Inductive Predicate Synthesis Modulo Programs (Extended)
A growing trend in program analysis is to encode verification conditions within the language of the input program. This simplifies the design of analysis tools by utilizing off-the-shelf verifiers, but makes communication with the underlying solver more challenging. Essentially, the analyzer operate...
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creator | Wesley, Scott Christakis, Maria Navas, Jorge A Trefler, Richard Wüstholz, Valentin Gurfinkel, Arie |
description | A growing trend in program analysis is to encode verification conditions
within the language of the input program. This simplifies the design of
analysis tools by utilizing off-the-shelf verifiers, but makes communication
with the underlying solver more challenging. Essentially, the analyzer operates
at the level of input programs, whereas the solver operates at the level of
problem encodings. To bridge this gap, the verifier must pass along proof-rules
from the analyzer to the solver. For example, an analyzer for concurrent
programs built on an inductive program verifier might need to declare
Owicki-Gries style proof-rules for the underlying solver. Each such proof-rule
further specifies how a program should be verified, meaning that the problem of
passing proof-rules is a form of invariant synthesis.
Similarly, many program analysis tasks reduce to the synthesis of pure,
loop-free Boolean functions (i.e., predicates), relative to a program. From
this observation, we propose Inductive Predicate Synthesis Modulo Programs
(IPS-MP) which extends high-level languages with minimal synthesis features to
guide analysis. In IPS-MP, unknown predicates appear under assume and assert
statements, acting as specifications modulo the program semantics. Existing
synthesis solvers are inefficient at IPS-MP as they target more general
problems. In this paper, we show that IPS-MP admits an efficient solution in
the Boolean case, despite being generally undecidable. Moreover, we show that
IPS-MP reduces to the satisfiability of constrained Horn clauses, which is less
general than existing synthesis problems, yet expressive enough to encode
verification tasks. We provide reductions from challenging verification tasks
-- such as parameterized model checking -- to IPS-MP. We realize these
reductions with an efficient IPS-MP-solver based on SeaHorn, and describe a
application to smart-contract verification. |
doi_str_mv | 10.48550/arxiv.2407.08455 |
format | Article |
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within the language of the input program. This simplifies the design of
analysis tools by utilizing off-the-shelf verifiers, but makes communication
with the underlying solver more challenging. Essentially, the analyzer operates
at the level of input programs, whereas the solver operates at the level of
problem encodings. To bridge this gap, the verifier must pass along proof-rules
from the analyzer to the solver. For example, an analyzer for concurrent
programs built on an inductive program verifier might need to declare
Owicki-Gries style proof-rules for the underlying solver. Each such proof-rule
further specifies how a program should be verified, meaning that the problem of
passing proof-rules is a form of invariant synthesis.
Similarly, many program analysis tasks reduce to the synthesis of pure,
loop-free Boolean functions (i.e., predicates), relative to a program. From
this observation, we propose Inductive Predicate Synthesis Modulo Programs
(IPS-MP) which extends high-level languages with minimal synthesis features to
guide analysis. In IPS-MP, unknown predicates appear under assume and assert
statements, acting as specifications modulo the program semantics. Existing
synthesis solvers are inefficient at IPS-MP as they target more general
problems. In this paper, we show that IPS-MP admits an efficient solution in
the Boolean case, despite being generally undecidable. Moreover, we show that
IPS-MP reduces to the satisfiability of constrained Horn clauses, which is less
general than existing synthesis problems, yet expressive enough to encode
verification tasks. We provide reductions from challenging verification tasks
-- such as parameterized model checking -- to IPS-MP. We realize these
reductions with an efficient IPS-MP-solver based on SeaHorn, and describe a
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within the language of the input program. This simplifies the design of
analysis tools by utilizing off-the-shelf verifiers, but makes communication
with the underlying solver more challenging. Essentially, the analyzer operates
at the level of input programs, whereas the solver operates at the level of
problem encodings. To bridge this gap, the verifier must pass along proof-rules
from the analyzer to the solver. For example, an analyzer for concurrent
programs built on an inductive program verifier might need to declare
Owicki-Gries style proof-rules for the underlying solver. Each such proof-rule
further specifies how a program should be verified, meaning that the problem of
passing proof-rules is a form of invariant synthesis.
Similarly, many program analysis tasks reduce to the synthesis of pure,
loop-free Boolean functions (i.e., predicates), relative to a program. From
this observation, we propose Inductive Predicate Synthesis Modulo Programs
(IPS-MP) which extends high-level languages with minimal synthesis features to
guide analysis. In IPS-MP, unknown predicates appear under assume and assert
statements, acting as specifications modulo the program semantics. Existing
synthesis solvers are inefficient at IPS-MP as they target more general
problems. In this paper, we show that IPS-MP admits an efficient solution in
the Boolean case, despite being generally undecidable. Moreover, we show that
IPS-MP reduces to the satisfiability of constrained Horn clauses, which is less
general than existing synthesis problems, yet expressive enough to encode
verification tasks. We provide reductions from challenging verification tasks
-- such as parameterized model checking -- to IPS-MP. We realize these
reductions with an efficient IPS-MP-solver based on SeaHorn, and describe a
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within the language of the input program. This simplifies the design of
analysis tools by utilizing off-the-shelf verifiers, but makes communication
with the underlying solver more challenging. Essentially, the analyzer operates
at the level of input programs, whereas the solver operates at the level of
problem encodings. To bridge this gap, the verifier must pass along proof-rules
from the analyzer to the solver. For example, an analyzer for concurrent
programs built on an inductive program verifier might need to declare
Owicki-Gries style proof-rules for the underlying solver. Each such proof-rule
further specifies how a program should be verified, meaning that the problem of
passing proof-rules is a form of invariant synthesis.
Similarly, many program analysis tasks reduce to the synthesis of pure,
loop-free Boolean functions (i.e., predicates), relative to a program. From
this observation, we propose Inductive Predicate Synthesis Modulo Programs
(IPS-MP) which extends high-level languages with minimal synthesis features to
guide analysis. In IPS-MP, unknown predicates appear under assume and assert
statements, acting as specifications modulo the program semantics. Existing
synthesis solvers are inefficient at IPS-MP as they target more general
problems. In this paper, we show that IPS-MP admits an efficient solution in
the Boolean case, despite being generally undecidable. Moreover, we show that
IPS-MP reduces to the satisfiability of constrained Horn clauses, which is less
general than existing synthesis problems, yet expressive enough to encode
verification tasks. We provide reductions from challenging verification tasks
-- such as parameterized model checking -- to IPS-MP. We realize these
reductions with an efficient IPS-MP-solver based on SeaHorn, and describe a
application to smart-contract verification.</abstract><doi>10.48550/arxiv.2407.08455</doi><oa>free_for_read</oa></addata></record> |
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subjects | Computer Science - Software Engineering |
title | Inductive Predicate Synthesis Modulo Programs (Extended) |
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