The cleanroom case study in the Software Engineering Laboratory: Project description and early analysis

This case study analyzes the application of the cleanroom software development methodology to the development of production software at the NASA/Goddard Space Flight Center. The cleanroom methodology emphasizes human discipline in program verification to produce reliable software products that are right the first time. Preliminary analysis of the cleanroom case study shows that the method can be applied successfully in the FDD environment and may increase staff productivity and product quality. Compared to typical Software Engineering Laboratory (SEL) activities, there is evidence of lower failure rates, a more complete and consistent set of inline code documentation, a different distribution of phase effort activity, and a different growth profile in terms of lines of code developed. The major goals of the study were to: (1) assess the process used in the SEL cleanroom model with respect to team structure, team activities, and effort distribution; (2) analyze the products of the SEL cleanroom model and determine the impact on measures of interest, including reliability, productivity, overall life-cycle cost, and software quality; and (3) analyze the residual products in the application of the SEL cleanroom model, such as fault distribution, error characteristics, system growth, and computer usage

Operationally Responsive Space (ORS): An Architecture and Enterprise Model for Adaptive Integration, Test and Logistics

The capability to rapidly deploy tactical satellites to meet a Joint Force Commander\u27s immediate battlespace requirements is a well-documented joint capability need. Key U.S. strategic documentation cites the need for the capability to maintain persistent surveillance or an unblinking eye over battlespace and to rapidly reconstitute critical space capabilities to preserve situational awareness. The warfighter requires a tactical space-based deployment capability which employs a request to launch and operational deployment window of 90 to 120 days. This master\u27s thesis executed two (2) major areas of work: apply, and reinforce the Operationally Responsive Space (ORS) mission tasks using the Joint Capabilities Integration Development System (JCIDS) process; then based on capability gap data generated from the process, analyze and define the capability gap of an ORS Adaptive Integration, Test and Logistics (IT&L) process for payload to bus deployment to meet the identified time scales. This document recommends engineering solutions and processes for the ORS IT&L to-be state for this warfighter capability. The ORS adaptive IT&L CONOPS developed as part of this work focuses on the Tactical Satellite Rapid Deployment System (TSRDS), which is an adaptive integration, test and logistics capability that enables rapid and effective payload to bus integration to meet a 90- to 120-day warfighter window

Big Data Testing Techniques: Taxonomy, Challenges and Future Trends

Big Data is reforming many industrial domains by providing decision support through analyzing large data volumes. Big Data testing aims to ensure that Big Data systems run smoothly and error-free while maintaining the performance and quality of data. However, because of the diversity and complexity of data, testing Big Data is challenging. Though numerous research efforts deal with Big Data testing, a comprehensive review to address testing techniques and challenges of Big Data is not available as yet. Therefore, we have systematically reviewed the Big Data testing techniques evidence occurring in the period 2010-2021. This paper discusses testing data processing by highlighting the techniques used in every processing phase. Furthermore, we discuss the challenges and future directions. Our findings show that diverse functional, non-functional and combined (functional and non-functional) testing techniques have been used to solve specific problems related to Big Data. At the same time, most of the testing challenges have been faced during the MapReduce validation phase. In addition, the combinatorial testing technique is one of the most applied techniques in combination with other techniques (i.e., random testing, mutation testing, input space partitioning and equivalence testing) to find various functional faults through Big Data testing.Comment: 32 page

