Logical foundations for representing object-oriented systems

Abstract

Object-oriented programming languages are designed for computing or simulating the behaviour of interacting objects, but their encapsulated contexts and procedural methods are not well suited to non-procedural techniques in theorem provers, optimizers, and automated design and analysis tools. Logic is the non-procedural system par excellence, but the predicate calculus notation for logic is awkward for representing and reasoning about encapsulated contexts. Conceptual graphs are a graphic system of logic that is better suited to O-O systems. First, they explicitly represent the contexts that are ignored or obscured in predicate calculus. Second, Peirce's rules of inference for reasoning with graphs are explicitly formulated in terms of contexts and the conditions for importing and exporting information from contexts. This article describes the context mechanisms of conceptual graphs, the rules of inference for reasoning with the graphs, and their use as a design language for object-oriented systems.     

A Game-theoretic approach to analyze interacting actors in GRL goal models

Goal-oriented requirements engineering aims to capture desired goals and strategies of relevant stakeholders during early requirements engineering stages, using goal models. Goal-oriented modeling techniques support the analysis of system requirements (especially non-functional ones) from an operationalization perspective, through the evaluation of alternative design options. However, conflicts and undesirable interactions between requirements produced from goals are inevitable, especially as stakeholders often aim for different objectives. In this paper, we propose an approach based on game theory and the Goal-oriented Requirement Language (GRL) to reconcile interacting stakeholders (captured as GRL actors), leading to reasonable trade-offs. This approach consists in building a payoff bimatrix that considers all actor’s valid GRL strategies, and computing its Nash equilibrium. Furthermore, we use two optimization techniques to reduce the size of the payoff bimatrix, hence reducing the computational cost of the Nash equilibrium. The approach goes beyond existing work by supporting nonzero-sum games, multiple alternatives, and inter-actor dependencies. We demonstrate the applicability of our game-theoretic modeling and analysis approach using a running example and two GRL models from the literature, with positive results on feasibility and applicability, including performance results.

     

A multicontext architecture for formalizing complex reasoning

We propose multicontext systems (MC systems) as a formal framework for the specification of complex reasoning. MC systems provide the ability to structure the specification of “global” reasoning in terms of “local” reasoning subpatterns. Each subpattern is modeled as a deduction in a context, formally defined as an axiomatic formal system. the global reasoning pattern is modeled as a concatenation of contextual deductions via bridge rules, i.e., inference rules that infer a fact in one context from facts asserted in other contexts. Besides the formal framework, in this article we propose a three-layer architecture designed to specify and automatize complex reasoning. At the first level we have object-level contexts (called s-contexts) for domain specifications. Problem-solving principles and, more in general, meta-level knowledge about the application domain is specified in a distinct context, called Problem-Solving Context (PSC). On top of s-contexts and PSC, we have a further context, called MT, where it is possible to specify strategies to control multicontext reasoning spanning through s-contexts and PSC. We show how GETFOL can be used as a computer tool for the implementation of MC systems and for the automatization of multicontext deductions. © 1995 John Wiley & Sons, Inc.     

Handling obstacles in goal-oriented requirements engineering

Requirements engineering is concerned with the elicitation of high-level goals to be achieved by the envisioned system, the refinement of such goals and their operationalization into specifications of services and constraints and the assignment of responsibilities for the resulting requirements to agents such as humans, devices and software. Requirements engineering processes often result in goals, requirements, and assumptions about agent behavior that are too ideal; some of them are likely not to be satisfied from time to time in the running system due to unexpected agent behavior. The lack of anticipation of exceptional behaviors results in unrealistic, unachievable, and/or incomplete requirements. As a consequence, the software developed from those requirements will not be robust enough and will inevitably result in poor performance or failures, sometimes with critical consequences on the environment. This paper presents formal techniques for reasoning about obstacles to the satisfaction of goals, requirements, and assumptions elaborated in the requirements engineering process. The techniques are based on a temporal logic formalization of goals and domain properties; they are integrated into an existing method for goal-oriented requirements elaboration with the aim of deriving more realistic, complete, and robust requirements specifications. A key principle is to handle exceptions at requirements engineering time and at the goal level, so that more freedom is left for resolving them in a satisfactory way. The various techniques proposed are illustrated and assessed in the context of a real safety-critical system     

