Imperative Programming Research Articles

LOIS: syntax and semantics

We present the semantics of an imperative programming language called LOIS (Looping Over Infinite Sets), which allows iterating through certain infinite sets, in finite time. Our semantics intuitively correspond to execution of infinitely many threads in parallel. This allows to merge the power of abstract mathematical constructions into imperative programming. Infinite sets are internally represented using first order formulas over some underlying logical structure, and SMT solvers are employed to evaluate programs.

Coming to terms with quantified reasoning

The theory of finite term algebras provides a natural framework to describe the semantics of functional languages. The ability to efficiently reason about term algebras is essential to automate program analysis and verification for functional or imperative programs over inductively defined data types such as lists and trees. However, as the theory of finite term algebras is not finitely axiomatizable, reasoning about quantified properties over term algebras is challenging. In this paper we address full first-order reasoning about properties of programs manipulating term algebras, and describe two approaches for doing so by using first-order theorem proving. Our first method is a conservative extension of the theory of term alge- bras using a finite number of statements, while our second method relies on extending the superposition calculus of first-order theorem provers with additional inference rules. We implemented our work in the first-order theorem prover Vampire and evaluated it on a large number of inductive datatype benchmarks, as well as game theory constraints. Our experimental results show that our methods are able to find proofs for many hard problems previously unsolved by state-of-the-art methods. We also show that Vampire implementing our methods outperforms existing SMT solvers able to deal with inductive data types.

Stateful manifest contracts

This paper studies hybrid contract verification for an imperative higher-order language based on a so-called manifest contract system . In manifest contract systems, contracts are part of static types and contract verification is hybrid in the sense that some contracts are statically verified, typically by subtyping, but others are dynamically by casts. It is, however, not trivial to extend existing manifest contract systems, which have been designed mostly for pure functional languages, to imperative features, mainly because of the lack of flow-sensitivity, which should be taken into account in verifying imperative programs statically. We develop an imperative higher-order manifest contract system λ ref H for flow-sensitive hybrid contract verification. We introduce a computational variant of Nanevski et al's Hoare types, which are flow-sensitive types to represent pre- and postconditions of impure computation. Our Hoare types are computational in the sense that pre- and postconditions are given by Booleans in the same language as programs so that they are dynamically verifiable. λ ref H also supports refinement types as in existing manifest contract systems to describe flow-insensitive, state-independent contracts of pure computation. While it is desirable that any-possibly state-manipulating-predicate can be used in contracts, abuse of stateful operations will break the system. To control stateful operations in contracts, we introduce a region-based effect system, which allows contracts in refinement types and computational Hoare types to manipulate states, as long as they are observationally pure and read-only, respectively. We show that dynamic contract checking in our calculus is consistent with static typing in the sense that the final result obtained without dynamic contract violations satisfies contracts in its static type. It in particular means that the state after stateful computations satisfies their postconditions. As in some of prior manifest contract systems, static contract verification in this work is "post facto," that is, we first define our manifest contract system so that all contracts are checked at run time, formalize conditions when dynamic checks can be removed safely, and show that programs with and without such removable checks are contextually equivalent. We also apply the idea of post facto verification to region-based local reasoning, inspired by the frame rule of Separation Logic.

On the Minimization Problem for Sequential Programs

First-order program schemata is one of the simplest models of sequential imperative programs intended for solving verification and optimization problems. We consider the decidable relation of logical-thermal equivalence of these schemata and the problem of their size minimization while preserving logical-thermal equivalence. We prove that this problem is decidable. Further we show that the first-order program schemata supplied with logical-thermal equivalence and finite state deterministic transducers operating over substitutions are mutually translated into each other. This relationship implies that the equivalence checking problem and the minimization problem for these transducers are also decidable. In addition, on the basis of the discovered relationship, we have found a subclass of firstorder program schemata such that their minimization can be performed in polynomial time by means of known techniques for minimization of finite state transducers operating over semigroups. Finally, we demonstrate that in general case the minimization problem for finite state transducers over semigroups may have several non-isomorphic solutions.

Categorical model of structural operational semantics for imperative language

Definition of programming languages consists of the formal definition of syntax and semantics. One of the most popular semantic methods used in various stages of software engineering is structural operational semantics. It describes program behavior in the form of state changes after execution of elementary steps of program. This feature makes structural operational semantics useful for implementation of programming languages and also for verification purposes. In our paper we present a new approach to structural operational semantics. We model behavior of programs in category of states, where objects are states, an abstraction of computer memory and morphisms model state changes, execution of a program in elementary steps. The advantage of using categorical model is its exact mathematical structure with many useful proved properties and its graphical illustration of program behavior as a path, i.e. a composition of morphisms. Our approach is able to accentuate dynamics of structural operational semantics. For simplicity, we assume that data are intuitively typed. Visualization and facility of our model is not only a new model of structural operational semantics of imperative programming languages but it can also serve for education purposes.

