An overview of the Jahob analysis system: project goals and current status

Kuncak,; Rinard,

doi:10.1109/ipdps.2006.1639580

Cited by 14 publications

(12 citation statements)

References 68 publications

(63 reference statements)

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“…(i) It extends the Jahob framework [20] by handling mD arrays and floating point numbers; (ii) It performs all the preprocessing steps needed for translating loops in the format described in Section 5, for instance, finding read-and write-only arrays and checking that the guards are pairwise disjoint using the SMT solver Z3 [5]. (iii) Most importantly, it integrates the software package Aligator [17] for synthesizing loops and generating quantified array invariants and loop properties.…”

Section: Implementation and Experimentsmentioning

confidence: 94%

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Invariant and Type Inference for Matrices

Henzinger

Hottelier

Kovács

et al. 2010

Lecture Notes in Computer Science

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Abstract. We present a loop property generation method for loops iterating over multi-dimensional arrays. When used on matrices, our method is able to infer their shapes (also called types), such as upper-triangular, diagonal, etc. To generate loop properties, we first transform a nested loop iterating over a multidimensional array into an equivalent collection of unnested loops. Then, we infer quantified loop invariants for each unnested loop using a generalization of a recurrence-based invariant generation technique. These loop invariants give us conditions on matrices from which we can derive matrix types automatically using theorem provers. Invariant generation is implemented in the software package Aligator and types are derived by theorem provers and SMT solvers, including Vampire and Z3. When run on the Java matrix package JAMA, our tool was able to infer automatically all matrix types describing the matrix shapes guaranteed by JAMA's API.

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Section: Implementation and Experimentsmentioning

confidence: 94%

“…We implemented a tool that infers matrix loop properties as described in Sections 6 and 7. Our tool is implemented in the Jahob verification system [20]. It takes a Java program as its input, and returns a quantified matrix loop property for each loop from its input.…”

Section: Implementation and Experimentsmentioning

confidence: 99%

Invariant and Type Inference for Matrices

Henzinger

Hottelier

Kovács

et al. 2010

Lecture Notes in Computer Science

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“…We discuss our initial experience in using our implementation of BAPA to discharge verification conditions generated in the Jahob verification system (Kuncak and Rinard, 2006).…”

Section: Contributionsmentioning

confidence: 99%

“…Our initial experience with BAPA is in the context of the Jahob system (Kuncak and Rinard, 2006) for verifying data structure consistency of Java programs. Jahob parses Java source code annotated with formulas in Isabelle syntax written in comments, generates verification conditions, and uses decision procedures and theorem provers to discharge these verification conditions.…”

Section: Experience Using Our Decision Procedures For Bapamentioning

confidence: 99%

Deciding Boolean Algebra with Presburger Arithmetic

Kunčak¹,

Nguyen

Rinard

2006

J Autom Reasoning

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Abstract. We describe an algorithm for deciding the first-order multisorted theory BAPA, which combines 1) Boolean algebras of sets of uninterpreted elements (BA) and 2) Presburger arithmetic operations (PA). BAPA can express the relationship between integer variables and cardinalities of unbounded finite sets, and supports arbitrary quantification over sets and integers.Our original motivation for BAPA is deciding verification conditions that arise in the static analysis of data structure consistency properties. Data structures often use an integer variable to keep track of the number of elements they store; an invariant of such a data structure is that the value of the integer variable is equal to the number of elements stored in the data structure. When the data structure content is represented by a set, the resulting constraints can be captured in BAPA. BAPA formulas with quantifier alternations arise when verifying programs with annotations containing quantifiers, or when proving simulation relation conditions for refinement and equivalence of program fragments. Furthermore, BAPA constraints can be used for proving the termination of programs that manipulate data structures, as well as in constraint database query evaluation and loop invariant inference.We give a formal description of an algorithm for deciding BAPA. We analyze our algorithm and show that it has optimal alternating time complexity, and that the complexity of BAPA matches the complexity of PA. Because it works by a reduction to PA, our algorithm yields the decidability of a combination of sets of uninterpreted elements with any decidable extension of PA. When restricted to BA formulas, the algorithm can be used to decide BA in optimal alternating time. Furthermore, the algorithm can eliminate individual quantifiers from a formula with free variables and therefore perform projection onto a desirable set of variables.We have implemented our algorithm and used it to discharge verification conditions in the Jahob system for data structure consistency checking of Java programs; our experience suggest that a straightforward implementation of the algorithm is effective on non-trivial formulas as long as the number of set variables is small. We also report on a new algorithm for solving the quantifier-free fragment of BAPA.

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“…The related Jahob project [47] explores the use of a Java subset as an implementation language for verifying data structure consistency properties.…”

Section: A) Choice Of Implementation and Specification Languagesmentioning

confidence: 99%

Modular Pluggable Analyses for Data Structure Consistency

Kunčak¹,

Lam²,

Zee³

et al. 2006

IIEEE Trans. Software Eng.

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Abstract-Hob is a program analysis system that enables the focused application of multiple analyses to different modules in the same program. In our approach, each module encapsulates one or more data structures and uses membership in abstract sets to characterize how objects participate in data structures. Each analysis verifies that the implementation of the module 1) preserves important internal data structure consistency properties and 2) correctly implements a set algebra interface that characterizes the effects of operations on the data structure. Collectively, the analyses use the set algebra to 1) characterize how objects participate in multiple data structures and to 2) enable the inter-analysis communication required to verify properties that depend on multiple modules analyzed by different analyses.We implemented our system and deployed several pluggable analyses, including a flag analysis for modules in which abstract set membership is determined by a flag field in each object, a PALE shape analysis plugin, and a theorem proving plugin for analyzing arbitrarily complicated data structures. Our experience shows that our system can effectively 1) verify the consistency of data structures encapsulated within a single module and 2) combine analysis results from different analysis plugins to verify properties involving objects shared by multiple modules analyzed by different analyses.

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An overview of the Jahob analysis system: project goals and current status

Cited by 14 publications

References 68 publications

Invariant and Type Inference for Matrices

Invariant and Type Inference for Matrices

Deciding Boolean Algebra with Presburger Arithmetic

Modular Pluggable Analyses for Data Structure Consistency

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