The study of large-scale decentralised systems composed of numerous interacting agents that self-organise to perform a common task is receiving growing attention in several application domains. However, real world implementations are limited by a lack of well-established design methodologies that provide performance guarantees. Engineering such systems is a challenging task because of the difficulties to obtain the micro-macro link: a correspondence between the microscopic description of the individual agent behaviour and the macroscopic models that describe the system's dynamics at the global level. In this thesis, we propose an engineering methodology for designing decentralised systems, based on the concept of design patterns. A design pattern provides a general solution to a specific class of problems which are relevant in several application domains. The main component of the solution consists of a multi-level description of the collective process, from macro to micro models, accompanied by rules for converting the model parameters between description levels. In other words, the design pattern provides a formal description of the micro-macro link for a process that tackles a specific class of problems. Additionally, a design pattern provides a set of case studies to illustrate possible implementation alternatives both for simple or particularly challenging scenarios. We present a design pattern for the best-of-n, decentralised decision problem that is derived from a model of nest-site selection in honeybees. We present two case studies to showcase the design pattern usage in (i) a multiagent system interacting through a fully-connected network, and (ii) a swarm of particles moving on a bidimensional plane. / Doctorat en Sciences de l'ingénieur et technologie / info:eu-repo/semantics/nonPublished

Ontologies are formal knowledge models that describe concepts and relationships and enable data integration, information search, and reasoning. Ontology Design Patterns (ODPs) are reusable solutions intended to simplify ontology development and support the use of semantic technologies by ontology engineers. ODPs document and package good modelling practices for reuse, ideally enabling inexperienced ontologists to construct high-quality ontologies. Although ODPs are already used for development, there are still remaining challenges that have not been addressed in the literature. These research gaps include a lack of knowledge about (1) which ODP features are important for ontology engineering, (2) less experienced developers' preferences and barriers for employing ODP tooling, and (3) the suitability of the eXtreme Design (XD) ODP usage methodology in non-academic contexts. This dissertation aims to close these gaps by combining quantitative and qualitative methods, primarily based on five ontology engineering projects involving inexperienced ontologists. A series of ontology engineering workshops and surveys provided data about developer preferences regarding ODP features, ODP usage methodology, and ODP tooling needs. Other data sources are ontologies and ODPs published on the web, which have been studied in detail. To evaluate tooling improvements, experimental approaches provide data from comparison of new tools and techniques against established alternatives. The analysis of the gathered data resulted in a set of measurable quality indicators that cover aspects of ODP documentation, formal representation or axiomatisation, and usage by ontologists. These indicators highlight quality trade-offs: for instance, between ODP Learnability and Reusability, or between Functional Suitability and Performance Efficiency. Furthermore, the results demonstrate a need for ODP tools that support three novel property specialisation strategies, and highlight the preference of inexperienced developers for template-based ODP instantiation---neither of which are supported in prior tooling. The studies also resulted in improvements to ODP search engines based on ODP-specific attributes. Finally, the analysis shows that XD should include guidance for the developer roles and responsibilities in ontology engineering projects, suggestions on how to reuse existing ontology resources, and approaches for adapting XD to project-specific contexts.