Semantics-based generation of verification conditions via program specialization

We present a method for automatically generating verification conditions for a class of imperative programs and safety properties. Our method is parametric with respect to the semantics of the imperative programming language, as it generates the verification conditions by specializing, using unfold/fold transformation rules, a Horn clause interpreter that encodes that semantics. We define a multi-step operational semantics for a fragment of the C language and compare the verification conditions obtained by using this semantics with those obtained by using a more traditional small-step semantics. The flexibility of the approach is further demonstrated by showing that it is possible to easily take into account alternative operational semantics definitions for modeling additional language features. We have proved that the verification condition generation takes a number of transformation steps that is linear with respect to the size of the imperative program to be verified. Also the size of the verification conditions is linear with respect to the size of the imperative program. Besides the theoretical computational complexity analysis, we also provide an experimental evaluation of the method by generating verification conditions using the multi-step and the small-step semantics for a few hundreds of programs taken from various publicly available benchmarks, and by checking the satisfiability of these verification conditions by using state-of-the-art Horn clause solvers. These experiments show that automated verification of programs from a formal definition of the operational semantics is indeed feasible in practice.

OpenVX-Based Python Framework for Real-time Cross-Platform Acceleration of Embedded Computer Vision Applications

Embedded real-time vision applications are being rapidly deployed in a large realm of consumer electronics, ranging from automotive safety to surveillance systems. However, the relatively limited computational power of embedded platforms is considered as a bottleneck for many vision applications, necessitating optimization. OpenVX is a standardized interface, released in late 2014, in an attempt to provide both system and kernel level optimization to vision applications. With OpenVX, Vision processing are modeled with coarse-grained data flow graphs, which can be optimized and accelerated by the platform implementer. Current full implementations of OpenVX are given in the programming language C, which does not support advanced programming paradigms such as object-oriented, imperative and functional programming, nor does it have runtime or type-checking. Here we present a python-based full Implementation of OpenVX, which eliminates much of the discrepancies between the object-oriented paradigm used by many modern applications and the native C implementations. Our open-source implementation can be used for rapid development of OpenVX applications in embedded platforms. Demonstration includes static and real-time image acquisition and processing using a Raspberry Pi and a GoPro camera. Code is given as supplementary information. Code project and linked deployable virtual machine are located on GitHub: https://github.com/NBEL-lab/PythonOpenVX.

Automatically Proving Termination and Memory Safety for Programs with Pointer Arithmetic

While automated verification of imperative programs has been studied intensively, proving termination of programs with explicit pointer arithmetic fully automatically was still an open problem. To close this gap, we introduce a novel abstract domain that can track allocated memory in detail. We use it to automatically construct a symbolic execution graph that over-approximates all possible runs of a program and that can be used to prove memory safety. This graph is then transformed into an integer transition system, whose termination can be proved by standard techniques. We implemented this approach in the automated termination prover AProVE and demonstrate its capability of analyzing C programs with pointer arithmetic that existing tools cannot handle.

Optimisation of language-integrated queries by query unnesting

Native functional-style querying extensions for programming languages (e.g., LINQ or Java 8 streams) are widely considered as declarative. However, their very limited degree of optimisation when dealing with local collection processing contradicts this statement. We show that developers constructing complex LINQ queries or combining queries expose themselves to the risk of severe performance deterioration. For an inexperienced programmer, a way of getting an appropriate query form can be too complicated. Also, a manual query transformation is justified by the need of improving performance, but achieved at the expense of reflecting an actual business goal. As a result, benefits from a declarative form and an increased level of abstraction are lost.In this paper, we claim that moving of selected methods for automated optimisation elaborated for declarative query languages to the level of imperative programming languages is possible and desired. Our approach is based on the assumption that programmer is able distinguish whether a language-integrated query is intentionally used to introduce some side-effects or its sole purpose is to only query the data. We propose two optimisation procedures through query unnesting designed to avoid unnecessary multiple calculations in collection-processing constructs based on higher-order functions. We have implemented and verified this idea as a simple proof-of-concept LINQ optimiser library.

