Pattern-based and composition-driven automatic generation of logical specifications for workflow-oriented software models

Logical specifications for behavioural models are crucial for the formal analysis of complex system designs. The automation of obtaining such a specification is essential particularly for promoting logical and deductive methods in software development. This article replicates earlier methods for automatically generating logical specifications equivalent to behavioural models, while also extending the approach to include workflow mining processes. Various and effective interactions with existing theorem provers are also proposed. We conducted straightforward, yet comprehensive, experiments covering multiple stages, which include workflow extraction, automatic logical specification generation, and theorem prover based analysis and the evaluation of these specifications.

Logical specifications for behavioural models are crucial for the formal analysis of complex system designs. The automation of obtaining such a specification is essential particularly for promoting logical and deductive methods in software development. This article replicates earlier methods for automatically generating logical specifications equivalent to behavioural models, while also extending the approach to include workflow mining processes. Various and effective interactions with existing theorem provers are also proposed. We conducted straightforward, yet comprehensive, experiments covering multiple stages, which include workflow extraction, automatic logical specification generation, and theorem prover based analysis and the evaluation of these specifications.

The work concerns issues related to automatic generation of logical specifications. Logical specifications can be extracted directly from developed software models. Received specification can be used in the process of a system formal verification using a deductive approach. The generated logical specification is just a set of temporal logic formulas as well as verified system properties are expressed in temporal logic. The extraction process is based on the idea of organizing the whole analyzed model as a set of certain design patterns of control flows. A method of automatic transformation of workflow design patterns to temporal logic formulas is proposed. These formulas constitute a logical specification and may be the first step towards a formal verification of system correctness using any method of the deduction-based reasoning. Applying the presented concepts enables bridging the gap between naturalness and intuitive of the deductive inference and the difficulty of its practical application in the case of software models.

The work concerns formal verification of workflow-oriented software models using the deductive approach. The formal correctness of a model’s behaviour is considered. Manually building logical specifications, which are regarded as a set of temporal logic formulas, seems to be a significant obstacle for an inexperienced user when applying the deductive approach. A system, along with its architecture, for deduction-based verification of workflow-oriented models is proposed. The process inference is based on the semantic tableaux method, which has some advantages when compared with traditional deduction strategies. The algorithm for automatic generation of logical specifications is proposed. The generation procedure is based on predefined workflow patterns for BPMN, which is a standard and dominant notation for the modeling of business processes. The main idea behind the approach is to consider patterns, defined in terms of temporal logic, as a kind of (logical) primitives which enable the transformation of models to temporal logic formulas constituting a logical specification. Automation of the generation process is crucial for bridging the gap between the intuitiveness of deductive reasoning and the difficulty of its practical application when logical specifications are built manually. This approach has gone some way towards supporting, hopefully enhancing, our understanding of deduction-based formal verification of workflow-oriented models.

This work concerns requirements gathering and their formal verification using deductive approach. The approach is based on temporal logic and the semantic tableaux reasoning method. Requirements elicitation is carried out with some UML diagrams. A use case, its scenario and its activity diagram may be linked to each other during the process of gathering requirements. Activities are identified in the use case scenario and then their workflows are modeled using the activity diagram. Organizing the activity diagram workflows into design patterns is crucial and enables generating logical specifications in an automated way. Temporal logic specifications, formulas and properties are difficult to specify by inexperienced users and this fact can be a significant obstacle to the practical use of deduction-based verification tools. The approach presented in this paper attempts to overcome this problem. Automatic transformation of workflow patterns to temporal logic formulas considered as a logical specification is defined. The architecture of an automatic generation and deduction-based verification system is proposed.KeywordsRequirements EngineeringUMLUse Case DiagramUse Case ScenarioActivity DiagramFormal VerificationDeductive ReasoningSemantic Tableaux MethodTemporal LogicWorkflowsDesign PatternsLogical ModelingGenerating Formulas

Design of a high bit rate burst mode clock and data recovery (BMCDR) circuit for gigabit passive optical networks (GPON) is described. A top-down design flow is established and some of the key issues related to the behavioural level modeling are addressed in consideration for the complexity of the BMCDR integrated circuit (IC). Precise implementation of Simulink behavioural model accounting for the saturation of frequency control voltage is therefore developed for the BMCDR, and the parameters of the circuit blocks can be readily adjusted and optimized based on the behavioural model. The newly designed BMCDR utilizes the 0.18um standard CMOS technology and is shown to be capable of operating at bit rate of 2.5Gbps, as well as the recovery time of one bit period in our simulation. The developed behaviour model is verified by comparing with the detailed circuit simulation.

