Mirroring or misting: On the role of product architecture, product complexity, and the rate of product component change

This paper contributes to the literature on the within-firm and across-firm mirroring hypothesis – the assumed architectural mapping between firms’ strategic choices of product architecture and firm architecture, and between firms’ architectural choices and the industry structures that emerge. Empirical evidence is both limited and mixed and there is evidently a need for a more nuanced theory that embeds not only whether the mirroring hypothesis holds, but under what product architecture and component-level conditions it may or may not hold. We invoke an industrial economics perspective to develop a stylised product architecture typology and hypothesise how the combined effects of product architecture type, product complexity and the rate of product component change may be associated with phases of mirroring or misting. Our framework helps to reconcile much existing mixed evidence and provides the foundation for further empirical research

Observational models of requirements evolution

Requirements Evolution is one of the main issues that affect development activities as well as system features (e.g., system dependability). Although researchers and practitioners recognise the importance of requirements evolution, research results and experience are still patchy. This points out a lack of methodologies that address requirements evolution. This thesis investigates the current understanding of requirements evolution and explores new directions in requirements evolution research. The empirical analysis of industrial case studies highlights software requirements evolution as an important issue. Unfortunately, traditional requirements engineering methodologies provide limited support to capture requirements evolution. Heterogeneous engineering provides a comprehensive account of system requirements. Heterogeneous engineering stresses a holistic viewpoint that allows us to understand the underlying mechanisms of evolution of socio-technical systems. Requirements, as mappings between socio-technical solutions and problems, represent an account of the history of socio-technical issues arising and being solved within industrial settings. The formal extension of a heterogeneous account of requirements provides a framework to model and capture requirements evolution. The application of the proposed framework provides further evidence that it is possible to capture and model evolutionary information about requirements. The discussion of scenarios of use stresses practical necessities for methodologies addressing requirements evolution. Finally, the identification of a broad spectrum of evolutions in socio-technical systems points out strong contingencies between system evolution and dependability. This thesis argues that the better our understanding of socio-techn..

A productive response to legacy system petrification

Requirements change. The requirements of a legacy information system change, often in unanticipated ways, and at a more rapid pace than the rate at which the information system itself can be evolved to support them. The capabilities of a legacy system progressively fall further and further behind their evolving requirements, in a degrading process termed petrification. As systems petrify, they deliver diminishing business value, hamper business effectiveness, and drain organisational resources. To address legacy systems, the first challenge is to understand how to shed their resistance to tracking requirements change. The second challenge is to ensure that a newly adaptable system never again petrifies into a change resistant legacy system. This thesis addresses both challenges. The approach outlined herein is underpinned by an agile migration process - termed Productive Migration - that homes in upon the specific causes of petrification within each particular legacy system and provides guidance upon how to address them. That guidance comes in part from a personalised catalogue of petrifying patterns, which capture recurring themes underlying petrification. These steer us to the problems actually present in a given legacy system, and lead us to suitable antidote productive patterns via which we can deal with those problems one by one. To prevent newly adaptable systems from again degrading into legacy systems, we appeal to a follow-on process, termed Productive Evolution, which embraces and keeps pace with change rather than resisting and falling behind it. Productive Evolution teaches us to be vigilant against signs of system petrification and helps us to nip them in the bud. The aim is to nurture systems that remain supportive of the business, that are adaptable in step with ongoing requirements change, and that continue to retain their value as significant business assets

Technological roadmap on AI planning and scheduling

At the beginning of the new century, Information Technologies had become basic and indispensable constituents of the production and preparation processes for all kinds of goods and services and with that are largely influencing both the working and private life of nearly every citizen. This development will continue and even further grow with the continually increasing use of the Internet in production, business, science, education, and everyday societal and private undertaking. Recent years have shown, however, that a dramatic enhancement of software capabilities is required, when aiming to continuously provide advanced and competitive products and services in all these fast developing sectors. It includes the development of intelligent systems – systems that are more autonomous, flexible, and robust than today’s conventional software. Intelligent Planning and Scheduling is a key enabling technology for intelligent systems. It has been developed and matured over the last three decades and has successfully been employed for a variety of applications in commerce, industry, education, medicine, public transport, defense, and government. This document reviews the state-of-the-art in key application and technical areas of Intelligent Planning and Scheduling. It identifies the most important research, development, and technology transfer efforts required in the coming 3 to 10 years and shows the way forward to meet these challenges in the short-, medium- and longer-term future. The roadmap has been developed under the regime of PLANET – the European Network of Excellence in AI Planning. This network, established by the European Commission in 1998, is the co-ordinating framework for research, development, and technology transfer in the field of Intelligent Planning and Scheduling in Europe. A large number of people have contributed to this document including the members of PLANET non- European international experts, and a number of independent expert peer reviewers. All of them are acknowledged in a separate section of this document. Intelligent Planning and Scheduling is a far-reaching technology. Accepting the challenges and progressing along the directions pointed out in this roadmap will enable a new generation of intelligent application systems in a wide variety of industrial, commercial, public, and private sectors

CAESAR8: an agile enterprise architecture approach to managing information security risks in business change projects

