Att utveckla applikationer med mikrotjänstarkitektur har idag blivit ett trendande tillvägagångssätt för att skapa tjänster som är anpassade för att köras i molnet med fördelar som mindre underhållsarbete och lättare skalbarhet. Mikrotjänster kännetecknas som löstkopplade och oberoende tjänster som kommunicerar genom att exponera ett API. För många populära programmeringsspråk, som till exempel Java, finns det flera ramverk att använda för att underlätta utvecklandet av mikrotjänster. Företaget Redpill Linpro i Karlstad, som är uppdragsgivare för den här studien, använder sig idag av Javaramverket Quarkus vid utvecklandet av mikrotjänster. De är dock intresserade av att veta hur mikrotjänster som utvecklats i Quarkus jämför sig prestandamässigt mot mikrotjänster som utvecklats i ett annat programmeringsspråk. Redpill Linpro har märkt att intresset för programmeringsspråket Go har ökat på sistone. I Gos officiella dokumentation rekommenderas ramverket Gin för att få bättre prestanda när det kommer till att utveckla tjänster som exponerar ett API. Redpill Linpro har tilldelat författaren av denna uppsats ett uppdrag att utveckla mikrotjänster med hjälp av ramverken Quarkus och Gin för att studera skillnader i prestanda samt beskriva tillvägagångssättet för hur utvecklingen av mikrotjänsterna gått till. Studien syfte är att identifiera vilken av mikrotjänsterna utvecklade i Gin eller Quarkus som presterar snabbast beträffande kompileringstid och uppstartstid, skillnader i filstorlek och skillnader i responstid vid HTTP-anropen GET och POST med och utan koppling till databas. Även vilken mikrotjänst som använder minst CPU-kraft och RAM-minne. Studiens resultat visar för- och nackdelar med båda ramverken men att mikrotjänsterna skapade med Gin presterade bäst i flest antalet parametrar som mättes i den här studien.

Throughout history, humans have proven to develop and improve their quality of life constantly. Incorporating mechanical principles into otherwise manual labor was one such aspect. Today, introducing mechanization to the industry and steam power is regarded as the first industrial revolution. Since then, a second and a third have followed, introducing concepts such as electricity, automation, computers, and computerization. Finally, in 2011 the fourth industrial revolution was introduced as Industry 4.0 by a project started in Germany, which considers digitalization. Industry 4.0 uses concepts such as Cyber-Physical Systems (CPS), the Internet of Things (IoT), and cloud computing. The goal of these concepts is to be able to further the capabilities of automation in the industry, creating smart factories. A problem experienced today when making changes to the production line is that an immense amount of hard coding is required for the Programmable Logic Controller (PLC) controlling the system as well as for the system controlling the factory. The Eclipse Arrowhead Framework addresses these issues by applying a particular set of parameters to all systems within the IT infrastructure. The Arrowheadframework offers parameters such as orchestrator, authorization, and a service registry to each system incorporated within the framework. By applying this, the System of Systems (SoS) and the parameters provided by the Arrowhead framework create a local cloud. In doing so, each system within a factory belongs to its local cloud, building a factory made of a cluster of local clouds. By applying the ideas of Industry 4.0, a proof of concept is created, showing that today’s industry would benefit from using the concepts stated above with digital twins. The thesis explores and proves that, with the help of digital twins, today’s industry can cut down on manufacturing process development. In addition, it reduces the time it takes to apply changes to the production line by enabling machine learning to facilitate human interaction. A model factory created by fischertechnik is used, together with a PLC, as the physical twin in this master thesis. In addition, using Siemens Computer-Aided Design (CAD) software NX, a digital twin is created; this digital twin will communicate with the physical twin to simulate the behavior of the physical twin in real-time. A server has been created and is acting as a hub of communication for both of the twins. The use of the digital twin to communicate with the physical twin will enable tremendous advances in automation regarding industry 4.0.

This thesis evaluates various ways of displaying tabular data on mobile devices using different responsive table solutions. It also presents a tool to help web developers and designers in the process of choosing and implementing a suitable table approach. The proposed solution for this thesis is a web system called The Visualizing Wizard that allows the user to answer some questions about the intended table and then get a recommended responsive table solution generated based on the answers. The system uses a rule-based approach via Prolog to match the answers to a set of rules and provide an appropriate result. In order to determine which table solutions are more appropriate to use for which type of data a statistical analysis and user tests were performed. The statistical analysis contains an investigation to identify the most common table approaches and data types used on various websites. The result indicates that solutions such as "squish", "collapse by rows", "click" and "scroll" are most common. The most common table categories are product comparison, product offerings, sports and stock market/statistics. This information was used to implement and establish user tests to collect feedback and opinions. The data and statistics gathered from the user tests were mapped into sets of rules to answer the question of which responsive table solution is more appropriate to use for which type of data. This serves as the foundation for The Visualizing Wizard.