Ring: A unifying meta-model and infrastructure for Smalltalk source code analysis tools

Source code management systems record different versions of code. Tool support can then compute deltas between versions. To ease version history analysis we need adequate models to represent source code entities. Now naturally the questions of their definition, the abstractions they use, and the APIs of such models are raised, especially in the context of a reflective system which already offers a model of its own structure.We believe that this problem is due to the lack of a powerful code meta-model as well as an infrastructure. In Smalltalk, often several source code meta-models coexist: the Smalltalk reflective API coexists with the one of the Refactoring engine or distributed versioning system such as Monticello or Store. While having specific meta-models is an adequate engineered solution, it multiplies meta-models and it requires more maintenance efforts (e.g., duplication of tests, transformation between models), and more importantly hinders navigation tool reuse when meta-models do not offer polymorphic APIs.As a first step to provide an infrastructure to support history analysis, this article presents Ring, a unifying source code meta-model that can be used to support several activities and proposes a unified and layered approach to be the foundation for building an infrastructure for version and stream of change analyses. We re-implemented three tools based on Ring to show that it can be used as the underlying meta-model for remote and off-image browsing, scoping refactoring, and visualizing and analyzing changes. As a future work and based on Ring we will build a new generation of history analysis tools.     

Enterprise modeling of a project-oriented fractal company for SMEs networking

To address competitive threats and concentrate in their core competences and strengths networking is the alternative of choice for survival and prosperity of most small and medium enterprises (SMEs) all over the world. For networking advantages to be fully grasped, an enterprise model describing the main organizational structure and relationships, information flows, management roles, actor behavior and constraints in the network is required. This work presents a conceptual model for SMEs networking based on the fractal company approach and concepts like projects, resources, goals, specialized actors, plans, and relationships thereof. The fractal company idea is a conceptual enterprise design that seeks to achieve a high degree of flexibility to react and adapt quickly to environmental changes using decentralized and autonomous organizational units known as fractals. In this work, each fractal management unit is modeled as a project. The fractal company is thus seen as a temporary set of client–server and delegation-to-do relationships among project-managers interacting so as to diversify product portfolio, gain economy of scale and share expensive costs. The proposed enterprise model can be used to specify the requirements of an integrated information and management system for virtual SMEs networking. The enterprise model is exemplified using a case study related to process development of a new pharmaceutical product in a SME network of the specialty chemical sector.     

中小企业EIP的研究与设计

中小企业组织结构较为简单,并且人力资源相对较弱、财力抗风险能力相对较差。所以将EIP系统进行模块化分解,形成各个灵活的子系统,不仅可以减少中小企业EIP资金的投入,而且可以由企业根据发展的需要合理组织和搭配这些灵活的子系统,形成适合企业自身的EIP系统。由此,提出了中小企业EIP的解决方案：借鉴标准EIP的某些概念,取标准EIP的局部,运用XML和Web Services技术进行企业现有系统资源集成和更多的个性化的定制,形成适合中小企业的企业信息门户。     

Genericity for model management operations

Models are the core assets in model-driven engineering, and are therefore subject to all kind of manipulations, such as refactorings, animations, transformations into other languages, comparisons and merging. This set of model-related activities is known as model management. Even though many languages and approaches have been proposed for model management, most of them are type-centric, specific to concrete meta-models, and hence leading to specifications with a low level of abstraction and difficult to be reused in practice. In this paper, we introduce ideas from generic programming into model management to raise the level of abstraction of the specifications of model manipulations and facilitate their reuse. In particular we adopt generic meta-model concepts as an intermediate, abstract meta-model over which model management specifications are defined. Such meta-model concepts are mapped to concrete meta-models, so that specifications can be applied to families of meta-models satisfying the concept requirements. As a proof of concept, we show the implementation of these ideas using the Eclipse Modeling Framework and the Epsilon family of languages for model management.     

Hybrid genetic algorithm and association rules for mining workflow best practices

Business workflow analysis has become crucial in strategizing how to create competitive edge. Consequently, deriving a series of positively correlated association rules from workflows is essential to identify strong relationships among key business activities. These rules can subsequently, serve as best practices. We have addressed this problem by hybridizing genetic algorithm with association rules. First, we used correlation to replace support-confidence in genetic algorithm to enable dynamic data-driven determination of support and confidence, i.e., use correlation to optimize the derivation of positively correlated association rules. Second, we used correlation as fitness function to support upward closure in association rules (hitherto, association rules support only downward closure). The ability to support upward closure allows derivation of the most specific association rules (business model) from less specific association rules (business meta-model) and generic association rules (reference meta-model). Downward closure allows the opposite. Upward-downward closures allow the manager to drill-down and analyze based on the degree of dependency among business activities. Subsequently, association rules can be used to describe best practices at the model, meta-model and reference meta-model levels with the most general positively dependent association rules as reference meta-model. Experiments are based on an online hotel reservation system.     

