1,692 research outputs found

    Formalization and Verification of Behavioral Correctness of Dynamic Software Updates

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    AbstractDynamic Software Updating (DSU) is a technique of updating running software systems on-the-fly. Whereas there are some studies on the correctness of dynamic updating, they focus on how to deploy updates correctly at the code level, e.g., if procedures refer to the data of correct types. However, little attention has been paid to the correctness of the dynamic updating at the behavior level, e.g., if systems after being updated behave as expected, and if unexpected behaviors can never occur. We present an algebraic methodology of specifying dynamic updates and verifying their behavioral correctness by using off-the-shelf theorem proving and model checking tools. By theorem proving we can show that systems after being updated indeed satisfy their desired properties, and by model checking we can detect potential errors. Our methodology is general in that: (1) it can be applied to three updating models that are mainly used in current DSU systems; and (2) it is not restricted to dynamic updates for certain programming models

    Abstract State Machines 1988-1998: Commented ASM Bibliography

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    An annotated bibliography of papers which deal with or use Abstract State Machines (ASMs), as of January 1998.Comment: Also maintained as a BibTeX file at http://www.eecs.umich.edu/gasm

    Towards a General Framework for Formal Reasoning about Java Bytecode Transformation

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    Program transformation has gained a wide interest since it is used for several purposes: altering semantics of a program, adding features to a program or performing optimizations. In this paper we focus on program transformations at the bytecode level. Because these transformations may introduce errors, our goal is to provide a formal way to verify the update and establish its correctness. The formal framework presented includes a definition of a formal semantics of updates which is the base of a static verification and a scheme based on Hoare triples and weakest precondition calculus to reason about behavioral aspects in bytecode transformationComment: In Proceedings SCSS 2012, arXiv:1307.802

    A Case Study on Formal Verification of Self-Adaptive Behaviors in a Decentralized System

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    Self-adaptation is a promising approach to manage the complexity of modern software systems. A self-adaptive system is able to adapt autonomously to internal dynamics and changing conditions in the environment to achieve particular quality goals. Our particular interest is in decentralized self-adaptive systems, in which central control of adaptation is not an option. One important challenge in self-adaptive systems, in particular those with decentralized control of adaptation, is to provide guarantees about the intended runtime qualities. In this paper, we present a case study in which we use model checking to verify behavioral properties of a decentralized self-adaptive system. Concretely, we contribute with a formalized architecture model of a decentralized traffic monitoring system and prove a number of self-adaptation properties for flexibility and robustness. To model the main processes in the system we use timed automata, and for the specification of the required properties we use timed computation tree logic. We use the Uppaal tool to specify the system and verify the flexibility and robustness properties.Comment: In Proceedings FOCLASA 2012, arXiv:1208.432

