Generalised compositionality in graph transformation

We present a notion of composition applying both to graphs and to rules, based on graph and rule interfaces along which they are glued. The current paper generalises a previous result in two different ways. Firstly, rules do not have to form pullbacks with their interfaces; this enables graph passing between components, meaning that components may “learn” and “forget” subgraphs through communication with other components. Secondly, composition is no longer binary; instead, it can be repeated for an arbitrary number of components

Saying Hello World with GROOVE - A Solution to the TTC 2011 Instructive Case

This report presents a solution to the Hello World case study of TTC 2011 using GROOVE. We provide and explain the grammar that we used to solve the case study. Every requested question of the case study was solved by a single rule application.Comment: In Proceedings TTC 2011, arXiv:1111.440

Incremental pattern matching for regular expressions

Graph pattern matching lies at the heart of any graph transformation-based system. Incremental pattern matching is one approach proposed for reducingthe overall cost of pattern matching over successive transformations by preserving the matches that stay relevant after a rule application. An important issue in any matching scheme, is the ability to properly and consistently deal with various facilities that add to the expressiveness of a GT-tool’s rule language. One such feature is the support for regular path expressions, which would let two nodes to be consideredas a “match”, if a certain path of edges exists between them. In this paper, the incorporation of regular expression support into incremental pattern matching is discussed within the context of the GROOVE tool set. This includes laying down a formal foundation for incremental pattern matching for regular expressions which is then used to justify the extension proposed to add regular expression support to a well-known pattern matching algorithm

Pulse electrochemical deposition and photo-electrochemical characterization of CuInSe2 thin films.

Direct band gap and high absorption coefficient of copper indium diselenide (CIS) make it as one of the most studied ternary chalcogenides for energy conversion. Low cost methods, such as electrochemical deposition are very beneficial because of large scale production possibility, minimum waste of components and no requirement of pure starting materials. The pulse electrodeposition allows independent variation of duty cycle. In this study pulse electrodeposition of polycrystalline thin film of CuInSe2 (CIS) onto ITO glass substrates from aqueous solution containing CuSO4, In2(SO4)3 and SeO2 was carried out. The probable potential for deposition was determined as -0.9 V from cyclic voltammogram. The deposited film was annealed at 400°C under nitrogen gas flow to provide neutral atmosphere to improve the crystalline quality and remove excess selenium. The film was analyzed using X-ray diffraction which confirmed that CIS deposit has tetragonal structure. The chalcopyrite formation and consistency in terms of stoichiometry in the deposit were proved. The optical property of the thin film was determined base on the measurement by using UV-Vis spectrophotometer. The direct band gap for the thin film is around 1.21 eV. As a result, the deposited CIS thin film is a potential candidate to be used in solar cell devices as an energy convertor. Atomic force microscope was employed to monitor the effect of duty cycles on the morphology of the thin film. It is revealed that with increasing duty cycle the surface morphology shift from smooth to dendrite structure. Photo-electrochemical characterization was performed under chopped white light in acidic redox media. It was showed that CIS film is a photosensitive material and stands as p and n-p type semiconductors by adjusting different duty cycles. The photoactivity of the films was highly affected by their surface morphology

Modelling and Analysis Using GROOVE

In this paper we present case studies that describe how the graph transformation tool GROOVE has been used to model problems from a wide variety of domains. These case studies highlight the wide applicability of GROOVE in particular, and of graph transformation in general. They also give concrete templates for using GROOVE in practice. Furthermore, we use the case studies to analyse the main strong and weak points of GROOVE

Verifying Monadic Second-Order Properties of Graph Programs

The core challenge in a Hoare- or Dijkstra-style proof system for graph programs is in defining a weakest liberal precondition construction with respect to a rule and a postcondition. Previous work addressing this has focused on assertion languages for first-order properties, which are unable to express important global properties of graphs such as acyclicity, connectedness, or existence of paths. In this paper, we extend the nested graph conditions of Habel, Pennemann, and Rensink to make them equivalently expressive to monadic second-order logic on graphs. We present a weakest liberal precondition construction for these assertions, and demonstrate its use in verifying non-local correctness specifications of graph programs in the sense of Habel et al.Comment: Extended version of a paper to appear at ICGT 201

Towards the specification and verification of modal properties for structured systems

