A Smart Products Lifecycle Management (sPLM) Framework - Modeling for Conceptualization, Interoperability, and Modularity

Autonomy and intelligence have been built into many of today’s mechatronic products, taking advantage of low-cost sensors and advanced data analytics technologies. Design of product intelligence (enabled by analytics capabilities) is no longer a trivial or additional option for the product development. The objective of this research is aimed at addressing the challenges raised by the new data-driven design paradigm for smart products development, in which the product itself and the smartness require to be carefully co-constructed. A smart product can be seen as specific compositions and configurations of its physical components to form the body, its analytics models to implement the intelligence, evolving along its lifecycle stages. Based on this view, the contribution of this research is to expand the “Product Lifecycle Management (PLM)” concept traditionally for physical products to data-based products. As a result, a Smart Products Lifecycle Management (sPLM) framework is conceptualized based on a high-dimensional Smart Product Hypercube (sPH) representation and decomposition. First, the sPLM addresses the interoperability issues by developing a Smart Component data model to uniformly represent and compose physical component models created by engineers and analytics models created by data scientists. Second, the sPLM implements an NPD3 process model that incorporates formal data analytics process into the new product development (NPD) process model, in order to support the transdisciplinary information flows and team interactions between engineers and data scientists. Third, the sPLM addresses the issues related to product definition, modular design, product configuration, and lifecycle management of analytics models, by adapting the theoretical frameworks and methods for traditional product design and development. An sPLM proof-of-concept platform had been implemented for validation of the concepts and methodologies developed throughout the research work. The sPLM platform provides a shared data repository to manage the product-, process-, and configuration-related knowledge for smart products development. It also provides a collaborative environment to facilitate transdisciplinary collaboration between product engineers and data scientists

Empirically-Grounded Construction of Bug Prediction and Detection Tools

There is an increasing demand on high-quality software as software bugs have an economic impact not only on software projects, but also on national economies in general. Software quality is achieved via the main quality assurance activities of testing and code reviewing. However, these activities are expensive, thus they need to be carried out efficiently. Auxiliary software quality tools such as bug detection and bug prediction tools help developers focus their testing and reviewing activities on the parts of software that more likely contain bugs. However, these tools are far from adoption as mainstream development tools. Previous research points to their inability to adapt to the peculiarities of projects and their high rate of false positives as the main obstacles of their adoption. We propose empirically-grounded analysis to improve the adaptability and efficiency of bug detection and prediction tools. For a bug detector to be efficient, it needs to detect bugs that are conspicuous, frequent, and specific to a software project. We empirically show that the null-related bugs fulfill these criteria and are worth building detectors for. We analyze the null dereferencing problem and find that its root cause lies in methods that return null. We propose an empirical solution to this problem that depends on the wisdom of the crowd. For each API method, we extract the nullability measure that expresses how often the return value of this method is checked against null in the ecosystem of the API. We use nullability to annotate API methods with nullness annotation and warn developers about missing and excessive null checks. For a bug predictor to be efficient, it needs to be optimized as both a machine learning model and a software quality tool. We empirically show how feature selection and hyperparameter optimizations improve prediction accuracy. Then we optimize bug prediction to locate the maximum number of bugs in the minimum amount of code by finding the most cost-effective combination of bug prediction configurations, i.e., dependent variables, machine learning model, and response variable. We show that using both source code and change metrics as dependent variables, applying feature selection on them, then using an optimized Random Forest to predict the number of bugs results in the most cost-effective bug predictor. Throughout this thesis, we show how empirically-grounded analysis helps us achieve efficient bug prediction and detection tools and adapt them to the characteristics of each software project

RFID Technology in Intelligent Tracking Systems in Construction Waste Logistics Using Optimisation Techniques

