Object-oriented distributed computing is becoming increasingly important for critical infrastructure in society. In standard objectoriented models, objects synchronize on method calls. These models may be criticized in the distributed setting for their tight coupling of communication and synchronization; network delays and instabilities may locally result in much waiting and even deadlock. The Creol model targets distributed objects by a looser coupling of method calls and synchronization. Asynchronous method calls and high-level local control structures allow local computation to adapt to network instability. Object variables are typed by interfaces, so communication with remote objects is independent from their implementation. The inheritance and subtyping relations are distinct in Creol. Interfaces form a subtype hierarchy, whereas multiple inheritance is used for code reuse at the class level. This paper presents the Creol syntax, operational semantics, and type system. It is shown that runtime type errors do not occur for well-typed programs.
Modern applications distributed across networks such as the Internet may need to evolve without compromising application availability. Object systems are well suited for runtime upgrade, as encapsulation clearly separates internal structure and external services. This paper considers a mechanism for dynamic class upgrade, allowing class hierarchies to be upgraded in such a way that the existing objects of the upgraded class and of its subclasses gradually evolve at runtime. The mechanism is integrated in Creol, a high-level language which targets distributed applications by means of concurrent objects communicating by asynchronous method calls. The dynamic class construct is given a formal semantics in rewriting logic, extending the semantics of the Creol language.
Late binding allows flexible code reuse but complicates formal reasoning significantly, as a method call's receiver class is not statically known. This is especially true when programs are incrementally developed by extending class hierarchies. This report develops a novel method to reason about late bound method calls. In contrast to traditional behavioral subtyping, reverification is avoided without restricting method overriding to fully behavior-preserving redefinition. The approach ensures that when analyzing the methods of a class, it suffices to consider that class and its superclasses. Thus, the full class hierarchy is not needed, and incremental reasoning is supported. We formalize this approach as a calculus which lazily imposes context-dependent subtyping constraints on method definitions. The calculus ensures that all method specifications required by late bound calls remain satisfied when new classes extend a class hierarchy. The calculus does not depend on a specific program logic, but the examples in the report use a Hoare-style proof system. We show soundness of the analysis method.
Abstract. Today's software systems are becoming increasingly configurable and designed for deployment on a plethora of architectures, ranging from sequential machines via multicore and distributed architectures to the cloud. Examples of such systems are found in, e.g., software product lines, service-oriented computing, information systems, embedded systems, operating systems, and telephony. To model and analyze systems without a fixed architecture, the models need to naturally capture and range over relevant deployment scenarios. For this purpose, it is interesting to lift aspects of low-level deployment concerns to the abstraction level of the modeling language. In this paper, the objectoriented modeling language Creol is extended with a notion of dynamic deployment components with parametric processing resources, such that processor resources may be explicitly reallocated. The approach is compositional in the sense that functional models and reallocation strategies are both expressed in Creol, and functional models can be run alone or in combination with different reallocation strategies. The formal semantics of deployment components is given in rewriting logic, extending the semantics of Creol, and executes on Maude, which allows simulations and test suites to be applied to models which vary in their available resources as well as in their resource reallocation strategies.
Abstract. Wireless sensor networks are typically ad-hoc networks of resource-constrained nodes; in particular, the nodes are limited in power resources. It can be difficult and costly to replace sensor nodes, for instance when implanted in the human body. Data transmission is the major consumer of power, so it is important to have power-efficient protocols. In order to reduce the total power consumption in the network, we consider nodes which cooperate to transmit data. Nodes which cooperate, form a group. A mobile node may at some point be without a group, in which case it is desirable for the node to be able to join a group. In this paper we propose a modification of the AODV protocol to decide whether a node should join a given group, using coalitional game theory to determine what is beneficial in terms of power consumption. The protocol is formalized in rewriting logic, implemented in the Maude tool, and validated by means of Maude's model exploration facilities.
a b s t r a c tObject-orientation supports code reuse and incremental programming. Multiple inheritance increases the possibilities for code reuse, but complicates the binding of method calls and thereby program analysis. Behavioral subtyping allows program analysis under an open world assumption; i.e., under the assumption that class hierarchies are extensible. However, method redefinition is severely restricted by behavioral subtyping, and multiple inheritance may lead to conflicting restrictions from independently designed superclasses. This paper presents a more liberal approach to incremental reasoning for multiple inheritance under an open world assumption. The approach, based on lazy behavioral subtyping, is well-suited for multiple inheritance, as it incrementally imposes context-dependent behavioral constraints on new subclasses. We first present the approach for a simple language and show how incremental reasoning can be combined with flexible code reuse. Then this language is extended with a hierarchy of interface types which is independent of the class hierarchy. In this setting, flexible code reuse can be combined with modular reasoning about external calls in the sense that each class is analyzed only once. We formalize the approach as a calculus and show soundness for both languages.
We propose a new and systematic framework for proof reuse in the context of deductive software verification. The framework generalizes abstract contracts into incremental proof repositories. Abstract contracts enable a separation of concern between called methods and their implementations, facilitating proof reuse. Proof repositories allow the systematic caching of partial proofs that can be adapted to different method implementations. The framework provides flexible support for verification-in-the-large in the context of, e.g., partly developed programs, evolution of programs and contracts, and product variability.Partly funded by the EU project H2020-644298 HyVar: Scalable Hybrid Variability for Distributed Evolving Software Systems (www.hyvar-project.eu), the EU project FP7-610582 Envisage: Engineering Virtualized Services (www.envisage-project.eu), the Ateneo/CSP project RunVar, and the ICT COST Actions IC1402 ARVI (www.cost-arvi.eu) and IC1201 BETTY (www.behavioural-types.eu).
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.