Focus of B-to-B e-commerce initiatives and related benefits in manufacturing small- and medium-sized enterprises

Empirical research into business-to-business e-commerce issues involving manufacturing small- and medium-sized enterprises (SMEs) is still embryonic. In an attempt to partially fill this gap, this paper presents empirical data from an electronic survey conducted among 96 manufacturing SMEs to investigate e-commerce initiatives and their related benefits. E-commerce initiatives are assessed using a set of 36 business processes that can be conducted electronically. These processes were classified according to their focus: customer (downstream), supplier (upstream) or in-house. The research findings point to four main profiles of manufacturing SMEs with different e-commerce focuses. The first group seems to lack any focus or may still be exploring e-commerce opportunities. The second and third groups are supplier- and customer-focused, respectively. The fourth group consists of the more involved SMEs that have leveraged their e-commerce initiatives with both their customers and their suppliers. Results also suggest the existence of a close alignment between e-commerce focus and related benefits.An earlier and much shorter version of this paper was published in the Proceedings of the 37th Hawaii International Conference on System Sciences (HICSS-37). Helpful comments from two anonymous reviewers were greatly appreciated. The authors gratefully acknowledge financial support from SSHRC, FCAR and NSERC.     

From types to type requirements: genericity for model-driven engineering

Model-driven engineering (MDE) is a software engineering paradigm that proposes an active use of models during the development process. This paradigm is inherently type-centric, in the sense that models and their manipulation are defined over the types of specific meta-models. This fact hinders the reuse of existing MDE artefacts with other meta-models in new contexts, even if all these meta-models share common characteristics. To increase the reuse opportunities of MDE artefacts, we propose a paradigm shift from type-centric to requirement-centric specifications by bringing genericity into models, meta-models and model management operations. For this purpose, we introduce so-called concepts gathering structural and behavioural requirements for models and meta-models. In this way, model management operations are defined over concepts, enabling the application of the operations to any meta-model satisfying the requirements imposed by the concept. Model templates rely on concepts to define suitable interfaces, hence enabling the definition of reusable model components. Finally, similar to mixin layers, templates can be defined at the meta-model level as well, to define languages in a modular way, as well as layers of functionality to be plugged-in into other meta-models. These ideas have been implemented in MetaDepth, a multi-level meta-modelling tool that integrates action languages from the Epsilon family for model management and code generation.     

AspectMaps: Extending Moose to visualize AOP software

When using aspect-oriented programming the application implicitly invokes the functionality contained in the aspects. Consequently program comprehension of such a software is more intricate. To alleviate this difficulty we developed the AspectMaps visualization and tool. AspectMaps extends the Moose program comprehension and reverse engineering platform with support for aspects, and is implemented using facilities provided by Moose. In this paper we present the AspectMaps tool, and show how it can be used by performing an exploration of a fairly large aspect-oriented application. We then show how we extended the FAMIX meta-model family that underpins Moose to also provide support for aspects. This extension is called ASPIX, and thanks to this enhancement Moose can now also treat aspect-oriented software. Finally, we report on our experiences using some of the tools in Moose; Mondrian to implement the visualization, and Glamour to build the user interface. We discuss how we were able to implement a sizable visualization tool using them and how we were able to deal with some of their limitations.Note: This paper uses colors extensively. Please use a color version to better understand the ideas presented here.     

Towards industrial robots as a service (IRaaS): Flexibility,usability, safety and business models

Industrial robots form an integral part of today's manufacturing industry, due to their high versatility, precision, and fatigue proof nature. Yet, many small and medium sized enterprises (SMEs) still predominantly rely on manual labor. The main barriers that prevent SMEs from utilizing robots to a larger degree are described to be the large initial investment, uncertainty about costs (total cost of ownership), and lack of expertise. An opportunity to eliminate these barriers can be found in servitisation. While paradigms such as software as a service (SaaS) or Robot as a Service (RaaS) already exist, these focus mostly on software (functionality) via cloud computing. In this paper, a new paradigm based on software and hardware is proposed as Industrial Robots as a Service (IRaaS), which is composed of four elements: Flexibility (Plug and Produce, mobility), Usability (Easy Programming, Intuitive Interaction), Safety (Standards, Strategies), and Business Models (Time-based, Usage-based). To provide an overview of the current state-of-the-art a scoping survey is performed on each of the four key elements from an IRaaS perspective.     