TOWARD SHIPBUILDING 4.0 - AN INDUSTRY 4.0 CHANGING THE FACE OF THE SHIPBUILDING INDUSTRY

The Shipbuilding 4.0 at the principles of the Industry 4.0 will transform the design, manufacturing, operation, shipping, services, production systems, maintenance and value chains in the all aspects of the shipbuilding industry. Over the last few years, the fourth industrial revolution has spread in almost all industries. The whole world is talking about Industry 4.0 which has increased implication in the manufacturing process and the future of the work. The impact of the Shipbuilding 4.0 will be significant. In the past, shipbuilding industry where continuously improved with new machines, software and new implemented organizational restructuring. In today shipbuilding industry, there are three main problems that are considered; production efficiency, the ship safety, cost efficiency and energy conservation and environmental protection. In order to create new value, the ship must become a Smart Ship capable of “thinking”, and to be produced in Smart Shipbuilding Process. The aim of this article is a review of the present academic and industrial progress of this new industrial revolution wave in the shipbuilding sector called Shipbuilding 4.0 (Shipping 4.0, Maritime 4.0, Shipyard 4.0). Reviewed publications were analyzed different topics and level of improvements in the industrial aspects of the society. The implementation of the Shipbuilding 4.0 in the shipbuilding industry, presents the future, creating new value in the process, creating new demands with reduction in production and operational cost while increasing production efficiency

BIM Integrated and Reference Process-based Simulation Method for Construction Project Planning