System specification formalisms should come with suitable property specification languages and effective verification tools. We sketch a framework for the verification of quantified temporal properties of systems with dynamically evolving structure. We consider visual specification formalisms like graph transformation systems (GTS) where program states are modelled as graphs, and the program behavior is specified by graph transformation rules. The state space of a GTS can be represented as a graph transition system (GTrS), i.e. a transition system with states and transitions labelled, respectively, with a graph, and with a partial morphism representing the evolution of state components. Unfortunately, GTrSs are prohibitively large or infinite even for simple systems, making verification intractable and hence calling for appropriate abstraction techniques

Application of artificial neural networks for the optimisation of wetting contact angle for lead free Bi-Ag soldering alloys

In the recent years, electronic packaging provides significant research and development challenges across multiple disciplines such as performance, materials, reliability, thermals and interconnections. New technologies and techniques frequently adopted can be implemented in soldering alloys of semiconductor sectors in terms of optimisation. Wetting contact angle or wettability of solder alloys is one of the important factors which has got the attention of scholars. Hence in this study, due to the remarkable similarity over classical solder alloys (Pb-Sn), Bi-Ag solder was investigated. Data were collected through the effects of aging time variation and different weight percentages of Ag in solder alloys. The contact angle of the alloys with Cu plate was measured by optical microscopy. Artificial neural networks (ANNs) were applied on the measured datasets to develop a numerical model for further simulation. Results of the experiments and simulations showed that the coefficient of determination (R2) is around 0.97, which signifies that the ANN set up is appropriate for the evaluation

Application of ASTAR/precession electron diffraction technique to quantitatively study defects in nanocrystalline metallic materials

Nanocrystalline metallic materials have the potential to exhibit outstanding performance which leads to their usage in challenging applications such as coatings and biomedical implant devices. To optimize the performance of nanocrystalline metallic materials according to the desired applications, it is important to have a decent understanding of the structure, processing and properties of these materials. Various efforts have been made to correlate microstructure and properties of nanocrystalline metallic materials. Based on these research activities, it is noticed that microstructure and defects (e.g., dislocations and grain boundaries) play a key role in the behavior of these materials. Therefore, it is of great importance to establish methods to quantitatively study microstructures, defects and their interactions in nanocrystalline metallic materials. Since the mechanisms controlling the properties of nanocrystalline metallic materials occur at a very small length scale, it is fairly difficult to study them. Unfortunately, most of the characterization techniques used to explore these materials do not have the high enough spatial resolution required for the characterization of these materials. For instance, by applying complex profile-fitting algorithms to X-ray diffraction patterns, it is possible to get an estimation of the average grain size and the average dislocation density within a relatively large area. However, these average values are not enough for developing meticulous phenomenological models which are able to correlate microstructure and properties of nanocrystalline metallic materials. As another example, electron backscatter diffraction technique also cannot be used widely in the characterization of these materials due to problems such as relative poor spatial resolution (which is ~90 nm) and the degradation of Kikuchi diffraction patterns in severely deformed nano-size grain metallic materials. In this study, ASTAR/precession electron diffraction is introduced as a relatively new orientation microscopy technique to characterize defects (e.g., geometrically necessary dislocations and grain boundaries) in challenging nanocrystalline metallic materials. The capability of this characterization technique to quantitatively determine the dislocation density distributions of geometrically necessary dislocations in severely deformed metallic materials is assessed. Based on the developed method, it is possible to determine the distributions and accumulations of dislocations with respect to the nearest grain boundaries and triple junctions. Also, the competency of this technique to study the grain boundary character distributions of nanocrystalline metallic materials is presented

A Graph-Based Semantics Workbench for Concurrent Asynchronous Programs

A number of novel programming languages and libraries have been proposed that offer simpler-to-use models of concurrency than threads. It is challenging, however, to devise execution models that successfully realise their abstractions without forfeiting performance or introducing unintended behaviours. This is exemplified by SCOOP---a concurrent object-oriented message-passing language---which has seen multiple semantics proposed and implemented over its evolution. We propose a "semantics workbench" with fully and semi-automatic tools for SCOOP, that can be used to analyse and compare programs with respect to different execution models. We demonstrate its use in checking the consistency of semantics by applying it to a set of representative programs, and highlighting a deadlock-related discrepancy between the principal execution models of the language. Our workbench is based on a modular and parameterisable graph transformation semantics implemented in the GROOVE tool. We discuss how graph transformations are leveraged to atomically model intricate language abstractions, and how the visual yet algebraic nature of the model can be used to ascertain soundness.Comment: Accepted for publication in the proceedings of FASE 2016 (to appear