Inferring Loop Invariants using Postconditions

One of the obstacles in automatic program proving is to obtain suitable loop invariants. The invariant of a loop is a weakened form of its postcondition (the loop's goal, also known as its contract); the present work takes advantage of this observation by using the postcondition as the basis for invariant inference, using various heuristics such as "uncoupling" which prove useful in many important algorithms. Thanks to these heuristics, the technique is able to infer invariants for a large variety of loop examples. We present the theory behind the technique, its implementation (freely available for download and currently relying on Microsoft Research's Boogie tool), and the results obtained.Comment: Slightly revised versio

Inferring Concise Specifications of APIs

Modern software relies on libraries and uses them via application programming interfaces (APIs). Correct API usage as well as many software engineering tasks are enabled when APIs have formal specifications. In this work, we analyze the implementation of each method in an API to infer a formal postcondition. Conventional wisdom is that, if one has preconditions, then one can use the strongest postcondition predicate transformer (SP) to infer postconditions. However, SP yields postconditions that are exponentially large, which makes them difficult to use, either by humans or by tools. Our key idea is an algorithm that converts such exponentially large specifications into a form that is more concise and thus more usable. This is done by leveraging the structure of the specifications that result from the use of SP. We applied our technique to infer postconditions for over 2,300 methods in seven popular Java libraries. Our technique was able to infer specifications for 75.7% of these methods, each of which was verified using an Extended Static Checker. We also found that 84.6% of resulting specifications were less than 1/4 page (20 lines) in length. Our technique was able to reduce the length of SMT proofs needed for verifying implementations by 76.7% and reduced prover execution time by 26.7%

SPEEDY: An Eclipse-based IDE for invariant inference

SPEEDY is an Eclipse-based IDE for exploring techniques that assist users in generating correct specifications, particularly including invariant inference algorithms and tools. It integrates with several back-end tools that propose invariants and will incorporate published algorithms for inferring object and loop invariants. Though the architecture is language-neutral, current SPEEDY targets C programs. Building and using SPEEDY has confirmed earlier experience demonstrating the importance of showing and editing specifications in the IDEs that developers customarily use, automating as much of the production and checking of specifications as possible, and showing counterexample information directly in the source code editing environment. As in previous work, automation of specification checking is provided by back-end SMT solvers. However, reducing the effort demanded of software developers using formal methods also requires a GUI design that guides users in writing, reviewing, and correcting specifications and automates specification inference.Comment: In Proceedings F-IDE 2014, arXiv:1404.578

Reducing the Number of Annotations in a Verification-oriented Imperative Language

Automated software verification is a very active field of research which has made enormous progress both in theoretical and practical aspects. Recently, an important amount of research effort has been put into applying these techniques on top of mainstream programming languages. These languages typically provide powerful features such as reflection, aliasing and polymorphism which are handy for practitioners but, in contrast, make verification a real challenge. In this work we present Pest, a simple experimental, while-style, multiprocedural, imperative programming language which was conceived with verifiability as one of its main goals. This language forces developers to concurrently think about both the statements needed to implement an algorithm and the assertions required to prove its correctness. In order to aid programmers, we propose several techniques to reduce the number and complexity of annotations required to successfully verify their programs. In particular, we show that high-level iteration constructs may alleviate the need for providing complex loop annotations.Comment: 15 pages, 8 figure

Survey of annotation generators for deductive verifiers

Deductive verifiers require intensive user interaction in the form of writing precise specifications, thereby limiting their use in practice. While many solutions have been proposed to generate specifications, their evaluations and comparisons to other tools are limited. As a result, it is unclear what the best approaches for specification inference are and how these impact the overall specification writing process. In this paper we take steps to address this problem by providing an overview of specification inference tools that can be used for deductive verification of Java programs. For each tool, we discuss its approach to specification inference and identify its advantages and disadvantages. Moreover, we identify the types of specifications that it infers and use this to estimate the impact of the tool on the overall specification writing process. Finally, we identify the ideal features of a specification generator and discuss important challenges for future research.</p

Análisis de recursos de programas enteros y abstractos

Tesis inédita de la Universidad Complutense de Madrid, Facultad de Informática, Departamento de Sistemas lnformáticos y de Computación, leída el 27-05-2022Since the beginning of automated computing in the middle of the last century, the development of computer science has been linked to an increasing importance in all areas of the current society. The inclusion of computer science processes in everyday life and, in particular, its inclusion in critical situations, cannot go linked only to the generation of hardware and software, but also to the analysis and verification of all its components. While hardware analysis is crucial for the generation and maintenance of the computation infrastructure, as it is able to detect or predict components that can have a wrong behavior, software analysis focuses on analyzing the behavior of computer programs to address properties such as security, correctness or optimality. Depending on the type of analysis applied to the software, we can detect potential vulnerabilities in the code, find incorrect specifications, apply optimizations based on the maximun and minimun cost of the programs, calculate the resource consumption of a program..Desde el comienzo de la computación automática a mediados del siglo pasado, el avance de la informática ha ido ligado a una cada vez mayor importancia en todos los ámbitos d ela sociedad actual. La inclusión de procesos informáticos en la vida cotidiana y, en particular, su inclusión en situaciones críticas, no puede ir ligada solo a la generación del hardware el software, sino también al análisis y verificación de todos sus componentes. Mientras que el análisis de hardware es crucial para la generación de la infraestructura informática y el mantenimiento de la misma, detectando o prediciendo componentes que puedan funcionar de manera errónea, el análisis de software se enfoca hacia el análisis del comportamiento de los programas informáticos para abordar propiedades como la seguridad, la corrección o la optimalidad. Dependiendo del tipo de análisis aplicado al software, podremos detectar fragmentos de código potencialmente vulnerables, especificaciones incorrectas, aplicar optimizaciones en base al coste máximo y mínimo de los programas, calcular el consumo de recursos de un programa...Fac. de InformáticaTRUEunpu