Implementing an Enterprise Architecture (EA) should enable organizations to increase the accuracy of information security risk assessments. Studies show that EAs provide an holistic perspective that improves information security risk management (ISRM). However, many organizations have been unable or unwilling to fully implement EA frameworks. The requirements for implementation of an EA can be unclear, the full benefits of many commercial frameworks is uncertain and the overheads of creating and maintaining EA artifacts considered unacceptable, especially for organizations following agile business change programs or having limited resource. Following the Design Science Research methodology, this thesis describes a comprehensive and multidisciplinary approach to design a new model that can be used for the dynamic and holistic reviews of information security risks in business change projects. The model incorporates five novel design principles that are independent of any existing EA framework, security standard or maturity model. This new model is called CAESAR8 - Continuous Agile Enterprise Security Architecture Review in 8 domains. CAESAR8 incorporates key ISRM success factors that have been determined from root cause analysis of information security failures. Combining systems thinking with agile values and lean concepts into the design has ensured that the impact of a change is considered holistically and continuously, prioritizing the EA process over the creation of EA artifacts. Inclusion of human behavioral-science has allowed the capture of diverse and often tacit knowledge held by different stakeholders impacted by a business change, whilst avoiding the dangers of groupthink. CAESAR8’s presentation of the results provides an impactive and easy-to-interpret metric that is designed to be shared with senior business executives to improve intervention decisions. This thesis demonstrates how CAESAR8 has been developed into a working prototype and presents case studies that describe the model in operation. A diverse group of experts were given access to a working IT prototype for a hands-on evaluation of CAESAR8. An analysis of their findings confirms the model’s novel scientific contribution to ISRM

Deep Learning, Shallow Dips: Transit light curves have never been so trendy

At the crossroad between photometry and time-domain astronomy, light curves are invaluable data objects to study distant events and sources of light even when they can not be spatially resolved. In particular, the field of exoplanet sciences has tremendously benefited from acquired stellar light curves to detect and characterise a majority of the outer worlds that we know today. Yet, their analysis is challenged by the astrophysical and instrumental noise often diluting the signals of interest. For instance, the detection of shallow dips caused by transiting exoplanets in stellar light curves typically require a precision of the order of 1 ppm to 100 ppm in units of stellar flux, and their very study directly depends upon our capacity to correct for instrumental and stellar trends. The increasing number of light curves acquired from space and ground-based telescopes—of the order of billions—opens up the possibility for global, efficient, automated processing algorithms to replace individual, parametric and hard-coded ones. Luckily, the field of deep learning is also progressing fast, revolutionising time series problems and applications. This reinforces the incentive to develop data-driven approaches hand-in-hand with existing scientific models and expertise. With the study of exoplanetary transits in focus, I developed automated approaches to learn and correct for the time-correlated noise in and across light curves. In particular, I present (i) a deep recurrent model trained via a forecasting objective to detrend individual transit light curves (e.g. from the Spitzer space telescope); (ii) the power of a Transformer-based model leveraging whole datasets of light curves (e.g. from large transit surveys) to learn the trend via a masked objective; (iii) a hybrid and flexible framework to combine neural networks with transit physics

HERITAGE 2022. International Conference on Vernacular Heritage: Culture, People and Sustainability

Vernacular architecture, tangible and intangible heritage of great importance to European and global culture, represents the response of a society culturally linked to its territory, in terms of climate and landscape. Its construction features are born from the practical experience of the inhabitants, making use of local materials, taking into consideration geographical conditions and cultural, social and constructive traditions, based on the conditions of the surrounding nature and habitat. Above all, it plays an essential role in contemporary society as it is able to teach us important principles and lessons for a respectful sustainable architecture. Vernacular Heritage: Culture, People and Sustainability will be a valuable source of information for academics and professionals in the fields of Environmental Science, Civil Engineering, Construction and Building Engineering and ArchitectureMileto, C.; Vegas López-Manzanares, F.; Cristini, V.; García Soriano, L. (2022). HERITAGE 2022. International Conference on Vernacular Heritage: Culture, People and Sustainability. Editorial Universitat Politècnica de València. https://doi.org/10.4995/HERITAGE2022.2022.15942EDITORIA

A Systematic Performance Study of Object Database Management Systems

Many previous performance benchmarks for Object Database Management Systems (ODBMSs) have typically used arbitrary sets of tests based on what their designers felt were the characteristics of Engineering applications. Increasingly, however, ODBMSs are being used in non-engineering domains, such as Financial Trading, Clinical Healthcare, Telecommunications Network Management, etc. Part of the reason for this is that the technology has matured over the past few years and has become a less risky choice for organisations looking for better w'ays to manage complex data. However, the development of suitable application- or industry-specific benchmarks, based on actual performance studies, has not paralleled this growth. The research reported here approaches performance evaluation of ODBMSs pragmatically. It uses a combination of case studies and benchmark experiments to investigate the performance characteristics of ODBMSs for particular applications, following the successful use of this approach by Youssef [Youss93] for studying the performance of On- Line Transaction Processing (OLTP) applications for Relational Database Management Systems (RDBMSs). Six case studies at five organisations show’ that organisations consider a wide range of factors when undertaking their own performance studies or benchmarks. Furthermore, none of the studied organisations considered using any public benchmarks. Six current and derived benchmarks also highlight statistically significant performance differences between three major commercial products: Objectivity/DB, ObjectStore and UniSQL. These benchmarks indicate the suitability of the products tested for particular application domains. The research could not find any evidence at this time to support the concept of a generic or canonical performance workload for ODBMSs. This is demonstrated by the case studies and supported by the benchmark experiments. However, the research shows that performance benchmarks serve a very useful role in ODBMS evaluations and can help identify architectural and quality problems with products that would not otherwise be observed until significant application or system development was already in progress