Ubiquitous enterprise service adaptations based on contextual user behavior

Recent advances in mobile technologies and infrastructures have created the demand for ubiquitous access to enterprise services from mobile handheld devices. Further, with the invention of new interaction devices, the context in which the services are being used becomes an integral part of the activity carried out with the system. Traditional human–computer interface (HCI) theories are now inadequate for developing these context-aware applications, as we believe that the notion of context should be extended to different categories: computing contexts, user contexts, and physical contexts for ubiquitous computing. This demands a new paradigm for system requirements elicitation and design in order to make good use of such extended context information captured from mobile user behavior. Instead of redesigning or adapting existing enterprise services in an ad hoc manner, we introduce a methodology for the elicitation of context-aware adaptation requirements and the matching of context-awareness features to the target context by capability matching. For the implementation of such adaptations, we propose the use of three tiers of views: user interface views, data views, and process views. This approach centers on a novel notion of process views to ubiquitous service adaptation, where mobile users may execute a more concise version or modified procedure of the original process according to their behavior under different contexts. The process view also serves as the key mechanism for integrating user interface views and data views. Based on this model, we analyze the design and implementation issues of some common ubiquitous access situations and show how to adapt them systematically into a context-aware application by considering the requirements of a ubiquitous enterprise information system.

An unsupervised approach to modeling personalized contexts of mobile users

Mobile context modeling is a process of recognizing and reasoning about contexts and situations in a mobile environment, which is critical for the success of context-aware mobile services. While there are prior works on mobile context modeling, the use of unsupervised learning techniques for mobile context modeling is still under-explored. Indeed, unsupervised techniques have the ability to learn personalized contexts, which are difficult to be predefined. To that end, in this paper, we propose an unsupervised approach to modeling personalized contexts of mobile users. Along this line, we first segment the raw context data sequences of mobile users into context sessions where a context session contains a group of adjacent context records which are mutually similar and usually reflect the similar contexts. Then, we exploit two methods for mining personalized contexts from context sessions. The first method is to cluster context sessions and then to extract the frequent contextual feature-value pairs from context session clusters as contexts. The second method leverages topic models to learn personalized contexts in the form of probabilistic distributions of raw context data from the context sessions. Finally, experimental results on real-world data show that the proposed approach is efficient and effective for mining personalized contexts of mobile users.     

Goal-Oriented Requirements Engineering: A Unifying Framework

The study of contemporary requirements engineering (RE) methodologies indicates that modelling of organisational goals constitutes a central activity of the RE process. In particular, goals provide the rationale and drive the elaboration of the requirements that operationalise them. They also provide the criteria against which the completeness and correctness of the requirements specification is validated. In other words, requirements implement goals in the same way that programs implement design specifications. Despite the significance of goals in RE, research in the field is fragmented. No research has so far taken place in order to define the overall role that goals play in RE. This paper puts forward a unifying view of goal analysis in the context of RE. This allows the identification of similarities and differences between the different conceptions of goal used by different approaches and promotes the understanding of the overall role of goal analysis in RE. Based on this understanding the various approaches can be put together, thus leading to a stronger goal-driven RE framework that takes advantage of the contributions from the many streams of goal-oriented research.     