Ontologies are formal knowledge models that describe concepts and relationships and enable data integration, information search, and reasoning. Ontology Design Patterns (ODPs) are reusable solutions intended to simplify ontology development and support the use of semantic technologies by ontology engineers. ODPs document and package good modelling practices for reuse, ideally enabling inexperienced ontologists to construct high-quality ontologies. Although ODPs are already used for development, there are still remaining challenges that have not been addressed in the literature. These research gaps include a lack of knowledge about (1) which ODP features are important for ontology engineering, (2) less experienced developers' preferences and barriers for employing ODP tooling, and (3) the suitability of the eXtreme Design (XD) ODP usage methodology in non-academic contexts. This dissertation aims to close these gaps by combining quantitative and qualitative methods, primarily based on five ontology engineering projects involving inexperienced ontologists. A series of ontology engineering workshops and surveys provided data about developer preferences regarding ODP features, ODP usage methodology, and ODP tooling needs. Other data sources are ontologies and ODPs published on the web, which have been studied in detail. To evaluate tooling improvements, experimental approaches provide data from comparison of new tools and techniques against established alternatives. The analysis of the gathered data resulted in a set of measurable quality indicators that cover aspects of ODP documentation, formal representation or axiomatisation, and usage by ontologists. These indicators highlight quality trade-offs: for instance, between ODP Learnability and Reusability, or between Functional Suitability and Performance Efficiency. Furthermore, the results demonstrate a need for ODP tools that support three novel property specialisation strategies, and highlight the preference of inexperienced developers for template-based ODP instantiation---neither of which are supported in prior tooling. The studies also resulted in improvements to ODP search engines based on ODP-specific attributes. Finally, the analysis shows that XD should include guidance for the developer roles and responsibilities in ontology engineering projects, suggestions on how to reuse existing ontology resources, and approaches for adapting XD to project-specific contexts.

TINAG, which stands for This is Not a Game, can be defined as "the concept that there are pervasive games, often ARGs, that are designed to immerse players in such a way that they suspend their disbelief in a fictional narrative and act like the world they have entered is real during their play time" (Pohjola 2004). Many designers and educators want to create games that appear real, but they are unsure of how to accomplish this. Increasing TINAG allows designers to create more realistic games while taking advantage of the many benefits that TINAG experiences offer. The purpose of this research was to identify and validate design patterns that enhance TINAG. As part of this research, design patterns to increase TINAG in ARG and PCS games were identified and presented. After defining the design patterns, workshops were completed to validate the design patterns and their usefulness to designers. We were able to verify that both novice and more experienced designers are able to understand the design patterns and apply them, with a few exceptions. We found that the design patterns were helpful tools, especially when used in group settings. All of the design patterns could be used and applied to a PCS and the designers felt like they would be impactful. This suggests that they are applicable to non ARG contexts, even though they were generated primarily from PCSs. Participants were drawn to design patterns that help create more authenticity and give players tools to succeed because they agreed that TINAG can increase transfer of learning into real context (Balzotti & Hansen, 2019). We imagine these design patterns could be used to help designers of ARGs, educational simulations, or escape rooms, or other experienced that have the goal of feeling real or authentic.

In this study we will investigate the evolution of manipulative and experientially devaluative business practices in the mobile game industry from the perspective of game designers. The focus will be placed on the use of Dark Design Patterns defined in previous research by Zagal et al. (2013), significant changes since their cataloguing in said study, and the emergence of new ones. To do this, we isolate the different Game Modes of Coin Master and use Formal Analysis to break down various systems and interactions. In order to identify Dark Patterns, we use Zagal et al. (2013) study, supplemented by a list of potentially exploitable cognitive biases found in the work of Mathur et al (2019) as our theoretical framework. We discovered that many of the previously defined Dark Patterns can still be found in Coin master, along with hitherto new and undefined ones, chiefly related to company or developer interests as opposed to the players’. Dark Patterns of monetary and temporal nature appeared to have a close connection as they often manifested together, also commonly underpinned by exploitation of cognitive biases. Our findings are indicative of an increased intensity of predation on players, primarily motivated by monetary gain and to the detriment of player experience. / I denna studie undersöker vi utvecklingen av manipulativa och upplevelsemässigt nedvärderande affärsmodeller i mobil-spelsindustrin ur en speldesigners perspektiv. Undersökningens fokus riktas mot användningen och inkluderingen av Mörka Design Mönster, definierade i en tidigare studie av Zagal et al. (2013), förändringar i dessa mönster sedan deras kategorisering i sagd studie, och uppkomsten av tidigare odefinierade mönster. För att genomföra detta isolerar och analyserar vi de olika spellägena funna i spelet Coin Master med hjälp av Formell Analys, och nyttjar i syfte av identifiering Zagal et al. (2013) studie, samt som komplement den lista över kognitiva bias framtagen i en studie utförd av Mathur et al (2019) som teoretisk grundstomme. Vi upptäckte att flera utav de redan definierade mönstren i Zagal et al (2013) forskning består i sin närvaro än idag i Coin Master, beblandade med ett antal nya mönster, i överlag relaterade till företagets eller utvecklarens egna intressen istället för spelarens. Mörka Mönster av monetär och temporal karaktär påträffas ofta i samband med varandra, då i flera fall även med utnyttjande av kognitiva bias. Våra resultat är indikativa av en ökad vikt placerad på målsättningen att föregå värdet av spelupplevelsen i utvecklarens ekonomiska intressen, på spelares bekostnad.