Accomplishing the layered modular architecture in digital innovation: The case of the car’s driver information module

Architectural theory of digital innovation contends that, to enhance physical products with digital capabilities, a layered modular architecture is required. This architecture hybridizes hierarchically arranged components of physical products with modules of digital functionality configured into layers. Despite considerable research adopting this architectural perspective on digital innovation, questions of how this hybrid architecture is accomplished organizationally and technologically lack both conceptual clarity and empirical illustration. Noting pervasive tensions that characterize digital innovation efforts and the contradictions between hierarchical and layered modular configurations, this paper seeks to answer the following research question: Given that the layered modular architecture needs to hybridize modular arrangements with opposing logics, how is it accomplished?Employing the concepts of digitalization, physical product hierarchy and digital control system to better theorize a product architecture’s movement from a modular to a layered modular architecture accompanied by organizational structures that enable this change, we abductively analyze the increasing digitization of a car’s Driver Information Module (DIM) over a 10 year period. We conclude by proposing three transformations through which the layered modular architecture is accomplished.     

A digital twin emulator of a modular production system using a data-driven hybrid modeling and simulation approach

Virtual commissioning is a key technology in Industry 4.0 that can address issues faced by engineers during early design phases. The process of virtual commissioning involves the creation of a Digital Twin—a dynamic, virtual representation of a corresponding physical system. The digital twin model can be used for testing and verifying the control system in a simulated virtual environment to achieve rapid set-up and optimization prior to physical commissioning. Additionally, the modular production control systems, can be integrated and tested during or prior to the construction of the physical system. This paper describes the implementation of a digital twin emulator of an automated mechatronic modular production system that is linked with the running programmable logic controllers and allow for exchanging near real-time information with the physical system. The development and deployment of the digital twin emulator involves a novel hybrid simulation- and data-driven modeling approach that combines Discrete Event Simulation and Agent Based Modeling paradigms. The Digital Twin Emulator can support design decisions, test what-if system configurations, verify and validate the actual behavior of the complete system off-line, test realistic reactions, and provide statistics on the system’s performance.

     

Multiagent meta-model for strategic decision support

This research describes a meta-model which can generate multiagents system (MAS) of strategic decision support. These MAS profit from new concepts of bargaining with learning to determine the cooperation between agents. They answer an insufficiency of the concept of bargaining in the game theory which is proved in this article. The original framework of the meta-model is characterized by three essential functions provided with a technique of learning: the search for typical plan of decisions adapted to the problem and the search for the coalitions in the spatial and temporal dimension. It allows an adaptation to all the types of strategic decision support.     

Combining unit and specification-based testing for meta-model validation and verification

Meta-models play a cornerstone role in Model-Driven Engineering as they are used to define the abstract syntax of modelling languages, and so models and all sorts of model transformations depend on them. However, there are scarce tools and methods supporting their Validation and Verification (V&V), which are essential activities for the proper engineering of meta-models.In order to fill this gap, we propose two complementary meta-model V&V languages. The first one has similar philosophy to the xUnit framework, as it enables the definition of meta-model unit test suites comprising model fragments and assertions on their (in-)correctness. The second one is directed to express and verify expected properties of a meta-model, including domain and design properties, quality criteria and platform-specific requirements.As a proof of concept, we have developed tooling for both languages in the Eclipse platform, and illustrate its use within an example-driven approach for meta-model construction. The expressiveness of our languages is demonstrated by their application to build a library of meta-model quality issues, which has been evaluated over the ATL zoo of meta-models and some OMG specifications. The results show that integrated support for meta-model V&V (as the one we propose here) is urgently needed in meta-modelling environments.     

A framework and computer system for knowledge-level acquisition,representation, and reasoning with process knowledge

The development of knowledge-based systems is usually approached through the combined skills of software and knowledge engineers (SEs and KEs, respectively) and of subject matter experts (SMEs). One of the most critical steps in this task aims at transferring knowledge from SMEs’ expertise to formal, machine-readable representations, which allow systems to reason with such knowledge. However, this process is costly and error prone. Alleviating such knowledge acquisition bottleneck requires enabling SMEs with the means to produce the target knowledge representations, minimizing the intervention of KEs. This is especially difficult in the case of complex knowledge types like processes. The analysis of scientific domains like Biology, Chemistry, and Physics uncovers: (i) that process knowledge is the single most frequent type of knowledge occurring in such domains and (ii) specific solutions need to be devised in order to allow SMEs to represent it in a computational form. We present a framework and computer system for the acquisition and representation of process knowledge in scientific domains by SMEs. We propose methods and techniques to enable SMEs to acquire process knowledge from the domains, to formally represent it, and to reason about it. We have developed an abstract process metamodel and a library of problem solving methods (PSMs), which support these tasks, respectively providing the terminology for SME-tailored process diagrams and an abstract formalization of the strategies needed for reasoning about processes. We have implemented this approach as part of the DarkMatter system and formally evaluated it in the context of the intermediate evaluation of Project Halo, an initiative aiming at the creation of question answering systems by SMEs.     

