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Live sequence charts (LSCs) have been defined recently as an extension of message sequence charts (MSCs; or their UML variant, sequence charts (MSCs; or their UML variant, sequence diagrams) for rich inter-object specification. One of the main additions is the notion of universal charts and hot, mandatory behavior, which, among other things, enables one to specify forbidden scenarios. LSCs are thus essentially as expressive as statecharts. This paper deals with synthesis, which is the problem of deciding, given an LSC specification, if there exists a satisfying object system and, if so, to synthesize one automatically. The synthesis problem is crucial in the development of complex systems, since sequence diagrams serve as the manifestation of use cases — whether used formally or informally — and if synthesizable they could lead directly to implementation. Synthesis is considerably harder for LSCs than for MSCs, and we tackle it by defining consistency, showing that an entire LSC specification is consistent iff it is satisfiable by a state-based object system, and them synthesizing a satisfying system as a collection of finite state machines or statecharts.

We propose a sound and complete compositional proof rule for distributed synthesis. Applying our proof rule only requires the manual strengthening of the specification into a conjunction of formulas that can be guaranteed by individual black-box processes. All premises of the proof rule can be checked automatically.

For this purpose, we give an automata-theoretic synthesis algorithm for single processes in distributed architectures. The behavior of the local environment of a process is unknown in the process of synthesis and cannot be assumed to be maximal. We therefore consider reactive environments that have the power to disable some of their own actions, and provide methods for synthesis (and realizability checking) in this setting. We establish upper bounds for CTL (2EXPTIME) and CTL* (3EXPTIME) synthesis with incomplete information, matching the known lower bounds for these problems, and provide matching upper and lower bounds for μ-calculus synthesis (2EXPTIME) with complete or incomplete information. Synthesis in reactive environments is harder than synthesis in maximal environments, where CTL, CTL* and μ-calculus synthesis are EXPTIME, 2EXPTIME and EXPTIME complete, respectively.

We investigate how two agents can communicate through a noisy medium modeled as a finite non deterministic transducer. The sender and the receiver are also described by finite transducers which can respectively encode and decode binary messages. When the communication is reliable, we call the encoder/decoder pair a channel.

We study the channel synthesis problem which, given a transducer, asks whether or not such sender and receiver exist and builds them if the answer is positive. To that effect we introduce the structural notion of encoding state in a transducer which is a necessary condition for the existence of a channel. It is not, however, a sufficient condition. In fact, we prove that the problem is undecidable. Nonetheless, we obtain a synthesis procedure when the transducer is functional. We discuss these results in relation to security properties.

The synthesis problem asks to automatically generate, if it exists, an algorithm from a specification of correct input-output pairs. In this paper, we consider the synthesis of computable functions of infinite words, for a classical Turing computability notion over infinite inputs. We consider specifications which are rational relations of infinite words, i.e., specifications defined by non-deterministic parity transducers. We prove that the synthesis problem of computable functions from rational specifications is undecidable. We provide an incomplete but sound reduction to some parity game, such that if Eve wins the game, then the rational specification is realizable by a computable function. We prove that this function is even computable by a deterministic two-way transducer.

We provide a sufficient condition under which the latter game reduction is complete. This entails the decidability of the synthesis problem of computable functions, which we proved to be ExpTime-complete, for a large subclass of rational specifications, namely deterministic rational specifications. This subclass contains the class of automatic relations over infinite words, a yardstick in reactive synthesis.

We propose a method of description and modeling of complex symmetrical images, which can be used for the synthesis of ornamental patterns. Our approach allows considerable memory reduction for storing symmetrical images and considerable time reduction for their synthesis. Our algorithms for ornamental patterns synthesis suggest the design of a special purpose ornamental patterns editor which can store and synthesize symmetrical images.

The traditional embroidery identification technology cannot present the target image of the art network in a more comprehensive and three-dimensional manner. A research on the segmentation and synthesis of embroidery art images based on deep learning convolutional neural network is proposed. Based on the semantic image segmentation technology of deep learning, this paper analyzes the embroidery semantic image segmentation technology, obtains the information of image technology, analyzes the embroidery rendering technology of convolutional neural networks, and puts forward the embroidery rendering algorithm. In order to verify the effectiveness of the algorithm, a simulation test experiment was carried out on the target content image and the embroidery art network image. The test results show that compared with the traditional method, this method has more specific and flexible image generation, stronger three-dimensional sense, closer to the real art embroidery network, and the direction of its needlework is also more hierarchical.

This paper starts with a brief discussion of so-called wavelet transforms, i.e., decompositions of arbitrary signals into localized contributions labelled by a scale parameter. The main features of the method are first illustrated through simple mathematical examples. Then we present the first applications of the method to the recognition and visualisation of characteristic features of speech and of musical sounds.

In this paper, we argue that model-based design and platform-based design are two views of the same thing. A platform is an abstraction layer in the design flow. For example, a core-based architecture and an instruction set architecture are platforms. We focus on the set of designs induced by this abstraction layer. For example, the set of all ASICs based on a particular core-based architecture and the set of all x86 programs are induced sets. Hence, a platform is equivalently a set of designs. Model-based design is about using platforms with useful modeling properties to specify designs, and then synthesizing implementations from these specifications. Hence model-based design is the view from above (more abstract, closer to the problem domain) and platform-based design is the view from below (less abstract, closer to the implementation technology).

One way to define a platform is to provide a design language. Any valid expression in the language is an element of the set. A platform provides a set of constraints together with known tradeoffs that flow from those constraints. Actor-oriented platforms, such as Simulink, abstract aspects of program-level platforms, such as Java, C++, and VHDL. Actor-oriented platforms orthogonalize the actor definition language and the actor composition language, enabling highly polymorphic actor definitions and design using multiple models of computation. In particular, we concentrate on the use of constrained models of computation in design. The modeling properties implied by well chosen constraints allow more easily understood designs and are preserved during synthesis into program-level descriptions. We illustrate these concepts by describing a design framework built on Ptolemy II.