Construction waste disposal is an urgent issue for protecting our environment. This paper proposes a waste management system and illustrates the work process using plasterboard waste as an example, which creates a hazardous gas when land filled with household waste, and for which the recycling rate is less than 10% in the UK. The proposed system integrates RFID technology, Rule-Based Reasoning, Ant Colony optimization and knowledge technology for auditing and tracking plasterboard waste, guiding the operation staff, arranging vehicles, schedule planning, and also provides evidence to verify its disposal. It h relies on RFID equipment for collecting logistical data and uses digital imaging equipment to give further evidence; the reasoning core in the third layer is responsible for generating schedules and route plans and guidance, and the last layer delivers the result to inform users. The paper firstly introduces the current plasterboard disposal situation and addresses the logistical problem that is now the main barrier to a higher recycling rate, followed by discussion of the proposed system in terms of both system level structure and process structure. And finally, an example scenario will be given to illustrate the system’s utilization

Views and concerns and interrelationships : Lessons learned from developing the multi-View software engineering environment PIROL

Software-Entwicklungsumgebungen sind komplexe Systeme mit besonderen Anforderungen an Modularität und Anpaßbarkeit. Diese Arbeit beschreibt die Entwicklung der Umgebung PIROL. Die Beschreibung ist dabei in eine Abfolge der folgenden 12 Themen gegliedert. (1) Metamodellierung ist das Grundkonzept, nach dem PIROL seine Daten gemäß einem objektorientierten Datenmodell zerlegt, so daß beliebige Werkzeuge auch auf die Daten anderer Werkzeuge auf sinnvolle Art und Weise zuzugreifen können. (2) Das Metamodell wird zur persistenten Speicherung der Daten auf Konzepte des Repositories H-PCTE abgebildet. (3) Die Granularität eines Metamodells ist für die Effektivität und Effizienz des Gesamtsystems entscheidend. PIROL unterstützt hybride Modellierung als Kompromiß beider Extreme. (4) Durch Methoden des Metamodells wird Verhaltensmodellierung für verschiedenste Aufgaben unterstützt. (5) Ausnahmebehandlung wird systematisch unterstützt. (6) Verschiedene Mechanismen zur Wahrung der Datenintegrität sind enthalten. (7) Das System wurde nach einer Client-Server Architektur entwickelt, deren zentrale Komponente eine "Workbench" ist, die die Repository-Sprache Lua/P ausführt. (8) Steuerungsintegration erlaubt durch verteilte Steuerflüsse das enge Zusammenspiel lose gekoppelter Komponenten. (9) Die koordinierte Zusammenarbeit mehrerer Benutzer wird unterstützt. (10) Die logische Unabhängigkeit von Werkzeugen wird durch das neue Konzept der Dynamic View Connectors erreicht. (11) Allgemeine Dienste sind in der Umgebung einheitlich verfügbar. (12) Das System unterstützt die Weiterentwicklung. All diese Themengebiete sind sehr eng miteinander verzahnt und die Darstellung ist zu großem Teil der gegenseitigen Beeinflussung gewidmet. Es wird gezeigt, wie eine Großzahl der Entwurfsentscheidungen genau aus diesen Beeinflussungen motiviert sind. Die Beschreibung folgt damit dem Konzept der "Concern Interaction Matrix", das hier zur Bewältigung von Komplexität vorgeschlagen wird. Dabei werden Charakteristika einzelner Anliegen und einzelner Zusammenhänge herausgearbeitet. Die Beschreibung PIROLs wird durch die Liste der integrierten Werkzeuge, Ansätze von Laufzeit-Messungen und einige Betrachtungen zur Beurteilung abgerundet. Abschließend werden verschiedene Konzepte rund um den Begriff "Sichten" erörtert. Sichten sind ein zentrale Anliegen von PIROL. Außerdem generalisiert die Diskussion über die mehrdimensionale Darstellung des Hauptteiles. Es werden Begrifflichkeit, Konzepte und Techniken für Sichten in der Softwaretechnik vorgestellt und diskutiert. Dabei wird die Brücke geschlagen von Sichten in objektorientierten Datenbanken, über aspekt-orientierte Softwareentwicklung bis hin zum allgemeinen "Concern Modeling", zu dem die o.g. Methode einen Beitrag leisten soll. Sichten werden dabei als ein zentrales Konzept der Softwaretechnik neben Abstraktion und Zerlegung beurteilt. Dynamic View Connectors sind ein wesentlicher Beitrag von PIROL, durch den Datenbanksichten und aspektorientierte Programmierung zusammengeführt werden. Zwar ist der Sichten-Begriff längst nicht so scharf definiert, wie die Begriffe Abstraktion und Zerlegung, aber gerade die Überlappungen und Diskrepanzen, die durch Sichten abgebildet werden können, machen dies Konzept zu einem starken Strukturierungsprinzip, das zwar einigen Aufwand zur Behandlung von Inkonsistenzen erfordert, aber andererseits hilft, komplexe Systeme handhabbar und wartbar zu gestalten.Software