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@leventeBajczi leventeBajczi commented Nov 13, 2025

  • Can parse non-variable references if they are referencing a literal-offset (currently only 0) dereference
  • Can parse GNU C builtins
  • Can parse ambiguous expressions such as (len) & a ( -- is it a cast? is it a bitwise AND? i hate C)
  • Can interpret GNU C builtins for atomic accesses

@leventeBajczi
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@csanadtelbisz, if we were able to change the StartLabel/JoinLabel handles to expressions (i'm okay with constraining them to LHS expressions, i.e., RefExpr and DerefExpr), we could now parse libvsync tasks.

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@csanadtelbisz, if we were able to change the StartLabel/JoinLabel handles to expressions (i'm okay with constraining them to LHS expressions, i.e., RefExpr and DerefExpr), we could now parse libvsync tasks.

I do not see any obstacle: we would only need to add an extra case for creating a memoryassignment when necessary. I am expecting some changes in both the LTS-based analysis (XcfaState), OC checker event graph mapping and the monolithic conversion, but none of them should be too challenging. Shall I do it or are you working on it?

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Please do it if you have the time, I won't really be able to work on this.
I'll happily do the atomic builtin mappings if you'd like me to, though!

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❗ Please modify build.gradle.kts to contain a later version than 6.26.2. Current version is 6.26.2.

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Benchexec test report for a selection of SV-Benchmarks (correct / incorrect / all):

Rundefinition BOUNDED CEGAR HORN
SV-COMP25_no-data-race ✅ (311 / 0 / 583) HTML/CSV ✅ (311 / 0 / 545) HTML/CSV
SV-COMP25_no-overflow ❓ (0 / 0 / 393) HTML/CSV ❓ (0 / 0 / 375) HTML/CSV ❓ (0 / 0 / 138) HTML/CSV
SV-COMP25_termination ❓ (0 / 0 / 610) HTML/CSV ❓ (0 / 0 / 617) HTML/CSV ✅ (6 / 0 / 76) HTML/CSV
SV-COMP25_unreach-call ❗ (1 / 1 / 480) HTML/CSV ❗ (1 / 1 / 535) HTML/CSV ✅ (19 / 0 / 181) HTML/CSV
SV-COMP25_valid-memcleanup ❓ (0 / 0 / 66) HTML/CSV ❓ (0 / 0 / 66) HTML/CSV ❓ (0 / 0 / 66) HTML/CSV
SV-COMP25_valid-memsafety ❓ (0 / 0 / 662) HTML/CSV ❓ (0 / 0 / 653) HTML/CSV ✅ (31 / 0 / 316) HTML/CSV

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3 participants