Service based meta-model for the development of distributed embedded real-time systems

The development complexity of Distributed Embedded Real-Time Systems (DERTS) can be reduced by the use of Service-Oriented Computing (SOC). However, the existing modeling methods allow modeling of either DERTS or SOC concepts and there is a lack of meta-model for Service-Oriented development of DERTS. This paper proposes a service-based meta-model for DERTS, along with the constraints of the elements of the meta-model. A Smart Home case study was designed to validate the meta-model. This meta-model could not only be beneficial for Service-Oriented development of DERTS, but can also be used at the Platform Independent Model (PIM) level of MDD.     

Introduction of static quality analysis in small- and medium-sized software enterprises: experiences from technology transfer

Today, small- and medium-sized enterprises (SMEs) in the software industry face major challenges. Their resource constraints require high efficiency in development. Furthermore, quality assurance (QA) measures need to be taken to mitigate the risk of additional, expensive effort for bug fixes or compensations. Automated static analysis (ASA) can reduce this risk because it promises low application effort. SMEs seem to take little advantage of this opportunity. Instead, they still mainly rely on the dynamic analysis approach of software testing. In this article, we report on our experiences from a technology transfer project. Our aim was to evaluate the results static analysis can provide for SMEs as well as the problems that occur when introducing and using static analysis in SMEs. We analysed five software projects from five collaborating SMEs using three different ASA techniques: code clone detection, bug pattern detection and architecture conformance analysis. Following the analysis, we applied a quality model to aggregate and evaluate the results. Our study shows that the effort required to introduce ASA techniques in SMEs is small (mostly below one person-hour each). Furthermore, we encountered only few technical problems. By means of the analyses, we could detect multiple defects in production code. The participating companies perceived the analysis results to be a helpful addition to their current QA and will include the analyses in their QA process. With the help of the Quamoco quality model, we could efficiently aggregate and rate static analysis results. However, we also encountered a partial mismatch with the opinions of the SMEs. We conclude that ASA and quality models can be a valuable and affordable addition to the QA process of SMEs.     

A meta-modelling framework for knowledge consistency in collaborative design

The design of complex system requires a lot of interactions between experts and then between numerous Computer Aided X software (CAX) (where X can be Design (CAD), Engineering (CAE), Manufacturing (CAM), etc.). In order to improve the consistency of the whole system design and the related data and information, knowledge crossing the expertises must be tracked and formalized regarding a shared reference. That means that instead of defining a large reference models to which each expert refers to, a light collaborative model is defined enabling to connect data from each expert model to adhoc data from other expert models, following the least commitment principle. In this topic, a new meta-model is proposed in a Model-Driven Engineering approach to manage the integration of heterogeneous experts’ knowledge models in a collaborative process. The structure of the proposed knowledge meta-model is defined taking into account the complexity of knowledge definition and the properties of its components. This meta-model is split in a meta-model of data on one hand and a Collaboration Meta-Model in the other hand, to represent the distinction between the core concepts of knowledge and additional elements serving to represent the relation between these concepts, and between concepts of heterogeneous experts’ models. The proposed meta-model is illustrated on an industrial case study to highlight the way to put it in use, and its interests to enable collaboration between experts throughout the design process.     

An investigation of ‘build vs. buy’ decision for software acquisition by small to medium enterprises

ContextThe prevalence of computing and communication technologies, combined with the availability of sophisticated and highly specialised software packages from software vendors has made package acquisition a viable option for many organisations. While some research has addressed the factors that influence the selection of the software acquisition method in large organisations, little is known about the factors affecting SMEs.ObjectiveTo provide an understanding of factors that affect the decision process of software acquisition for SMEs. It is expected that results from this study: (i) will assist the SME decision process for software acquisition, and (ii) will assist policy makers in terms of developing appropriate guidelines for SME software acquisition.MethodA positivist research perspective has been adopted involving semi-structured interviews in eight SMEs in Thailand with the interviewees assigning to each of the potential factors.ResultsThe study found that the following factors affect both SMEs and large organisations: requirements fit, cost, scale and complexity, commoditization/flexibility, time, in-house experts, support structure, and operational factors. Factors mainly applying to large organisations were strategic role of the software, intellectual property concerns, and risk, Factors particularly relevant to SMEs (ubiquitous systems, availability of free download, and customizable to specific government/tax regulations).ConclusionThe results suggest that: (i) when deciding on their software acquisition method, SMEs are generally less likely to pursue a long-term vision compared with larger organisations, possibly because SMEs mainly serve their local markets; and (ii) contrary to the large organisations, the role that the IT plays in SMEs may not be as vital to the SMEs’ core business processes, to their supply chains, and/or to the management of their customer relationship. Furthermore, neither the level of technological intensity nor size of the SME appears to affect the ranks given by the interviewees for the various factors.