    Abstract Execution: Automatically Proving Infinitely Many Programs

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    Abstract programs contain schematic placeholders representing potentially infinitely many concrete programs. They naturally occur in multiple areas of computer science concerned with correctness: rule-based compilation and optimization, code refactoring and other source-to-source transformations, program synthesis, Correctness-by-Construction, and more. Mechanized correctness arguments about abstract programs are frequently conducted in interactive environments. While this permits expressing arbitrary properties quantifying over programs, substantial effort has to be invested to prove them manually by writing proof scripts. Existing approaches to proving abstract program properties automatically, on the other hand, lack expressiveness. Frequently, they only support placeholders representing all possible instantiations; in some cases, minor refinements are supported. This thesis bridges that gap by presenting Abstract Execution (AE), an automatic reasoning technique for universal behavioral properties of abstract programs. The restriction to universal (no existential quantification) and behavioral (not addressing internal structure) properties excludes certain applications; however, it is the key to automation. Our logic for Abstract Execution uses abstract state changes to represent unknown effects on local variables and the heap, and models abrupt completion by symbolic branching. In this logic, schematic placeholders have names: It is possible to re-use them at several places, representing the same program elements in potentially different contexts. Furthermore, the represented concrete programs can be constrained by an expressive specification language, which is a unique feature of AE. We use the theory of dynamic frames to scale between full abstraction and total precision of frame specifications, and support fine-grained pre- and postconditions for (abrupt) completion. We implemented AE by extending the program verifier KeY. Specifically for relational verification of abstract Java programs, we developed REFINITY, a graphical KeY frontend. We used REFINITY it in our signature application of AE: to model well-known statement-level refactoring techniques and prove their conditional safety. Several yet undocumented behavioral preconditions for safe refactorings originated in this case study, which is one of very few attempts to statically prove behavioral correctness of statement-level refactorings, and the only one to cover them to that extent. AE extends Symbolic Execution (SE) for abstract programs. As a foundational contribution, we propose a general framework for SE based on the semantics of symbolic states. It natively integrates state merging by supporting m-to-n transitions. We define two orthogonal correctness notions, exhaustiveness and precision, and formally prove their relation to program proving and bug detection. Finally, we introduce Modal Trace Logic (MTL), a trace-based logic to represent a variety of different program verification tasks, especially for relational verification. It is a “plug-in” logic which can be integrated on-demand with formal languages that have a trace semantics. The core of MTL is the trace modality, which allows expressing that a specification approximates an implementation after a trace abstraction step. We demonstrate the versatility of this approach by formalizing concrete verification tasks in MTL, ranging from functional verification over program synthesis to program evolution. To reason about MTL problems, we translate them to symbolic traces. We suggest Symbolic Trace Logic (STL), which comes with a sequent calculus to prove symbolic trace inclusions. This requires checking symbolic states for subsumption; to that end, we provide two generally useful notions of symbolic state subsumption. This framework relates as follows to the other parts of this thesis: We use the language of abstract programs to express synthesis and compilation, which connects MTL to AE. Moreover, symbolic states of STL are based on our framework for SE

    Lightweight and static verification of UML executable models

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    Executable models play a key role in many development methods (such as MDD and MDA) by facilitating the immediate simulation/implementation of the software system under development. This is possible because executable models include a fine-grained specification of the system behaviour using an action language. Executable models are not a new concept but are now experiencing a comeback. As a relevant example, the OMG has recently published the first version of the “Foundational Subset for Executable UML Models” (fUML) standard, an executable subset of the UML that can be used to define, in an operational style, the structural and behavioural semantics of systems. The OMG has also published a beta version of the “Action Language for fUML” (Alf) standard, a concrete syntax conforming to the fUML abstract syntax, that provides the constructs and textual notation to specify the fine-grained behaviour of systems. The OMG support to executable models is substantially raising the interest of software companies for this topic. Given the increasing importance of executable models and the impact of their correctness on the final quality of software systems derived from them, the existence of methods to verify the correctness of executable models is becoming crucial. Otherwise, the quality of the executable models (and in turn the quality of the final system generated from them) will be compromised. Despite the number of research works targetting the verification of software models, their computational cost and poor feedback makes them difficult to integrate in current software development processes. Therefore, there is the need for efficient and useful methods to check the correctness of executable models and tools integrated to the modelling tools used by designers. In this thesis we propose a verification framework to help the designers to improve the quality of their executable models. Our framework is composed of a set of lightweight static methods, i.e. methods that do not require to execute the model in order to check the desired property. These methods are able to check several properties over the behavioural part of an executable model (for instance, over the set of operations that compose a behavioural executable model) such as syntactic correctness (i.e. all the operations in the behavioural model conform to the syntax of the language in which it is described), non-redundancy (i.e. there is no another operation with exactly the same behaviour), executability (i.e. after the execution of an operation, the reached system state is -in case of strong executability- or may be -in case of weak executability- consistent with the structural model and its integrity constraints) and completeness (i.e. all possible changes on the system state can be performed through the execution of the operations defined in the executable model). For incorrect models, the methods that compose our verification framework return a meaningful feedback that helps repairing the detected inconsistencies
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