Die Verwendung von Simulationen zur Unterstützung traditioneller Planungsverfahren für Bauprojekte hat viele Vorteile, die in verschiedenen akademischen Forschungen vorgestellt wurden. Viele Anwendungen haben erfolgreich das Potenzial der Simulationsmethode zur Verbesserung der Qualität der Projektplanung demonstriert. Doch eine breite Anwendung der Simulationsmethoden zur Unterstützung der Planung von Bauprojekten konnte sich in der Praxis bis zum jetzigen Zeitpunkt nicht durchsetzen. Aufgrund einiger großer Hindernisse und Herausforderungen ist der Einsatz im Vergleich zu anderen Branchen noch sehr begrenzt. Die Komplexität sowie die dynamischen Wechselprozesse der unterschiedlichen Bauvorhaben stellen die erste Herausforderung dar.Die Anforderungen machen es sehr schwierig die verschieden Situationen realistisch zu modellieren und das Verhalten von Bauprozessen und die Interaktion mit den zugehörigen Ressourcen für reale Bauvorhaben darzustellen. Das ist einer der Gründe für den Mangel an speziellen Simulationswerkzeugen in der Bauprojektplanung. Die zweite Herausforderung besteht in der großen Menge an Projektinformationen, die in das Simulationsmodell integriert und während des gesamten Lebenszyklus des Projekts angepasst werden müssen. Die Erstellung von Simulationsmodellen, Simulationsszenarien sowie die Analyse und Verifizierung der Simulationsergebnisse ist langwierig. Ad-hoc Simulation sind daher nicht möglich. Zur Erstellung zuverlässiger Simulationsmodelle sind daher umfangreiche Ressourcen und Mitarbeiter mit speziellen Fachwissen erforderlich. Die vorgestellten Herausforderungen verhindern die breite Anwendung der Simulationsmethode zur Unterstützung der Bauprojektplanung und das Einsetzen der Software als wesentlicher Bestandteil des Arbeitsablaufes für die Bauplanung in der Praxis. Die Forschungsarbeit in dieser Arbeit befasst sich mit diesen Herausforderungen durch die Entwicklung eines Ansatzes sowie einer Plattform für die schnelle Aufstellung von Simulationsmodellen für Bauprojekte. Das Hauptziel dieser Forschung ist die Entwicklung eines integrierten und referenzmodellbasierten BIM Simulationsansatz zur Unterstützung der Planung von Bauprojekten und die Möglichkeit der Zusammenarbeit aller am Planungs- und Simulationsprozess beteiligten Akteure. Die erste Herausforderung wird durch die Einführung eines RPM-Konzepts (Reference Process Model) durch die Modellierung von Konstruktionsprozessen unter Verwendung von Business Process Modeling and Notation (BPMN) angegangen. Der Vorteil der RPM Modelle ist das sie bearbeitet und modifiziert können und dass sie automatisch als einsatzbereite Module in Simulationsmodelle umgewandelt werden können. Die RPM-Modelle enthalten auch Informationen zu Ressourcenanforderungen und andere verwandte Informationen für verschiedene Baubereiche mit unterschiedlichen Detaillierungsgraden. Die Verwendung von BPMN hat den Vorteil, dass die Simulationsmodellierung für das Projektteam, einschließlich derjenigen, die sich nicht mit der Simulation auskennen, flexibler, interoperabler und verständlicher ist. Bei diesem Ansatz ist die Modellierung von Referenzprozessmodellen vollständig von den Simulationskernkomponenten getrennt, um das Simulations-Toolkit generisch und erweiterbar für verschiedenste Konstruktionsbereiche wie Gebäude und Brücken. Der vorgestellte Forschungsansatz unterstützt die kontinuierliche Anwendung von Simulationsmodellen während des gesamten Projektlebenszyklus. Die Simulationsmodelle, die zur Unterstützung der Planung in der frühen Entwurfsphase erstellt werden, können von Simulationsexperten während der gesamten Planungs- und Bauphase weiter ausgebaut und aktualisiert werden. Die zweite Herausforderung wird durch die direkte Integration der Building Information Modeling (BIM) -Methode in die Simulationsmodellierung auf der Grundlage des Industry Foundation Classes-IFC (ISO 16739) , dem am häufigsten verwendeten BIM-Austauschformat, angegangen. Da die BIM-Modelle einen wichtigen Teil der Eingabeinformationen von Simulationsmodellen enthalten, können sie als Grundlage für die Visualisierung von Ergebnissen in Form von 4D-BIM-Modellen verwendet werden. Diese Integration ermöglicht die schnelle und automatische Filterung und Extraktion sowie die Umwandlung notwendiger Informationen aus BIM Entwurf-Modellen. Um die Erstellung detaillierter Projektmodelle zu beschleunigen, wurde eine spezielle Methode für die halbautomatische Top-Down-Detaillierung von Projektstammmodelle entwickelt, die notwendige Eingangsdaten für die Simulationsmodelle sind. Diese Methode bietet den Vorteil, dass Konstruktionsalternativen mit minimalen Änderungen am Simulationsmodell untersucht werden können. Der entwickelte Ansatz wurde als Software- Prototyp in Form eines modularen Construction Simulation Toolkit (CST) basierend auf der Discrete Event Simulation (DES)- Methode und eines Collaboration- Webportals (ProSIM) zum Verwalten von Simulationsmodellen implementiert. Die so eingebettete Simulation ermöglicht mit minimalen Änderungen die Bewertung von Entwurfsalternativen und Konstruktionsmethoden auf den Bauablauf. Produktions- und Logistiksvorgänge können gleichzeitig in einer einheitlichen Umgebung simuliert werden und berücksichtigen die gemeinsam genutzten Ressourcen und die Interaktion zwischen Produktions- und Logistikaktivitäten. Es berücksichtigt auch die Änderungen im Baustellenlayout während der Konstruktionsphase. Die Verifizierung und Validierung des vorgeschlagenen Ansatzes wird durch verschiedene hypothetische und reale Bauprojekten durchgeführt.:1 Introduction: motivation, problem statement and objectives 1.1 Motivation 1.2 Problem statement 1.3 