Local Completeness Logic on Kleene Algebra with Tests

Milanese, Marco; Ranzato, Francesco

doi:10.1007/978-3-031-22308-2_16

Cited by 6 publications

(4 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, Partial Incorrectness Logic is applied to nondeterministic programs whereas our logic is applied to deterministic programs. Besides the aforementioned Incorrectness Logic (IL) [6][7][8], Adversarial Logic (AL) [9], Local Completeness Logic (LCL) [10,11], Exact Separation Logic (ESL) [12], Outcome Logic (OL) [13] and Hyper Hoare Logic (HHL) [14], there are more practical approach to nding bugs using formal methods. e use of a counterexample generated by an SMT solver for error localization was described in [26].…”

Section: Related Workmentioning

confidence: 99%

“…Reasoning about incorrectness using formal methods is an important task nowadays [5,6]. Special logics such as Incorrectness Logic (IL) [6][7][8], Adversarial Logic (AL) [9], Local Completeness Logic (LCL) [10,11], Exact Separation Logic (ESL) [12], Outcome Logic (OL) [13] and Hyper Hoare Logic (HHL) [14] have recently been proposed to address it. However, these logics have two disadvantages.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Logic for reasoning about bugs in loops over data sequences (IFIL)

Kondratyev

2023

Model. anal. inf. sist.

View full text Add to dashboard Cite

Classic deductive verification is not focused on reasoning about program incorrectness. Reasoning about program incorrectness using formal methods is an important problem nowadays. Special logics such as Incorrectness Logic, Adversarial Logic, Local Completeness Logic, Exact Separation Logic and Outcome Logic have recently been proposed to address it. However, these logics have two disadvantages. One is that they are based on under-approximation approaches, while classic deductive verification is based on the over-approximation approach. One the other hand, the use of the classic approach requires defining loop invariants in a general case. The second disadvantage is that the use of generalized inference rules from these logics results in having to prove too complex formulas in simple cases. Our contribution is a new logic for solving these problems in the case of loops over data sequences. These loops are referred to as finite iterations. We call the proposed logic the Incorrectness Finite Iteration Logic (IFIL). We avoid defining invariants of finite iterations using a symbolic replacement of these loops with recursive functions. Our logic is based on special inference rules for finite iterations. These rules allow generating formulas with recursive functions corresponding to finite iterations. The validity of these formulas may indicate the presence of bugs in the finite iterations. This logic has been implemented in a new version of the C-lightVer system for deductive verification of C programs.

show abstract

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Logic for reasoning about bugs in loops over data sequences (IFIL)

Kondratyev

2023

Model. anal. inf. sist.

View full text Add to dashboard Cite

show abstract

“…This is provable by Hoare logic as {𝑛 < 0 ∧ 𝑓 = 1} fact {false} but then we need two different logics to prove incorrectness, the main motivation for recent work on combining logics (e.g. [9,58,61,98], etc). This is also provable by the natural transformational under approximation logic which extends incorrectness logic to nontermination, that is, in the assertional form of Sect.…”

Section: I343mentioning

confidence: 99%

“…(The relational semantics could have been proved to be the abstraction of a finite and infinite trace semantics [11].) The natural relational semantics is isomorphic to Plotkin's natural denotational semantics in D → ℘(D ) [61] by considering the right image 𝝀𝜎 . {𝜎 ′ ∈ Σ | ⟨𝜎, 𝜎 ′ ⟩ ∈ S }.…”

Section: Calculational Design Of [In]correctness Transformational Pro...mentioning

confidence: 99%