A case study validation of a knowledge-based approach for the selection of requirements engineering techniques

Requirements engineering (RE) is a critical phase in the software engineering process and plays a vital role in ensuring the overall quality of a software product. Recent research has shown that industry increasingly recognizes the importance of good RE practices and the use of appropriate RE techniques. However, due to the large number of RE techniques, requirements engineers find it challenging to select suitable techniques for a particular project. Unfortunately, technique selection based on personal experience has limitations with regards to the scope, effectiveness and suitability of the RE techniques for the project at hand. In this paper, a Knowledge-based Approach for the Selection of Requirements Engineering Techniques (KASRET) is proposed that helps during RE techniques selection. This approach has three major features. First, a library of requirements techniques was developed which includes detailed knowledge about RE techniques. Second, KASRET integrates advantages of different knowledge representation schemata and reasoning mechanisms. Thus, KASRET provides mechanisms for the management of knowledge about requirements techniques and support for RE process development. Third, as a major decision support mechanism, an objective function evaluates the overall ability and cost of RE techniques, which is helpful for the selection of RE techniques. This paper makes not only a contribution to RE but also to research and application of knowledge management and decision support in process development. A case study using an industrial project shows the support of KASRET for RE techniques selection.

GODA: A goal-oriented requirements engineering framework for runtime dependability analysis

Context: Many modern software systems must deal with changes and uncertainty. Traditional dependability requirements engineering is not equipped for this since it assumes that the context in which a system operates be stable and deterministic, which often leads to failures and recurrent corrective maintenance. The Contextual Goal Model (CGM), a requirements model that proposes the idea of context-dependent goal fulfillment, mitigates the problem by relating alternative strategies for achieving goals to the space of context changes. Additionally, the Runtime Goal Model (RGM) adds behavioral constraints to the fulfillment of goals that may be checked against system execution traces.Objective: This paper proposes GODA (Goal-Oriented Dependability Analysis) and its supporting framework as concrete means for reasoning about the dependability requirements of systems that operate in dynamic contexts.Method: GODA blends the power of CGM, RGM and probabilistic model checking to provide a formal requirements specification and verification solution. At design time, it can help with design and implementation decisions; at runtime it helps the system self-adapt by analyzing the different alternatives and selecting the one with the highest probability for the system to be dependable. GODA is integrated into TAO4ME, a state-of-the-art tool for goal modeling and analysis.Results: GODA has been evaluated against feasibility and scalability on Mobee: a real-life software system that allows people to share live and updated information about public transportation via mobile devices, and on larger goal models. GODA can verify, at runtime, up to two thousand leaf-tasks in less than 35ms, and requires less than 240 KB of memory.Conclusion: Presented results show GODA’s design-time and runtime verification capabilities, even under limited computational resources, and the scalability of the proposed solution.     

On the observational theory of the CPS-calculus

We apply powerful proof-techniques of concurrency theory to study the observational theory of Thielecke’s CPS-calculus, a distillation of the target language of Continuation-Passing Style transforms. We define a labelled transition system from which we derive a (weak) labelled bisimilarity that completely characterises Morris’ context-equivalence. We prove a context lemma showing that Morris’ context-equivalence coincides with a simpler context-equivalence closed under a smaller class of contexts. Then we profit of the determinism of the CPS-calculus to give a simpler labelled characterisation of Morris’ equivalence, in the style of Abramsky’s applicative bisimilarity. We enhance our bisimulation proof-methods with up to bisimilarity and up to context proof techniques. We use our bisimulation proof techniques to investigate a few algebraic properties on diverging terms that cannot be proved using the original axiomatic semantics of the CPS-calculus.     

Model‐centric software architecture reconstruction

Much progress has been achieved in defining methods, techniques, and tools for software architecture reconstruction (SAR). However, less progress has been achieved in constructing reasoning frameworks from existing systems that support organizations in architecture analysis and design decisions. These reasoning frameworks are necessary, for example, to assemble existing components and deploy them in new system configurations. We propose a model‐centric approach where this kind of reasoning is driven by the analysis of quality attribute scenarios. The scenarios and the related quality attribute models guide the SAR effort by focusing on the elicitation of model relevant artifacts. The approach further drives the model construction towards the analytical support of What If scenarios that explore responses stimulated by new requirements, such as new deployments of existing components. The paper provides two real‐world case studies. The first case study introduces the model‐centric reconstruction approach in the context of a large satellite tracking system. The second case study provides the construction of a time performance model for an existing embedded system in the automotive industry. The model allows us to perform cost‐efficient predictions of component assemblies in new customer configurations. Copyright © 2005 John Wiley & Sons, Ltd.     