Objectives 1.4 Thesis Structure 2 Definitions, Related work and background information 2.1 Simulation definition 2.2 Simulation system definition 2.3 Discrete Event Simulation 2.5 How simulation works 2.6 Workflow of simulation study 2.7 Related work 2.8 Traditional construction planning methods 2.8.1 Gantt chart 2.8.2 Critical Path Method (CPM) 2.8.3 Linear scheduling method/Location-based scheduling 2.9 Business Process Model and Notation 2.10Workflow patterns 2.10.1 Supported Control Flow Patterns 3 Reference Process-based Simulation Approach 3.1 Reference Process-based simulation approach 3.2 Reference Process Models 3.3 Reference process model for single task 3.4 Reference process models for complex activities 3.5 Process Pool 3.6 Top-down automatic detailing of project schedules 3.7 Simulation model formalism 3.8 Fundamental design concepts and application scope 4 Data Integration between simulation and construction Project models 4.1 Data integration between BIM models and simulation models 4.1.1 Transformation of IFC models to Graph models 4.1.2 Checking BIM model quality 4.1.3 Filtering of BIM models 4.1.4 Semantic enrichment of BIM models 4.1.5 Reference process models and BIM models 4.2 Reference Process Models and resources models 4.3 Process models and productivity factors 5 Construction Simulation Toolkit 5.1 System architecture and implementation 5.2 Basic steps to create a CST simulation model 5.3 CST Simulation components 5.3.1 Input components 5.3.2 Process components 5.3.3 Output components 5.3.4 Logistic components 5.3.5 Collaboration platform ProSIM 6 Case Studies and Validation 6.1 Verification and Validation of Simulation Models 6.2 Verification and validation techniques for simulation models 6.3 Case study 1: generic planning model 6.4 Case study 2: high rise building 6.4.1 Scenario I: effect of changing number of workers on structural work duration 6.4.2 Scenario II: simulation of structural work on operation level 6.4.3 Scenario III: automatic generation of detailed project schedule 6.5 Case study 3: airport terminal building 6.5.1 Multimodel Container 6.5.2 Scenario I: automatic generation of detailed project schedule 6.5.3 Scenario II: Find the minimal project duration 6.5.4 Scenario III: construction work for a single floor 7 Conclusions and Future Research 7.1 Conclusions 7.2 Outlook of the possible future research topics 7.2.1 Integration with real data collecting 7.2.2 Multi-criteria optimisation 7.2.3 Extend the control-flow and resource patterns 7.2.4 Consideration of further structure domains 7.2.5 Considering of space allocation and space conflicts 8 Appendix - Scripts 9 Appendix B - Reference Process Models 9.1 Reference Process Models for structural work 9.1.1 Wall 9.1.2 Roof 9.1.3 Foundations 9.1.4 Concrete work 9.1.5 Top-Down RPMs for structural work in a work section 10 Appendix E 10.1 Basic elements of simulation models in Plant Simulation 10.2 Material Flow Objects 11 ReferencesUsing simulation to support construction project planning has many advantages, which have been presented in various academic researches. Many applications have successfully demonstrated the potential of using simulation to improve the quality of construction project planning. However, the wide adoption of simulation has not been achieved in practice yet. It still has very limited use compared with other industries due to some major obstacles and challenges. The first challenge is the complexity of construction processes and projects planning methods, which make it very difficult to develop realistic simulation models of construction processes and represent their dynamic behavior and the interaction with project resources. This led to lack of special simulation tools for construction project planning. The second challenge is the huge amount of project information that has to be integrated into the simulation model and to be maintained throughout the design, planning and construction phases. The preparation of ad-hoc simulation models and setting up different scenarios and verification of simulation results usually takes a long time. Therefore, creating reliable simulation models requires extensive resources with advanced skills. The presented challenges prevent the wide application of simulation techniques to support and improve construction project planning and adopt it as an essential part of the construction planning workflow in practice. The research work in this thesis addresses these challenges by developing an approach and platform for rapid development of simulation models for construction projects. The main objective of this research is to develop a BIM integrated and reference process-based simulation approach to support planning of construction projects and to enable collaboration among all actors involved in the planning and simulation process. The first challenge has been addressed through the development of a construction simulation toolkit and the Reference Process Model (RPM) method for modelling construction processes for production and logistics using Business Process Modelling and Notation (BPMN). The RPM models are easy to understood also by non-experts and they can be transformed automatically into simulation models as ready-to-use modules. They describe the workflow and logic of construction processes and include information about duration, resource requirements and other related information for different construction domains with different levels of details. The use of BPMN has many advantages. It enables the understanding of how simulation models work by project teams, including those who are not experts in simulation. In this approach, the modelling of Reference