Model Checking Software with First Order Logic Specifications Using AIG Solvers

Static verification techniques leverage Boolean formula satisfiability solvers such as SAT and SMT solvers that operate on conjunctive normal form and first order logic formulae, respectively, to validate programs. They force bounds on variable ranges and execution time and translate the program and its specifications into a Boolean formula. They are limited to programs of relatively low complexity for the following reasons. (1) A small increase in the bounds can cause a large increase in the size of the translated formula. (2) Boolean satisfiability solvers are restricted to using optimizations that apply at the level of the formula. Finally, (3) the Boolean formulae often need to be regenerated with higher bounds to ensure the correctness of the translation. We present a method that uses And-Inverter-Graph (AIG) sequential circuits, and AIG synthesis and verification frameworks to validate programs. An AIG is a Boolean formula with memory elements, logically complete negated conjunction gates, and a hierarchical structure. Encoding the validation problem of a program as an AIG (1) typically provides a more succinct representation than a Boolean formulae encoding with no memory elements, (2) preserves the high-level structure of the program, and (3) enables the use of a number of powerful automated analysis techniques that have no counterparts for other Boolean formulae such as CNF. Our method takes an imperative program with a first order logic specification consisting of a precondition and a postcondition pair, and a bound on the program variable ranges, and produces an AIG with a designated output that is ${true}$ when the program violates the specification. Our method uses AIG synthesis reduction techniques to reduce the AIG, and then uses AIG verification techniques to check the satisfiability of the designated output. The results show that our method can validate designs that are not possible with other state of the art techniques, and with bounds that are an order of magnitude larger.

Learners Programming Language a Helping System for Introductory Programming Courses

Programming is the core of computer science and due to this momentousness a special care is taken in designing the curriculum of programming courses. A substantial work has been conducted on the definition of programming courses, yet the introductory programming courses are still facing high attrition, low retention and lack of motivation. This paper introduced a tiny pre-programming language called LPL (Learners Programming Language) as a ZPL (Zeroth Programming Language) to illuminate novice students about elementary concepts of introductory programming before introducing the first imperative programming course. The overall objective and design philosophy of LPL is based on a hypothesis that the soft introduction of a simple and paradigm specific textual programming can increase the motivation level of novice students and reduce the congenital complexities and hardness of the first programming course and eventually improve the retention rate and may be fruitful in reducing the dropout/failure level. LPL also generates the equivalent high level programs from user source program and eventually very fruitful in understanding the syntax of introductory programming languages. To overcome the inherent complexities of unusual and rigid syntax of introductory programming languages, the LPL provide elementary programming concepts in the form of algorithmic and plain natural language based computational statements. The initial results obtained after the introduction of LPL are very encouraging in motivating novice students and improving the retention rate.

Symbolic execution for memory consumption analysis

With the advances in both hardware and software of embedded systems in the past few years, dynamic memory allocation can now be safely used in embedded software. As a result, the need to develop methods to avoid heap overflow errors in safety-critical embedded systems has increased. Resource analysis of imperative programs with non-regular loop patterns and signed integers, to support both memory allocation and deallocation, has long been an open problem. Existing methods can generate symbolic bounds that are parametric w.r.t. the program inputs; such bounds, however, are imprecise in the presence of non-regular loop patterns. In this paper, we present a worst-case memory consumption analysis, based upon the framework of symbolic execution. Our assumption is that loops (and recursions) of to-be-analyzed programs are indeed bounded. We then can exhaustively unroll loops and the memory consumption of each iteration can be precisely computed and summarized for aggregation. Because of path-sensitivity, our algorithm generates more precise bounds. Importantly, we demonstrate that by introducing a new concept of reuse, symbolic execution scales to a set of realistic benchmark programs.

Refinement types for TypeScript

We present Refined TypeScript (RSC), a lightweight refinement type system for TypeScript, that enables static verification of higher-order, imperative programs. We develop a formal system for RSC that delineates the interaction between refinement types and mutability, and enables flow-sensitive reasoning by translating input programs to an equivalent intermediate SSA form. By establishing type safety for the intermediate form, we prove safety for the input programs. Next, we extend the core to account for imperative and dynamic features of TypeScript, including overloading, type reflection, ad hoc type hierarchies and object initialization. Finally, we evaluate RSC on a set of real-world benchmarks, including parts of the Octane benchmarks, D3, Transducers, and the TypeScript compiler. We show how RSC successfully establishes a number of value dependent properties, such as the safety of array accesses and downcasts, while incurring a modest overhead in type annotations and code restructuring.

