Twinning automata and regular expressions for string static analysis

In this paper we formalize and prove the soundness of Tarsis, a new abstract domain based on the abstract interpretation theory that approximates string values through finite state automata. The main novelty of Tarsis is that it works over an alphabet of strings instead of single characters. On the one hand, such approach requires a more complex and refined definition of the widening operator, and the abstract semantics of string operators. On the other hand, it is in position to obtain strictly more precise results than than state-of-the-art approaches. We implemented a prototype of Tarsis, and we applied it on some case studies taken from some of the most popular Java libraries manipulating string values. The experimental results confirm that Tarsis is in position to obtain strictly more precise results than existing analyses

Twinning Automata and Regular Expressions for String Static Analysis

In this paper we formalize Tarsis, a new abstract domain based on the abstract interpretation theory that approximates string values through finite state automata. The main novelty of Tarsis is that it works over an alphabet of strings instead of single characters. On the one hand, such an approach requires a more complex and refined definition of the widening operator, and the abstract semantics of string operators. On the other hand, it is in position to obtain strictly more precise results than state-of-the-art approaches. We implemented a prototype of Tarsis, and we applied it to some case studies taken from some of the most popular Java libraries manipulating string values. The experimental results confirm that Tarsis is in position to obtain strictly more precise results than existing analyses

SUNNY-CP : a Sequential CP Portfolio Solver

International audienceThe Constraint Programming (CP) paradigm allows to model and solve Constraint Satisfaction / Optimization Problems (CSPs / COPs). A CP Portfolio Solver is a particular constraint solver that takes advantage of a portfolio of different CP solvers in order to solve a given problem by properly exploiting Algorithm Selection techniques. In this work we present sunny-cp: a CP portfolio for solving both CSPs and COPs that turned out to be competitive also in the MiniZinc Challenge, the reference competition for CP solvers

Portfolio Approaches for Constraint Optimization Problems

International audienceWithin the Constraints Satisfiability Problems (CSP) context, a methodology that has proved to be particularly performant consists in using a portfolio of different constraint solvers. Nevertheless, comparatively few studies and investigations has been done in the world of Constraint Optimization Problems (COP). In this work, we provide a generalization to COP as well as an empirical evaluation of different state of the art existing CSP portfolio approaches properly adapted to deal with COP. Experimental results confirm the effectiveness of portfolios even in the optimization field, and could give rise to some interesting future research

JSetL User's Manual - Version 2.3

This manual describes JSetL 2.3, a Java library that offers a number of facilities to support declarative programming like those usually found in constraint logic programming languages: logical variables, list and set data structures (possibly partially specfied), unfication, constraint solving over integers and sets, nondeterminism. JSetL is intended to be used as a general-purpose tool, not devoted to any specific application. The manual describes all the features of JSetL and it shows, through simple examples, how to use them. JSetL has been developed at the Department of Mathematics of the University of Parma (Italy). It is completely written in Java. The full Java code of the JSetL library, along with sample programs and related material, is available at the JSetL WEB page http://cmt.math.unipr.it/jsetl.html

Sequential Time Splitting and Bounds Communication for a Portfolio of Optimization Solvers

Scheduling a subset of solvers belonging to a given portfolio has proven to be a good strategy when solving Constraint Satisfaction Problems (CSPs). In this paper, we show that this approach can also be effective for Constraint Optimization Problems (COPs). Unlike CSPs, sequential execution of optimization solvers can communicate information in the form of bounds to improve the performance of the following solvers. We provide a hybrid and flexible portfolio approach that combines static and dynamic time splitting for solving a given COP. Empirical evaluations show the approach is promising and sometimes even able to outperform the best solver of the porfolio. \ua9 2014 Springer International Publishing Switzerland

Propagating Regular membership with dashed strings

Using dashed strings is an approach recently introduced in Constraint Programming (CP) to represent the domain of string variables, when solving combinatorial problems with string constraints. One of the most important string constraints is that of regular membership: regular (x, R) imposes string x to be a member of the regular language defined by automaton R. The regular constraint is useful for specifying complex constraints on fixed length finite sequences, and regularly appears in CP models. Dealing with regular is also desirable in software testing and verification, because regular expressions are often used in modern programming languages for pattern matching. In this paper, we define a regular propagator for dashed string solvers. We show that this propagator, implemented in the G-Strings solver, is substantially better than the current state-of-the-art. We also demonstrate that many regular constraints appearing in string solving benchmarks can actually be tackled by dashed strings solvers without explicitly using REGULAR

Sweep-based propagation for string constraint solving

Solving constraints over strings is an emerging important field. Recently, a Constraint Programming approach based on dashed strings has been proposed to enable a compact domain representation for potentially large bounded-length string variables. In this paper, we present a more efficient algorithm for propagating equality (and related constraints) over dashed strings. We call this propagation sweep-based. Experimental evidences show that sweep-based propagation is able to significantly outperform state-of-the-art approaches for string constraint solving

Propagating lex, find and replace with dashed strings

Dashed strings have been recently proposed in Constraint Programming to represent the domain of string variables when solving combinatorial problems over strings. This approach showed promising performance on some classes of string problems, involving constraints like string equality and concatenation. However, there are a number of string constraints for which no propagator has yet been defined. In this paper, we show how to propagate lexicographic ordering (lex), find and replace with dashed strings. All of these are fundamental string operations: lex is the natural total order over strings, while find and replace are frequently used in string manipulation. We show that these propagators, that we implemented in G-Strings solver, allows us to be competitive with state-of-the-art approaches

Dashed strings for string constraint solving

String processing is ubiquitous across computer science, and arguably more so in web programming — where it is also a critical part of security issues such as injection attacks. In recent years, a number of string solvers have been developed to solve combinatorial problems involving string variables and constraints. We examine the dashed string approach to string constraint solving, which represents an unknown string as a sequence of blocks of characters with bounds on their cardinalities. The solving approach relies on propagation of information about the blocks of characters that arise from reasoning about the constraints in which they occur. This approach shows promising performance on many benchmarks involving constraints like string length, equality, concatenation, and regular expression membership. In this paper, we formally review the definition, the properties and the use of dashed strings for string constraint solving, and we provide an empirical validation that confirms the effectiveness of this approach