Translating meaning representations to behavioural interface specifications

Various works have been done in verifying object constraint language (OCL) by translating it to formal specification language. This paper presents the process of translating OCL to prototype verification system (PVS) using model transformation. PVS is a formal specification language based on higher-order logic and comes with a theorem prover. Two processes have been identified to translate OCL to PVS. The first process translates OCL constraint to PVS specification directly using model-to-text transformation while the second process transforms OCL to PVS model. Both processes are evaluated to identify the advantages and disadvantages. Transforming OCL to PVS model allow the result to be use for other model management operation.

The complexity of designing concurrent and highly-evolving interactive systems has grown to a point where system verification has become a hurdle. Fortunately, formal verification methods have arrived at the right time. They detect errors, inconsistencies and incompleteness at early development stages of a system formally modeled using a formal specification language. -calculus (Milner, 1999) is one such formal language which provides strong mathematical base that can be used for verifying system specifications. But manually verifying the specifications of concurrent systems is a very tedious and error-prone work, especially if the specifications are large. Consequently, an automated verification tool would be essential for efficient system design and development. In addition, formal verification tools are vital ingredient to fully harness the potential of component-based software composition. The authors developed such an automated verification tool which is highly portable and seamlessly integrates with the visualization, reduction and performance evaluation tools introduced (Ahmad & Rahimi, 2008; Rahimi, 2006; Rahimi et al., 2001, 2008) to provide a comprehensive tool for designing and analyzing multi process/agent systems. Open-Bisimulation (Sangiorgi, 1996) concept is utilized as the theoretical base for the design and implementation of the tool which incorporates an expert system implemented in Java Expert System Shell (JESS) (Friedman-Hill, 2003).

Traditional structured analysis and design methods have been criticized because the methods lack formality to provide a design for rigorous development. Several approaches have been developed for verifying a design by integrating traditional structured analysis and design methods with formal specification languages. However, the integration of traditional structured analysis and design methods with formal specification languages may confuse the problem definition and understanding with the attempt to define system structures and algorithms in the design phase. In addition, formal specification languages may add complexity to the design due to the complexity of the language syntax and semantics. In this paper, we are presenting an approach to verification of a structured design in HOS without using formal specification languages. Rules for the partial and total correctness of the design are also discussed.

SOFL is a formal language and method for system specification and design. It was developed by integrating Petri Nets, Data Flow Diagrams, and VDM-SL. As the major feature of the original SOFL method is to use structured techniques for analysis and specification, and object-oriented techniques for design and implementation, SOFL has its own implementation language that is similar to C++. However during our recent work of applying SOFL to software systems, the transformation of structured specifications to object-oriented implementations creates some difficulties, simply because of paradigms mismatch. In this paper we extend SOFL to a formal object-oriented language and method while keeping its structured features. This will allow powerful object-oriented reuse mechanisms, such as class inheritance and object composition, to be utilized in the early phases, and transformation from SOFL specifications to commercial object-oriented programming languages to be readily achieved.

In this paper we gauge the utility of general-purpose, open-domain semantic parsing for textual entailment recognition by combining graph-structured meaning representations with semantic technologies and formal reasoning tools. Our approach achieves high precision, and in two case studies we show that when reasoning over n-best analyses from the parser the performance of our system reaches stateof-the-art for rule-based textual entailment systems. 1 Background and Motivation There is a growing interest in recent years in general-purpose semantic parsing into graphbased meaning representations, which provide greater expressive power than tree-based structures. Recent efforts in this spirit include, for example, Abstract Meaning Representation (Banarescu et al., 2013), and Semantic Dependency Parsing (SDP) (Oepen et al., 2014; Oepen et al., 2015). Simultaneously, in the Semantic Web community, a range of generic semantic technologies for storing and processing graph-structured data has been made available, but these have not been much used for natural language processing tasks. We propose a flexible, generic framework for precision-oriented Textual Entailment (TE) recognition that combines semantic parsing, graph-based representations of sentence meaning, and semantic technologies. During the decade since the TE task was defined, (logical) inference-based approaches have made some important contributions to the field. Systems such as Bos and Markert (2006) and Tatu and Moldovan (2006) employ automated proof search over logical representations of the input sentences. Other systems, such as Bar-Haim et al. (2007), apply transformational rules to linguistic representations of the sentence pairs, and determine entailment through graph subsumption. Because inference-based systems are vulnerable to incomplete knowledge in the rule set and errors in the mapping from natural language sentences to logical forms or linguistics representations, and because the definition of the TE task encourages a more relaxed, non-logical notion of entailment, the majority of TE systems have used more robust approaches, however. Our work supports a notion of logical inference for TE by reasoning with formal rules over graph-structured meaning representations, while achieving results that are comparable with robust approaches. We use a freely available, grammar-driven semantic parser and a well-defined reduction of underspecified logical-form meaning representations into variable-free semantic graphs called Elementary Dependency Structures (EDS) (Oepen and Lonning, 2006). We capitalize on a pre-existing storage and search infrastructure for EDSs using generic semantic technologies. For entailment classification, we create inference rules that enrich the EDS graphs, apply the rules with a generic reasoner, and use graph alignment as a decision tool. To test our generic setup, we perform two case studies where we replicate well-performing TE systems, one from the Parser Evaluation using Textual Entailments (PETE) task (Yuret et al., 2010), and one from SemEval 2014 Task 1 (Marelli et al., 2014). The best published results for the PETE task, Lien (2014), were obtained through heuristic rules that align meaning representations based on structural similarity. Lien and Kouylekov (2014) extend the same basic approach for SemEval 2014 by including lexical relations and negation handling. We recast the handwritten heuristic rules from these systems as formal Semantic Web Rule Language (SWRL) rules, and run them with a generic reasoning tool over EDS