Angry-HEX: An Artificial Player for Angry Birds Based on Declarative Knowledge Bases

This paper presents the Angry-HEX artificial intelligent agent that participated in the 2013 and 2014 Angry Birds Artificial Intelligence Competitions. The agent has been developed in the context of a joint project between the University of Calabria (UniCal) and the Vienna University of Technology (TU Vienna). The specific issues that arise when introducing artificial intelligence in a physics-based game are dealt with a combination of traditional imperative programming and declarative programming, used for modeling discrete knowledge about the game and the current situation. In particular, we make use of HEX programs, which are an extension of answer set programming (ASP) programs toward integration of external computation sources, such as 2-D physics simulation tools.

A Formal C Memory Model for Separation Logic.

The core of a formal semantics of an imperative programming language is a memory model that describes the behavior of operations on the memory. Defining a memory model that matches the description of C in the C11 standard is challenging because C allows both high-level (by means of typed expressions) and low-level (by means of bit manipulation) memory accesses. The C11 standard has restricted the interaction between these two levels to make more effective compiler optimizations possible, at the expense of making the memory model complicated. We describe a formal memory model of the (non-concurrent part of the) C11 standard that incorporates these restrictions, and at the same time describes low-level memory operations. This formal memory model includes a rich permission model to make it usable in separation logic and supports reasoning about program transformations. The memory model and essential properties of it have been fully formalized using the Coq proof assistant.

Dynamics of Change: Why Reactivity Matters

Professional programming is about dealing with software at scale. Everything is trivial when the problem is small and contained: it can be elegantly solved with imperative programming or functional programming or any other paradigm. Real-world challenges arise when programmers have to deal with large amounts of data, network requests, or intertwined entities, as in UI (user interface) programming.

Editorial

This special issue of the Formal Aspects of Computing journal contains a selection of the best papers accepted at the 12 th edition of the international conference series on Software Engineering and Formal Methods (SEFM). This conference was held in Grenoble (France) on September 1-5, 2014. The aim of the conference was to bring together practitioners and researchers from academia, industry and government to advance the state of the art in formal methods, to scale up their application in the software industry and to encourage their integration with practical engineering methods. The SEFM'14 conference received 106 full submissions, and the programme committee of the conference decided to accept 29 papers. Out of these 29 papers, we selected the best six papers, and the authors of these papers were invited to submit a revised and extended version of their work to this special issue. After a meticulous review process, we finally accepted five of the six invited papers. The topics covered in this special issue are the following: Domain Specific Languages, Component-based Systems and Architectures, Learning Finite State Machines, Construction and Verification of Imperative Programs, and Partial Order Reduction in the context of Model Checking.

Bounded-Choice Statements for User Interaction in Imperative Programming

Bounded-Choice Statements for User Interaction in Imperative Programming

Equivalence Checking of Two Functional Programs Using Inductive Theorem Provers

In this paper, we present a new method for generating inductive hypothesis for proving an equivalence between two imperative programs: one recursive and one iterative. The basic premise is to convert both programs in the form of term rewriting system that is acceptable to inductive theorem provers and to generate inductive generalization lemmas that such a theorem prover can discharge. As finding inductive generalizations automatically is an undecidable problem, we will focus on a certain class of recursive programs that cannot be handled by existing tools. We develop criteria under which we can prove the equivalence of two programs. A technique based on schematic programs for proving concrete ones is proposed.Schematic generalization lemmas are computed directly from given specifications.Concrete lemmas are obtained by instantiation of schematic generalization lemmas.The technique is applied prior to any proof attempt, then save time.Only the validity of the schematic generalization lemma is checked.

A capabilities driven model for web services description and composition

Service-oriented architectures SOA foster the integration of different technologies and platforms coming from various enterprises, and bring a new level of flexible modularity that is able to guarantee end-to-end quality of service. However, a current bottleneck in the current process of modelling compositions in SOA is the expert level needed in order to achieve such a composition. This is mainly due to the imperative programming paradigm they are based on. A language such as BPEL is clearly an expert language, and specifying and programming a composition using BPEL is a lengthy, costly, and high risk process. To overcome this limitation, we propose in this paper to use a declarative approach to model services and services compositions. This approach relies on a capabilities service specification, powered by reasoning techniques to handle both functional and non-functional requirements and highly expressive interaction models without over-specifying them. It enables to support flexible and self-managed compositions that are able to adapt to changes that may happen continuously and unpredictably.