The use of semantic technologies and Semantic Web ontologies in particular have enabled many recent developments in information integration, search engines, and reasoning over formalised knowledge. Ontology Design Patterns have been proposed to be useful in simplifying the development of Semantic Web ontologies by codifying and reusing modelling best practices. This thesis investigates the quality of Ontology Design Patterns. The main contribution of the thesis is a theoretically grounded and partially empirically evaluated quality model for such patterns including a set of quality characteristics, indicators, measurement methods and recommendations. The quality model is based on established theory on information system quality, conceptual model quality, and ontology evaluation. It has been tested in a case study setting and in two experiments. The main findings of this thesis are that the quality of Ontology Design Patterns can be identified, formalised and measured, and furthermore, that these qualities interact in such a way that ontology engineers using patterns need to make tradeoffs regarding which qualities they wish to prioritise. The developed model may aid them in making these choices. This work has been supported by Jönköing University.

Smart devices (or things) in the realm of IoT (Internet of Things) talk to each other and transfer data over the Internet.IoT vendors provide APIs for their clients to send data to the gateways and application servers. However, there is a lack of guidelines on how a vendor would design its API and resource URIs (Uniform Resource Identifiers). A generic design solution –design patterns– would make the API design and development easier for the vendors. Design patterns are reusable solutions to recurring problems and provide improved reusability and understandability. Currently, there are no design patterns for URIs of IoT APIs that IoT vendors can use. In this paper, we analyzed more than 1,300 URIs from 13 IoT APIs including IBM Watson and Microsoft Azure, and proposed eight novel design patterns for URIs of IoT APIs. We analyzed one dataset divided into two subsets: (1) analysis set with 70% of all our URIs to define design patterns for URIs of IoT APIs and (2) validation set with the remaining 30% of the URIs to verify the prevalence of the defined design patterns. We could map 84% of our validation set to the defined design patterns, i.e., design patterns are prevalent in the IoT domain.

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<p> Identifying design pattern instances within an existing software system can support understanding and reuse of the system functionality. Moreover, incorporating behavioral features through task scenario into the design pattern recovery would enhance both the scalability of the process and the usefulness of the design pattern instances. In this context, we present a novel method for recovering design pattern instances from the implementation of system behavioral features through a semi-automatic and multi-phase reverse engineering process.</p> <p> The proposed method consists of a feature-oriented dynamic analysis and a two-phase design pattern detection process. The feature-oriented dynamic analysis works on the software system behavioral features' run-time information and produces a mapping between features and their realization at class level. In the two-phase design pattern detection process, we employ an approximate matching and a structural matching to detect the instances of the target design pattern described in our proposed Pattern Description Language (PDL), which is an XML-based design pattern description language. The correspondence between system features and the identified design pattern instances can facilitate the construction of more reusable and configurable software components. Our target application domain is an evolutionary development of software product line which emphasizes on reusing software artifacts to construct a reference architecture for several similar products. We have implemented a prototype toolkit and conducted experimentations on three versions of JHotDraw systems to evaluate our approach.</p> / Thesis / Master of Applied Science (MASc)