Standardization of Formal Specification Languages

In this work the protocol WorldFIP for industrial communication networks, is specified with the formal specification language LOTOS. This specification is the foundation of new work lines such as efficiency analysis of WorldFIP performance with simulations in critical applications, the generation of benchmark patterns for conformance tests of WorldFIP communications equipment, and the proposal of new advances in the fieldbus area. Standardization institutions can benefit largely by this implemented methodology of formal specification, because some uncertainties in their description issues can be detected easily during the standard development, if a formal specification language is used at this stage.

A proof tool developed for CSP by customizing an existing general-purpose theorem prover based on higher order logic is described, and it is demonstrated how it can be used to conduct formal reasoning about CSP. The focus is on illustrating the usefulness of the approach. It is shown how reasoning about CSP can be done using a natural deduction theorem prover by illustrating how some standard CSP laws can be mechanically proved from semantic definitions mechanized previously by the author (1990). >

In Wide Area Networks (WANs)inconsistencies among the security policies of Administrative Domains (ADs) may cause severe security flaws. Recently, security policies are written in natural language and as they get more complicated, even for an expert it might be impossible to detect such inconsistencies. However, when a formal language is used, it might be possible to make verification of security policies by automated theorem proving tools. Due to the existence of mobile devices such as laptops, PDAs and mobile agents, we need a formal language that is capable of defining the concept of mobility. In this paper, we extend Mob adtl [1] according its refinement methodology to obtain a formal policy specification language for an 802.11 WLAN with enhanced security network.

The two most critical phases of SDLC are the specification and the designing phase as they involve the transformation of the semantics from real world domain to computer software systems. Unified Modelling Language (UML) has been accepted as blue print for design and specification of software critical systems. But, UML structures have the weakness in preciously defining the semantics of a system. Any misinterpretation in safety critical system’s specification may risks loss of lives. Formal methods are mathematical tools and techniques which are proven very adequate, principally, at requirement specification and design level. However, formal methods are not welcomed because of rigorous use of mathematics. Therefore, a bridge is required between UML and formal methods to overcome the above insufficiencies. The endeavour of this paper is to propose a new approach by integrating UML and Z notation, a formal specification language. The main focus of this paper is on transforming the UML diagram: use case diagram, class diagram and sequence diagram to Z Schema for capturing both the syntax and semantics, particularly for safety critical system. The resultant formal model of the approach are analyzed and verified by using Z/Eves tool.

