Abstract Interpretation-based verification/certification in the ciaoPP system

CiaoPP is the abstract interpretation-based preprocessor of the Ciao multi-paradigm (Constraint) Logic Programming system. It uses modular, incremental abstract interpretation as a fundamental tool to obtain information about programs. In CiaoPP, the semantic approximations thus produced have been applied to perform high- and low-level optimizations during program compilation, including transformations such as múltiple abstract specialization, parallelization, partial evaluation, resource usage control, and program verification. More recently, novel and promising applications of such semantic approximations are being applied in the more general context of program development such as program verification. In this work, we describe our extensión of the system to incorpórate Abstraction-Carrying Code (ACC), a novel approach to mobile code safety. ACC follows the standard strategy of associating safety certificates to programs, originally proposed in Proof Carrying- Code. A distinguishing feature of ACC is that we use an abstraction (or abstract model) of the program computed by standard static analyzers as a certifícate. The validity of the abstraction on the consumer side is checked in a single-pass by a very efficient and specialized abstractinterpreter. We have implemented and benchmarked ACC within CiaoPP. The experimental results show that the checking phase is indeed faster than the proof generation phase, and that the sizes of certificates are reasonable. Moreover, the preprocessor is based on compile-time (and run-time) tools for the certification of CLP programs with resource consumption assurances

Experiments with a Convex Polyhedral Analysis Tool for Logic Programs

Convex polyhedral abstractions of logic programs have been found very useful in deriving numeric relationships between program arguments in order to prove program properties and in other areas such as termination and complexity analysis. We present a tool for constructing polyhedral analyses of (constraint) logic programs. The aim of the tool is to make available, with a convenient interface, state-of-the-art techniques for polyhedral analysis such as delayed widening, narrowing, "widening up-to", and enhanced automatic selection of widening points. The tool is accessible on the web, permits user programs to be uploaded and analysed, and is integrated with related program transformations such as size abstractions and query-answer transformation. We then report some experiments using the tool, showing how it can be conveniently used to analyse transition systems arising from models of embedded systems, and an emulator for a PIC microcontroller which is used for example in wearable computing systems. We discuss issues including scalability, tradeoffs of precision and computation time, and other program transformations that can enhance the results of analysis.Comment: Paper presented at the 17th Workshop on Logic-based Methods in Programming Environments (WLPE2007

SMT-based Model Checking for Recursive Programs

We present an SMT-based symbolic model checking algorithm for safety verification of recursive programs. The algorithm is modular and analyzes procedures individually. Unlike other SMT-based approaches, it maintains both "over-" and "under-approximations" of procedure summaries. Under-approximations are used to analyze procedure calls without inlining. Over-approximations are used to block infeasible counterexamples and detect convergence to a proof. We show that for programs and properties over a decidable theory, the algorithm is guaranteed to find a counterexample, if one exists. However, efficiency depends on an oracle for quantifier elimination (QE). For Boolean Programs, the algorithm is a polynomial decision procedure, matching the worst-case bounds of the best BDD-based algorithms. For Linear Arithmetic (integers and rationals), we give an efficient instantiation of the algorithm by applying QE "lazily". We use existing interpolation techniques to over-approximate QE and introduce "Model Based Projection" to under-approximate QE. Empirical evaluation on SV-COMP benchmarks shows that our algorithm improves significantly on the state-of-the-art.Comment: originally published as part of the proceedings of CAV 2014; fixed typos, better wording at some place

A generic framework for context-sensitive analysis of modular programs

Context-sensitive analysis provides information which is potentially more accurate than that provided by context-free analysis. Such information can then be applied in order to validate/debug the program and/or to specialize the program obtaining important improvements. Unfortunately, context-sensitive analysis of modular programs poses important theoretical and practical problems. One solution, used in several proposals, is to resort to context-free analysis. Other proposals do address context-sensitive analysis, but are only applicable when the description domain used satisfies rather restrictive properties. In this paper, we argüe that a general framework for context-sensitive analysis of modular programs, Le., one that allows using all the domains which have proved useful in practice in the non-modular setting, is indeed feasible and very useful. Driven by our experience in the design and implementation of analysis and specialization techniques in the context of CiaoPP, the Ciao system preprocessor, in this paper we discuss a number of design goals for context-sensitive analysis of modular programs as well as the problems which arise in trying to meet these goals. We also provide a high-level description of a framework for analysis of modular programs which does substantially meet these objectives. This framework is generic in that it can be instantiated in different ways in order to adapt to different contexts. Finally, the behavior of the different instantiations w.r.t. the design goals that motivate our work is also discussed