非一致上下文的自动修复技术

在普适计算中,上下文持续快速变化,上下文感知的应用根据上下文变化自动调整自身的行为以适应这种变化。然而,由于不可预测的环境噪声和动态变化等诸多因素的影响,很容易造成上下文不一致。非一致上下文会导致应用异常,甚至失败。为了解决这个问题,提出了一种自动修复上下文的新技术。它分为两个阶段:生成抽象修复用例;执行用例,以验证上下文不一致性是否已经修复。从用户的实际需要出发,生成的修复用例可以分别满足完整性或正确性。实验结果表明,这种技术在修复成功率上远远超过其他技术。     

一种规则驱动的觉察上下文计算模式

以面向服务的体系结构和产生式推理技术为基础,提出一种规则驱动的自适应觉察上下文计算模式。在该模式中,用户的需求及服务复合策略的语义用产生式表示。在动态普适计算运行环境中,规则推理引擎能够在运行期间,根据当前的上下文知识自动选择服务构件,动态合成应用软件完成预定目标。     

A Survey on the Evolution of the Notion of Context-Awareness

The notion of context has been considered for a long time in different areas of Computer Science. This article considers the use of context-based reasoning from the earlier perspective of artificial intelligence as well as the newer developments in ubiquitous computing. Both communities have been somehow interested in the potential of context-reasoning to support real-time meaningful reactions from systems. We explain how the concept evolved in each of these different approaches. We found initially that each of them considered this topic quite independently and separated from each other; however, latest developments have started to show signs of cross-fertilization amongst these areas. The aim of our survey is to provide an understanding on the way context and context-reasoning were approached, to show that work in each area is complementary, and to highlight there are positive synergies arising amongst them. The overarching goal of this article is to encourage further and longer term synergies between those interested in further understanding and using context-based reasoning.     

Context reasoning using extended evidence theory in pervasive computing environments

Most existing context reasoning approaches implicitly assume that contexts are precise and complete. This assumption cannot be held in pervasive computing environments, where contexts are often imprecise and incomplete due to unreliable connectivity, user mobility and resource constraints. To this end, we propose an approach called CRET: Context Reasoning using extended Evidence Theory. CRET applies the evidence theory to context reasoning in pervasive computing environments. Because evidence theory is limited by two fundamental problems–computation-intensiveness and Zadeh paradox, CRET presents evidence selection and conflict resolution strategies. Empirical study shows that CRET is desirable for pervasive applications.     

A distributed logic for Networked Cyber-Physical Systems

We describe a distributed logical framework designed to serve as a declarative semantic foundation for Networked Cyber-Physical Systems. The framework provides notions of facts and goals that include interactions with the environment via external goal requests, observations that generate facts, and actions that achieve goals. Reasoning rules are built on a partially ordered knowledge-sharing model for loosely coupled distributed computing. The logic supports reasoning in the context of dynamically changing facts and system goals. It can be used both to program systems and to reason about possible scenarios and emerging properties.     

The brave new world of design requirements

Despite its success over the last 30 years, the field of Requirements Engineering (RE) is still experiencing fundamental problems that indicate a need for a change of focus to better ground its research on issues underpinning current practices. We posit that these practices have changed significantly in recent years. To this end we explore changes in software system operational environments, targets, and the process of RE. Our explorations include a field study, as well as two workshops that brought together experts from academia and industry. We recognize that these changes influence the nature of central RE research questions. We identify four new principles that underlie contemporary requirements processes, namely: (1) intertwining of requirements with implementation and organizational contexts, (2) dynamic evolution of requirements, (3) emergence of architectures as a critical stabilizing force, and (4) need to recognize unprecedented levels of design complexity. We recommend a re-focus of RE research based on a review and analysis of these four principles, and identify several theoretical and practical implications that flow from this analysis.