The accurate defining states in a newly designed state machine diagram can be a challenge, especially if we are not domain experts. There is an idea of the square of opposition in classical logic, which is highly informative and can support analysts when shaping states for behavioural models. We proposed an identification method employing a square-driven and state-oriented approach, ideally suited for cases where analysts struggle with understanding the investigated domain or in applications that demand rigorous adherence to formal methodologies. State identification is augmented by the encoding of state variables representing particular states and predicates along with the analysis in a logical style. We have shown a simple yet inspiring example to illustrate the entire methodology in a satisfactory manner.

In this paper we provide a brief description of some of the current efforts and report experiences and lessons learned in the use of modeling on some avionics development programs at Boeing. Performance and behavioral modeling is a valuable tool for evaluating hardware and software designs. Electronic component and assembly hardware models, based on standard languages such as Verilog and VHDL, have been useful for evaluating hardware architectures. Software models that can interoperate with the hardware models are useful for evaluating software architectures and the performance of the software architectures on given hardware platforms (co-simulation). These performance models can be used to specify systems and parts of systems. The simulations of the models can be used to provide a minimum set of acceptance tests that any design must achieve. In this sense, the models contain the dynamic specifications for the desired design. The authors have experience that includes performance only, behavior only, and performance and behavioral models used in the development of avionics systems, subsystems, and components. These models were useful at different stages of development and were able to provide insight into system requirements as well as the suitability of any proposed implementations. This paper addresses performance and behavioral modeling and simulation as applied to avionics systems and sub-systems in the product development phases.

We propose a simple imperative programming language, ERC, that features arbitrary real numbers as primitive data type, exactly. Equipped with a denotational semantics, ERC provides a formal programming language-theoretic foundation to the algorithmic processing of real numbers. In order to capture multi-valuedness, which is well-known to be essential to real number computation, we use a Plotkin powerdomain and make our programming language semantics computable and complete: all and only real functions computable in computable analysis can be realized in ERC. The base programming language supports real arithmetic as well as implicit limits; expansions support additional primitive operations (such as a user-defined exponential function). By restricting integers to Presburger arithmetic and real coercion to the `precision' embedding $\mathbb{Z}\ni p\mapsto 2^p\in\mathbb{R}$, we arrive at a first-order theory which we prove to be decidable and model-complete. Based on said logic as specification language for preconditions and postconditions, we extend Hoare logic to a sound (w.r.t. the denotational semantics) and expressive system for deriving correct total correctness specifications. Various examples demonstrate the practicality and convenience of our language and the extended Hoare logic.

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Software metrics have direct linkage with software quality and defect. Thus, for a software engineer, it becomes very hard to estimate the software quality and provide product assurance to the client. Most of the software becomes failure due to several kinds of defects. The software industry uses different kinds of software models such as SDLC for software product development, and it becomes very difficult to choose the correct software model for software development. The objective of this chapter is to show how we can use machine learning and data mining for software defect, quality and software model prediction. We analyse different kinds of machine learning algorithms for application in software engineering domain. This chapter reviews the various classifications used to predict software defects using software measurements in the literature. In this chapter, we perform a detailed analysis of application of data mining and machine learning approaches used for software quality, defect and quality analysis.

Software products in companies are a substantial part of their production and a necessary condition of their business success. However, there is still a problem of software proper specification and verification. We propose a formal specification method for software processes based on Transparent Intensional Logic, TIL. This method is logic-oriented, because logical specification within a rich formal framework makes it possible to explicitly define process resources as well as process logic. Moreover, our novel contribution consists in integrating a knowledge-based method with process dynamic modeling.

The work relates to formal verification of requirements models using deductive reasoning. Elicitation of requirements has significant impact on the entire software development process. Therefore, formal verification of requirements models may influence software cost and reliability in a positive way. However, logical specifications, considered as sets of temporal logic formulas, are difficult to specify manually by inexperienced users and this fact can be regarded as a significant obstacle to practical use of deduction-based verification tools. A method of building requirements models, including their logical specifications, is presented step by step. Requirements models are built using some UML diagrams, i.e. use case diagrams, use case scenarios, and activity diagrams. Organizing activity diagrams into predefined workflow patterns enables automated extraction of logical specifications. The crucial aspect of the presented approach is integrating the requirements engineering phase and the automatic generation of logical specifications. Formal verification of requirements models is based on the deductive approach using the semantic tableaux reasoning method. A simple yet illustrative example of development and verification of a requirements model is provided.

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Mature verification and monitoring approaches, such as complex event processing and model checking, can be applied for checking compliance specifications at design time and runtime. Little is known about the understandability of the different formal and technical languages associated with these approaches. This uncertainty regarding understandability might be a major obstacle for the broad practical adoption of those techniques. This article reports a controlled experiment with 215 participants on the understandability of modeling compliance specifications in representative modeling languages, namely linear temporal logic (LTL), the complex event processing-based event processing language (EPL) and property specification patterns (PSP). The formalizations in PSP were overall more correct. That is, the pattern-based approach provides a higher level of understandability than EPL and LTL. More advanced users, however, seemingly are able to cope equally well with PSP and EPL in modeling compliance specifications.