Domain theory is the mathematical theory underlying denotational semantics. This thesis presents a formalization of domain theory in the Higher Order Logic (HOL) theorem proving system along with a mechanization of proof functions and other tools to support reasoning about the denotations of functional programs. By providing a fixed point operator for functions on certain domains which have a special undefined (bottom) element, this extension of HOL supports the definition of recursive functions which are not also primitive recursive. Thus, it provides an approach to the long-standing and important problem of defining non-primitive recursive functions in the HOL system.<br /> <br />Our philosophy is that there must be a direct correspondence between elements of complete partial orders (domains) and elements of HOL types, in order to allow the reuse of higher order logic and proof infrastructure already available in the HOL system. Hence, we are able to mix domain theoretic reasoning with reasoning in the set theoretic HOL world to advantage, exploiting HOL types and tools directly. Moreover, by mixing domain and set theoretic reasoning, we are able to eliminate almost all reasoning about the bottom element of complete partial orders that makes the LCF theorem prover, which supports a first order logic of domain theory, difficult and tedious to use. A thorough comparison with LCF is provided.<br /> <br />The advantages of combining the best of the domain and set theoretic worlds in the same system are demonstrated in a larger example, showing the correctness of a unification algorithm. A major part of the proof is conducted in the set theoretic setting of higher order logic, and only at a late stage of the proof domain theory is introduced to give a recursive definition of the algorithm, which is not primitive recursive. Furthermore, a total well-founded recursive unification function can be defined easily in pure HOL by proving that the unification algorithm (defined in domain theory) always terminates; this proof is conducted by a non-trivial well-founded induction. In such applications, where non-primitive recursive HOL functions are defined via domain theory and a proof of termination, domain theory constructs only appear temporarily.

Analytica is an automatic theorem prover for theorems in elementary analysis. The prover is written in Mathematica language and runs in the Mathematica environment. The goal of the project is to use a powerful symbolic computation system to prove theorems that are beyond the scope of previous automatic theorem provers. The theorem prover is also able to guarantee the correctness of certain steps that are made by the symbolic computation system and therefore prevent common errors like division by a symbolic expression that could be zero. In this paper we describe the structure of Analytica and explain the main techniques that it uses to construct proofs. We have tried to make the paper as self-contained as possible so that it will be accessible to a wide audience of potential users. We illustrate the power of our theorem prover by several non-trivial examples including the basic properties of the stereographic projection and a series of three lemmas that lead to a proof of Weierstrass''s example of a continuous nowhere differentiable function. Each of the lemmas in the latter example is proved completely automatically.

The problem addressed in this paper is the following: how to use high-level Petri nets for the reverse engineering of implemented distributed applications. The paper presents a reverse engineering methodology applied on a real (simple) Java applet based client/server application. First, starting from the Java program, several abstraction steps are described using the CO-OPN/2 formal specification language. Then, the paper presents brand new research that studies property preservations during the refinement process.

The dominant paradigm in Natural Language Processing (NLP) has traditionally relied on sequential modelling, often overlooking the rich, non-linear structural dependencies inherent in linguistic data. Graph Neural Networks (GNNs) offer a powerful alternative by modelling text as structured graphs, yet a systematic evaluation of their comparative efficacy across tasks of varying structural complexity remains under-explored. This paper presents a comprehensive comparative study of three prominent GNN architectures- Graph Convolutional Networks (GCN), Graph Attention Networks (GAT), and Graph SAGE- applied to three distinct NLP tasks: Text Classification, Semantic Role Labelling (SRL), and Abstract Meaning Representation (AMR) Parsing. We construct task-specific graph topologies, utilizing heterogeneous corpus graphs for document classification and syntactic dependency trees for SRL and AMR. Our empirical results, derived from benchmarks on the 20 Newsgroups, CoNLL-2009, and AMR 2.0 datasets, reveal a clear correlation between architectural properties and task complexity. While GCNs provide a robust and efficient baseline for global text classification (Accuracy: 96.6%), they struggle with the fine-grained structural modelling required for semantic tasks. Conversely, GATs demonstrate superior performance on syntax-heavy tasks, achieving a Labelled F1 score of 85.8% on SRL and a Smatch score of 74.5 on AMR parsing, significantly outperforming the GCN baseline (82.5% and 71.2%, respectively). These findings suggest that the anisotropic aggregation capability of attention mechanisms is critical for capturing the nuanced, long-range dependencies in natural language, establishing GAT as the preferred architecture for structure-dependent NLP applications.

Manual placement of components is often used in FPGA circuit design in order to achieve better results than would be generated by automatic place and route algorithms. However, explicit placement of basic elements in parametrized hardware descriptions is tedious and error-prone. We describe a framework for the description and verification of parametrized hardware libraries with layout information, supporting both placing components with explicit symbolic coordinates and `neighboring' placement directives such as A beside B. The correctness of generated layouts is established by proof in higher-order logic, automated by using the Isabelle theorem prover. We have developed an extensive library of theorems describing properties of layouts that are combined by our compiler and the theorem prover to achieve a high level of automation in the verification of complete circuit layouts, making formal verification of circuit layouts practical with minimal user effort. Our system has been used to verify layout descriptions for a range of circuits that have been mapped to Xilinx FPGAs.