An Empirical Study of Cohesion and Coupling: Balancing Optimisation and Disruption

Search based software engineering has been extensively applied to the problem of finding improved modular structures that maximise cohesion and minimise coupling. However, there has, hitherto, been no longitudinal study of developers’ implementations, over a series of sequential releases. Moreover, results validating whether developers respect the fitness functions are scarce, and the potentially disruptive effect of search-based remodularisation is usually overlooked. We present an empirical study of 233 sequential releases of 10 different systems; the largest empirical study reported in the literature so far, and the first longitudinal study. Our results provide evidence that developers do, indeed, respect the fitness functions used to optimise cohesion/coupling (they are statistically significantly better than arbitrary choices with p << 0.01), yet they also leave considerable room for further improvement (cohesion/coupling can be improved by 25% on average). However, we also report that optimising the structure is highly disruptive (on average more than 57% of the structure must change), while our results reveal that developers tend to avoid such disruption. Therefore, we introduce and evaluate a multi-objective evolutionary approach that minimises disruption while maximising cohesion/coupling improvement. This allows developers to balance reticence to disrupt existing modular structure, against their competing need to improve cohesion and coupling. The multi-objective approach is able to find modular structures that improve the cohesion of developers’ implementations by 22.52%, while causing an acceptably low level of disruption (within that already tolerated by developers)

Different approaches to community detection

A precise definition of what constitutes a community in networks has remained elusive. Consequently, network scientists have compared community detection algorithms on benchmark networks with a particular form of community structure and classified them based on the mathematical techniques they employ. However, this comparison can be misleading because apparent similarities in their mathematical machinery can disguise different reasons for why we would want to employ community detection in the first place. Here we provide a focused review of these different motivations that underpin community detection. This problem-driven classification is useful in applied network science, where it is important to select an appropriate algorithm for the given purpose. Moreover, highlighting the different approaches to community detection also delineates the many lines of research and points out open directions and avenues for future research.Comment: 14 pages, 2 figures. Written as a chapter for forthcoming Advances in network clustering and blockmodeling, and based on an extended version of The many facets of community detection in complex networks, Appl. Netw. Sci. 2: 4 (2017) by the same author

Adopting Product Modularity in House Building to Support Mass Customisation

Product modularity is a concept that can contribute to the improvement of product quality and production efficiency in house-building. However, there is a lack of consensus in the literature on the concepts that define product modularity. Furthermore, little attention has been given to the differences between building construction and manufacturing, for which product modularity was originally developed. This research aims to address that gap by adapting the conceptualization of product modularity so that it can effectively be used in the house-building industry. The methodological approach adopted in this study was Design Science Research, and two empirical studies were carried out on construction companies based in Brazil and in the U.K. Those studies are used to illustrate the applicability and utility of the proposed concepts and tools. Research findings indicate that the adoption of product modularity concepts results in benefits to both traditional construction technologies and prefabricated building systems

Model granularity and related concepts

Models are integral to engineering design and basis for many decisions. Therefore, it is necessary to comprehend how a model’s properties might influence its behaviour. Model granularity is an important property but has so far only received limited attention. The terminology used to describe granularity and related phenomena varies and pertinent concepts are distributed across communities. This article positions granularity in the theoretical background of models, collects formal definitions for relevant terms from a range of communities and discusses the implications for engineering design

The modular structure of an ontology: Atomic decomposition

Extracting a subset of a given ontology that captures all the ontology’s knowledge about a specified set of terms is a well-understood task. This task can be based, for instance, on locality-based modules. However, a single module does not allow us to understand neither topicality, connectedness, structure, or superfluous parts of an ontology, nor agreement between actual and intended modeling. The strong logical properties of locality-based modules suggest that the family of all such modules of an ontology can support comprehension of the ontology as a whole. However, extracting that family is not feasible, since the number of localitybased modules of an ontology can be exponential w.r.t. its size. In this paper we report on a new approach that enables us to efficiently extract a polynomial representation of the family of all locality-based modules of an ontology. We also describe the fundamental algorithm to pursue this task, and report on experiments carried out and results obtained.

Developing modular product family using GeMoCURE within an SME

Companies adopt the strategy of producing variety of products to be competitive and responsive to market. Product variation is becoming an important factor in companies' ability to accurately meet customer requirements. Ever increasing consumer options mean that customers have more choices than ever before which put commercial pressures on companies to continue to diversify. This can be a particular problem within Small to Medium Enterprises (SMEs) who do not always have the level of resources to meet these requirements. As such, methods are required that provide means for companies to be able to produce a wide range of products at the lowest cost and shortest time. This paper details a new modular product design methodology that provides a focus on developing modular product families. The methodology's function is described and a case study detailed of how it was used within an SME to define the company's product portfolio and create a new Generic Product Function Structure from which a new family of product variants can be developed. The methodology lends itself to modular re-use which has the potential to support rapid development and configuration of product variants

Modular System for Shelves and Coasts (MOSSCO v1.0) - a flexible and multi-component framework for coupled coastal ocean ecosystem modelling

Shelf and coastal sea processes extend from the atmosphere through the water column and into the sea bed. These processes are driven by physical, chemical, and biological interactions at local scales, and they are influenced by transport and cross strong spatial gradients. The linkages between domains and many different processes are not adequately described in current model systems. Their limited integration level in part reflects lacking modularity and flexibility; this shortcoming hinders the exchange of data and model components and has historically imposed supremacy of specific physical driver models. We here present the Modular System for Shelves and Coasts (MOSSCO, http://www.mossco.de), a novel domain and process coupling system tailored---but not limited--- to the coupling challenges of and applications in the coastal ocean. MOSSCO builds on the existing coupling technology Earth System Modeling Framework and on the Framework for Aquatic Biogeochemical Models, thereby creating a unique level of modularity in both domain and process coupling; the new framework adds rich metadata, flexible scheduling, configurations that allow several tens of models to be coupled, and tested setups for coastal coupled applications. That way, MOSSCO addresses the technology needs of a growing marine coastal Earth System community that encompasses very different disciplines, numerical tools, and research questions.Comment: 30 pages, 6 figures, submitted to Geoscientific Model Development Discussion

Strategic perspectives on modularity

In this paper we argue that the debate on modularity has come to a point where a consensus is slowly emerging. However, we also contend that this consensus is clearly technology driven. In particular, no room is left for firm strategies. Typically, technology is considered as an exogenous variable to which firms have no choices but to adapt. Taking a slightly different perspective, our main objective is to offer a conceptual framework enabling to shed light on the role of corporate strategies in the process of modularization. From interviews with academic design engineers, we show that firms often consider product architecture as a critical variable to fit their strategic requirements. Based on design sciences, we build an original approach to product modularity. This approach, which leaves an important space for firms' strategic choices, proves also to seize a large part of the industrial reality of modularity. Our framework, which is a first step towards the consideration of strategies within the framework of modularity, gives an account for the diversity of industrial logics related to product modularization.product modularity ; corporate strategy ; technological determinism