Process Models is totally separated from the simulation core components. In this way, the simulation toolkit is generic and extendable for various construction types such as buildings, bridges and different construction domains such as structural work and indoor operations. The presented approach supports continuous adoption of simulation models throughout the whole project life cycle. The simulation model which supports project planning in the early design phase can be continuously extended with more detailed RPMs and updated information through the planning and construction phases. The second challenge has been addressed by supporting direct integration of Building Information Modelling (BIM) method with the simulation modelling based on the Industry Foundation Classes IFC (ISO 16739) standard, which is the most common and only ISO standard used for exchanging BIM models. As the BIM models contain the biggest part of the input information of simulation models and they can be used for effective visualization of results in the form of animated 4D BIM models. The integration between BIM and simulation enables fast and semi-automatic filtering, extraction and transformation of the necessary information from BIM models for both design and construction site models. In addition, a special top-down semi-automatic detailing method was developed in order to accelerate the process of preparing detailed project schedules, which are essential input data for the simulation models and hence reduce the time and efforts needed to create simulation models. The developed approach has been implemented as a software prototype in the form of a modular Construction Simulation Toolkit (CST) based on the Discrete Event Simulation (DES) method and an online collaboration web portal 'ProSIM' for managing simulation models. The collaboration portal helps to overcome the problem of huge information and make simulation models accessible for non simulation experts. Simulation models created by CST toolkit facilitate the evaluation of design alternatives and construction methods with minimal changes in the simulation model. Both production and logistic operations can be simulated at the same time in a unified environment and take into account the shared resources and the interaction between production and logistic activities. It also takes into account the dynamic nature of construction projects and hence the changes in the construction site layout during the construction phase. The verification and validation of the proposed approach is carried out through various academic and real construction project case studies.:1 Introduction: motivation, problem statement and objectives 1.1 Motivation 1.2 Problem statement 1.3 Objectives 1.4 Thesis Structure 2 Definitions, Related work and background information 2.1 Simulation definition 2.2 Simulation system definition 2.3 Discrete Event Simulation 2.5 How simulation works 2.6 Workflow of simulation study 2.7 Related work 2.8 Traditional construction planning methods 2.8.1 Gantt chart 2.8.2 Critical Path Method (CPM) 2.8.3 Linear scheduling method/Location-based scheduling 2.9 Business Process Model and Notation 2.10Workflow patterns 2.10.1 Supported Control Flow Patterns 3 Reference Process-based Simulation Approach 3.1 Reference Process-based simulation approach 3.2 Reference Process Models 3.3 Reference process model for single task 3.4 Reference process models for complex activities 3.5 Process Pool 3.6 Top-down automatic detailing of project schedules 3.7 Simulation model formalism 3.8 Fundamental design concepts and application scope 4 Data Integration between simulation and construction Project models 4.1 Data integration between BIM models and simulation models 4.1.1 Transformation of IFC models to Graph models 4.1.2 Checking BIM model quality 4.1.3 Filtering of BIM models 4.1.4 Semantic enrichment of BIM models 4.1.5 Reference process models and BIM models 4.2 Reference Process Models and resources models 4.3 Process models and productivity factors 5 Construction Simulation Toolkit 5.1 System architecture and implementation 5.2 Basic steps to create a CST simulation model 5.3 CST Simulation components 5.3.1 Input components 5.3.2 Process components 5.3.3 Output components 5.3.4 Logistic components 5.3.5 Collaboration platform ProSIM 6 Case Studies and Validation 6.1 Verification and Validation of Simulation Models 6.2 Verification and validation techniques for simulation models 6.3 Case study 1: generic planning model 6.4 Case study 2: high rise building 6.4.1 Scenario I: effect of changing number of workers on structural work duration 6.4.2 Scenario II: simulation of structural work on operation level 6.4.3 Scenario III: automatic generation of detailed project schedule 6.5 Case study 3: airport terminal building 6.5.1 Multimodel Container 6.5.2 Scenario I: automatic generation of detailed project schedule 6.5.3 Scenario II: Find the minimal project duration 6.5.4 Scenario III: construction work for a single floor 7 Conclusions and Future Research 7.1 Conclusions 7.2 Outlook of the possible future research topics 7.2.1 Integration with real data collecting 7.2.2 Multi-criteria optimisation 7.2.3 Extend the control-flow and resource patterns 7.2.4 Consideration of further structure domains 7.2.5 Considering of space allocation and space conflicts 8 Appendix - Scripts 9 Appendix B - Reference Process Models 9.1 Reference Process Models for structural work 9.1.1 Wall 9.1.2 Roof 9.1.3 Foundations 9.1.4 Concrete work 9.1.5 Top-Down RPMs for structural work in a work section 10 Appendix E 10.1 Basic elements of simulation models in Plant Simulation 10.2 Material Flow Objects 11 Reference