, stably infinite input lattices, and disjoint theories (apart from equality)). The downside is that the join and existential operators, at least in their implementation, have O(n^2) complexity, but that looks like it can be countered by laziness.
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Related Issues (20)
- Stateful transformation causes non-termination in Hoopl analysis.
- Hoopl not mentioned on "Library submission" page HOT 3
- Clean up the repository HOT 5
- Please update cabal file on hackage to point to this issue tracker HOT 3
- Decide on coding style HOT 23
- Migrate tests from test-framework to tasty HOT 4
- Who are maintainers of Hoopl? HOT 13
- Update website in cabal file HOT 3
- Runtime error caused by fromJust in module Dataflow HOT 2
- Interleaving of multiple passes HOT 1
- Interleaving multiple transfer functions using the same type of fact? HOT 1
- Passes using multiple types of facts (aka snooping) HOT 1
- Upload tag v3.10.2.2 to Hackage HOT 3
- Conditional jumps with fall-through not always ordered properly by postorder_dfs HOT 4
- Also revise test deps to allow base 4.11
- hoopl-3.10.2.2 test suite does not compile
- test build failure HOT 2
- Hoopl collection classes could use enummapset? HOT 6
- Inconsistency between paper and library
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