Examinando Presentaciones a Congresos por Materia "ANALISIS DE FALLAS"
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- Ponencia en CongresoAnalysis of invariants for efficient bounded verification(2010-07) Galeotti, Juan Pablo; Rosner, Nicolás; López Pombo, Carlos G.; Frías, Marcelo"SAT-based bounded veri cation of annotated code consists of translating the code together with the annotations to a propositional formula, and analyzing the formula for speci cation violations using a SAT-solver. If a violation is found, an execution trace exposing the error is exhibited. Code involving linked data structures with intricate invariants is particularly hard to analyze using these techniques. In this article we present TACO, a prototype tool which implements a novel, general and fully automated technique for the SAT-based analysis of JML-annotated Java sequential programs dealing with complex linked data structures. We instrument code analysis with a symmetry-breaking predicate that allows for the parallel, automated computation of tight bounds for Java elds. Experiments show that the translations to propositional formulas require signi cantly less propositional variables, leading in the experiments we have carried out to an improvement on the e ciency of the analysis of orders of magnitude, compared to the non instrumented SAT-based analysis. We show that, in somecases, our tool can uncover bugs that cannot be detected by state-of-the-art tools based on SAT-solving, model checking or SMT-solving."
- Ponencia en CongresoAutomated workarounds from Java Program specifications based on SAT solving(2017) Uva, Marcelo; Ponzio, Pablo; Regis, Germán; Aguirre, Nazareno; Frías, Marcelo"The failures that bugs in software lead to can sometimes be bypassed by the so called workarounds: when a (faulty) routine fails, alternative routines that the system offers can be used in place of the failing one, to circumvent the failure. Previous works have exploited this workarounds notion to automatically recover from runtime failures in some application domains. However, existing approaches that compute workarounds automatically either require the user to manually build an abstract model of the software under consideration, or to provide equivalent sequences of operations from which workarounds are computed, diminishing the automation of workaround-based system recovery. In this paper, we present two techniques that automatically compute workarounds from Java code equipped with formal specifications, avoiding abstract software models and user provided equivalences. These techniques employ SAT solving to compute workarounds on concrete program state characterizations. The first employs SAT solving to compute traditional workarounds, while the second directly exploits SAT solving to circumvent a failing method, building a state that mimics the (correct) behaviour of this failing routine. Our experiments, based on case studies involving implementations of collections and a library for date arithmetic, enable us to show that the techniques can effectively compute workarounds from complex contracts in an important number of cases, in time that makes them feasible to be used for run time repairs."
- Ponencia en CongresoFLACK: Counterexample-guided fault localization for alloy models(2021) Zheng, Guolong; Nguyen, Thanh Vu; Gutiérrez Brida, Simón; Regis, Germán; Frías, Marcelo; Aguirre, Nazareno; Bagher, Hamid"Fault localization is a practical research topic that helps developers identify code locations that might cause bugs in a program. Most existing fault localization techniques are designed for imperative programs (e.g., C and Java) and rely on analyzing correct and incorrect executions of the program to identify suspicious statements. In this work, we introduce a fault localization approach for models written in a declarative language, where the models are not “executed,” but rather converted into a logical formula and solved using backend constraint solvers. We present FLACK, a tool that takes as input an Alloy model consisting of some violated assertion and returns a ranked list of suspicious expressions contributing to the assertion violation. The key idea is to analyze the differences between counterexamples, i.e., instances of the model that do not satisfy the assertion, and instances that do satisfy the assertion to find suspicious expressions in the input model. The experimental results show that FLACK is efficient (can handle complex, real world Alloy models with thousand lines of code within 5 seconds), accurate (can consistently rank buggy expressions in the top 1.9% of the suspicious list), and useful (can often narrow down the error to the exact location within the suspicious expressions)."