engineering environments are complex systems with special requirements regarding modularity and adaptability. This thesis describes the development of the environment PIROL. The description is structured as a sequence of the following 12 concerns: (1) Meta modeling is the basic concept by which PIROL decomposes its data in accordance to an object-oriented data model. This allows arbitrary tools to access data of other tools in a meaningful way. (2) For persistent storage the model is mapped to the concepts of the repository H-PCTE. (3) The granularity of a meta model determines effectiveness and efficiency of the system. PIROL supports hybrid modeling as a compromise between extremes. (4) By methods of the meta model behavior modeling is supported for a wide range of tasks. (5) Exception handling is supported systematically. (6) Several mechanisms for preserving data integrity are integrated. (7) The system follows a client-server architecture. As its, central component the "workbench" executes the repository language LuaP. (8) Control integration allows for close cooperation of loosely coupled components by means of distributed control flows. (9) The coordinated cooperation of multiple users is supported. (10) Logical independence of tools is achieved by the novel concept of Dynamic View Connectors. (11) Common services are available throughout the environment in a uniform way. (12) The system is prepared for evolution. All these concerns are tightly interlocked. A considerable share of the presentation is dedicated to such mutual interactions. Is is shown, how a large number of design decisions is motivated exactly by these interactions. The description follows the concept of a "Concern Interaction Matrix" which is proposed for managing complexity. Characteristics of concerns and their interactions are elaborated. The description of PIROL is completed by a list of integrated tools, initial performance measurements and evaluation. Finally, several concepts relating to the notion of "views" are discussed. Views are a central concern of PIROL. Furthermore, the discussion generalizes over the multi-dimensional presentation in the body of this thesis. Notions, concepts and techniques for views in software engineering are presented and discussed. This discussion connects views in object-oriented databases, aspect-oriented software development and general "concern modeling", to which the method of "Concern Interaction Matrices" contributes. Views are regarded as a central concept of software engineering at the same level as abstraction and decomposition. Dynamic View Connectors are a significant contribution of PIROL that combines database views and aspect-oriented programming. The notion of "views" is defined with far less precision than abstraction and decomposition, but indeed by the overlap and mismatches, which can be captured by views, this concept is a strong principle for structuring software and information. Effort is needed for handling inconsistencies as they may arise, but after all, views are a suitable means for managing the complexity of systems and for designing these systems for evolution

Supporting Collaboration in Mobile Environments

Continued rapid improvements in the hardware capabilities of mobile computing devices is driving a parallel need for a paradigm shift in software design for such devices with the aim of ushering in new classes of software applications for devices of the future. One such class of software application is collaborative applications that seem to reduce the burden and overhead of collaborations on human users by providing automated computational support for the more mundane and mechanical aspects of a cooperative effort. This dissertation addresses the research and software engineering questions associated with building a workflow-based collaboration system that can operate across mobile ad hoc networks, the most dynamic type of mobile networks that can function without dependence on any fixed external resources. While workflow management systems have been implemented for stable wired networks, the transition to a mobile network required the development of a knowledge management system for improving the predictability of the network topology, a mobility-aware specification language to specify workflows, and its accompanying algorithms that help automate key pieces of the software. In addition to details of the formulation, design, and implementation of the various algorithms and software components. this dissertation also describes the construction of a custom mobile workflow simulator that can be used to conduct simulation experiments that verify the effectiveness of the approaches presented in this document and beyond. Also presented are empirical results obtained using this simulator that show the effectiveness of the described approaches