It is important in digital signal processing (DSP) architectures to minimize the silicon area of the integrated circuits. This can be achieved by reducing the number of functional units such as adders and multipliers. In literature, folding technique is used to reduce the functional units by executing multiple algorithm operations on a single functional unit. Register minimization techniques are used to reduce the number of registers in a folded architecture. Retiming is a technique that needs to be performed before applying folding. In this paper, retiming is performed based on nature inspired evolutionary computation method. This technique generates the database of solutions from which best solution can be picked for folding further.

As a part of this work, an efficient folded noise removal audio filter prototype is designed as an application example using evolutionary computation-based retiming and folding with register minimization. Folding technique will however increase the number of registers while multiplexing datapath adder and multiplier elements. Register minimization technique is used after folding to reduce the number of registers. After obtaining retimed, folded filter architecture, low level synthesis is performed which involves mapping of datapath adder and multiplier blocks to actual hardware. Various architectures of adders and multipliers are compared in area-power-performance space and depending on the user defined constraint, folded architecture with specific combination of data path elements is mapped on to hardware. A framework is designed in this paper to automate the entire process which reduces the design cycle time. All the designed filters are targeted for ASIC implementation. The results are compared and are provided as part of simulation results.

A method is proposed targeting the decrease of the number of look-up tables (LUTs) in logic circuits of field programmable gate arrays (FPGA)-based Mealy finite state machines. The method is based on constructing a partition for the set of output variables. It diminishes the number of additional variables encoding the collections of output variables (COVs). A formal method is proposed for finding the partition. An example of synthesis is given, as well as the results of investigations. The investigations were conducted for standard benchmarks.

Quantum computation relies on exploiting quantum mechanical phenomena, and has received significant attention in recent years. Higher-dimensional quantum systems increase the density of encoded information per computing element (e.g., qutrit for three-level system), resulting in less resource overhead. For instance, 63% reduction in the number of qutrits is possible for ternary quantum systems as compared to the corresponding binary systems. The proposed work exploits this fact to synthesize ternary reversible circuits employing a cycle-based technique. The method starts from the ternary reversible specification of a given function in the form of a permutation. The permutation cycles are factored into simpler three-cycles and two-cycles, which are then mapped to ternary reversible gates. Different gate libraries are used to synthesize three-cycles and two-cycles, respectively. A gate decomposition approach is also proposed to synthesize a quantum gate netlist in terms of elementary ternary quantum gates, viz. Muthukrishnan–Stroud gate and shift gate. Synthesis results on benchmark functions indicate that the proposed method results in 27% and 6% improvements in quantum cost and gate count, respectively, over existing works in the literature.

A use case is a specification of interactions involving a system and external actors of that system. The intuitive, user centered nature of textual use cases is one of the reasons for the success of the use case approach. A certain level of formalization is however needed to automate use case based system development, including tasks such as design synthesis, verification and validation. In this paper, a mapping from textual use cases to a formal model (Petri nets) is proposed. Use cases are described in a restricted-form of natural language. The abstract syntax of the language is formally defined using a tuple structure. The mapping from use cases to Petri nets considers use cases sequencing constraints defined at the syntactic-level, and provides a definition of execution semantics to use cases.

This paper addresses the issue of automatic service composition. We first develop a framework in which the exported behavior of a service is described in terms of a so-called execution tree, that is an abstraction for its possible executions. We then study the case in which such exported behavior (i.e. the execution tree of the service) can be represented by a finite state machine (i.e. finite state transition system). In this specific setting, we devise sound, complete and terminating techniques both to check for the existence of a composition, and to return a composition, if one exists. We also analyze the computational complexity of the proposed algorithms. Finally, we present an open source prototype tool, called (E-Service Composer), that implements our composition technique. To the best of our knowledge, our work is the first attempt to provide a provably correct technique for the automatic synthesis of service composition, in a framework where the behavior of services is explicitly specified.

There are several motives for creating process models ranging from technical scenarios in workflow automation to business scenarios in which management decisions are taken. As a consequence, companies typically have different process models for the same process, which differ in terms of granularity. In this context, business process model abstraction serves as a technique that takes a process model as an input and derives a high-level model with coarse-grained activities and the corresponding control flow between them. In this way, business process model abstraction reduces the number of models capturing the same business process on different abstraction levels. In this article, we provide a solution to the problem of deriving the control flow of an abstract process model for the case that an arbitrary grouping of activities is permitted. To this end, we use behavioral profiles and prove that the soundness of the synthesized process model requires a notion of well-structuredness of the abstract model behavioral profile. Furthermore, we demonstrate that the activities can be grouped according to the data flow of the model in a meaningful way, and that this grouping does not directly coincides with a structural decomposition of the process, which is generally assumed by other abstraction approaches. This finding emphasizes the need for handling arbitrary activity groupings in business process model abstraction.

This paper gives a brief overview of the well-known impossibility-possibility theorem in constructing a social welfare function from individual functions. The Analytic Hierarchy Process uses a fundamental scale of absolute numbers to represent judgments about dominance in paired comparisons. It is shown that it is possible to derive such a function in two ways. One is from the synthesized functions of the judgments of each of the individuals. The other is obtained by first combining corresponding pairwise comparison judgments made by all the individuals, thus obtaining a matrix of combined judgments for the group and then deriving a welfare function for the group. With consistency the four conditions imposed by Arrow are satisfied. With inconsistency, an additional condition is needed.