A method and framework to evaluate system architecture candidates on reliability criteria

Philips Lighting is moving from a lighting component business towards lighting solutions business in professional environments, offering lighting solutions for energy saving, productivity and effect creation. In these solutions (consisting of light sources, sensors and control devices) networked based systems are essential and software makes it possible to add intelligence into the system. Reliability aspects at system level are getting more important and architectural analysis is done during brainstorm sessions to evaluate possible system architecture candidates on reliability criteria. It is crucial that the reliability of the architectures is evaluated more formally, for example based on a model of each of the architectural candidates. This report describes the design, the implementation, and the experimentation with such a method that predicts the reliability and other non-functional criteria of the architecture candidates. Lighting entities, their attributes, behavior, and relationships are the core of evaluating a system on reliability criteria. This approach relies heavily on modeling principle. The results of the project show whether such an approach can been used to determine and evaluate an architecture candidate, and give input on how architecture evaluation can be done in the future

MEAN Web Application Development with Agile Kanban

I spent one year developing a project management web application in order to gain a better understanding of the software engineering process. The software was built on a technology stack of MongoDB, ExpressJS, AngularJS, and Node.js which is more commonly referred to as the MEAN stack. The experience has exposed me to a new set of tools, software practices, and engineering principles that have left me with a deeper understanding of what it means to be a software engineer and the incredible amount of time and work that is involved in designing and implementing a full-scale software application

Big Data – A State-of-the-Art

The term Big Data has an increased and tautological occurrence in scientific publications. It is of interest how and whether the data provisioning is able to support enterprises in the handling and value creation of this emerging issue. Considering the amount of growing publication and the fuzzy nature of this term, an overview is requested to avoid duplications to gain relevant findings and to identify potential research gaps. To address this issue, a general literature review is accomplished, which extrapolates and clusters discussed research fields and potential gaps. It becomes apparent that a huge part of the research is technical driven. Moreover, no identified paper addresses the research area of functional data provisioning. This initiates further investigations to discuss whether Big Data itself negate such intention or research has missed it and improvements regarding Big Data are possible