Heap Abstractions for Static Analysis

Heap data is potentially unbounded and seemingly arbitrary. As a consequence, unlike stack and static memory, heap memory cannot be abstracted directly in terms of a fixed set of source variable names appearing in the program being analysed. This makes it an interesting topic of study and there is an abundance of literature employing heap abstractions. Although most studies have addressed similar concerns, their formulations and formalisms often seem dissimilar and some times even unrelated. Thus, the insights gained in one description of heap abstraction may not directly carry over to some other description. This survey is a result of our quest for a unifying theme in the existing descriptions of heap abstractions. In particular, our interest lies in the abstractions and not in the algorithms that construct them. In our search of a unified theme, we view a heap abstraction as consisting of two features: a heap model to represent the heap memory and a summarization technique for bounding the heap representation. We classify the models as storeless, store based, and hybrid. We describe various summarization techniques based on k-limiting, allocation sites, patterns, variables, other generic instrumentation predicates, and higher-order logics. This approach allows us to compare the insights of a large number of seemingly dissimilar heap abstractions and also paves way for creating new abstractions by mix-and-match of models and summarization techniques.Comment: 49 pages, 20 figure

An assertion language for constraint logic programs

In an advanced program development environment, such as that discussed in the introduction of this book, several tools may coexist which handle both the program and information on the program in different ways. Also, these tools may interact among themselves and with the user. Thus, the different tools and the user need some way to communicate. It is our design principie that such communication be performed in terms of assertions. Assertions are syntactic objects which allow expressing properties of programs. Several assertion languages have been used in the past in different contexts, mainly related to program debugging. In this chapter we propose a general language of assertions which is used in different tools for validation and debugging of constraint logic programs in the context of the DiSCiPl project. The assertion language proposed is parametric w.r.t. the particular constraint domain and properties of interest being used in each different tool. The language proposed is quite general in that it poses few restrictions on the kind of properties which may be expressed. We believe the assertion language we propose is of practical relevance and appropriate for the different uses required in the tools considered

Using global analysis, partial specifications, and an extensible assertion language for program validation and debugging

We discuss a framework for the application of abstract interpretation as an aid during program development, rather than in the more traditional application of program optimization. Program validation and detection of errors is first performed statically by comparing (partial) specifications written in terms of assertions against information obtained from (global) static analysis of the program. The results of this process are expressed in the user assertion language. Assertions (or parts of assertions) which cannot be checked statically are translated into run-time tests. The framework allows the use of assertions to be optional. It also allows using very general properties in assertions, beyond the predefined set understandable by the static analyzer and including properties defined by user programs. We also report briefly on an implementation of the framework. The resulting tool generates and checks assertions for Prolog, CLP(R), and CHIP/CLP(fd) programs, and integrates compile-time and run-time checking in a uniform way. The tool allows using properties such as types, modes, non-failure, determinacy, and computational cost, and can treat modules separately, performing incremental analysis

Verification of Java Bytecode using Analysis and Transformation of Logic Programs

State of the art analyzers in the Logic Programming (LP) paradigm are nowadays mature and sophisticated. They allow inferring a wide variety of global properties including termination, bounds on resource consumption, etc. The aim of this work is to automatically transfer the power of such analysis tools for LP to the analysis and verification of Java bytecode (JVML). In order to achieve our goal, we rely on well-known techniques for meta-programming and program specialization. More precisely, we propose to partially evaluate a JVML interpreter implemented in LP together with (an LP representation of) a JVML program and then analyze the residual program. Interestingly, at least for the examples we have studied, our approach produces very simple LP representations of the original JVML programs. This can be seen as a decompilation from JVML to high-level LP source. By reasoning about such residual programs, we can automatically prove in the CiaoPP system some non-trivial properties of JVML programs such as termination, run-time error freeness and infer bounds on its resource consumption. We are not aware of any other system which is able to verify such advanced properties of Java bytecode