Applications 2023-02-15 - 2023-08-13
The purpose of the course is to show how security practices can be integrated into different software development processes (traditional, agile, continuous) and how to assess the maturity of the integration. The student will learn about different models, with a focus on a specific one touching upon security practices during software design, implementation, verification, and operation. In order to take different backgrounds and previous knowledge of the students into account, the course also covers the necessary background information on classical and security-oriented software development process models. The course enables students to assess the maturity of secure software development processes based on a model.
This course provides an understanding of automating software testing using program analysis with the goal of intelligently and algorithmically creating tests. The course covers search-based test generation, combinatorial and random testing while highlighting the challenges associated with the use of automatic test generation.
This course deals with model-based testing, a class of technologies shown to be effective and efficient in assessing the quality and correctness of large software systems. Throughout the course the participants will learn how to design and use model-based testing tools, how to create realistic models and how to use these models to automate the testing process in their organisation.
The rapid development of digital technologies and advances in communications have led to gigantic amounts of data with complex structures called ‘Big data’ being produced every day at exponential growth. The aim of this course is to give the student insights in fundamental concepts of machine learning with big data as well as recent research trends in the domain. The student will learn about problems and industrial challenges through domain-based case studies. Furthermore, the student will learn to use tools to develop systems using machine-learning algorithms in big data.
The aim of this course is to provide participants with the principles behind model-driven development of software systems and the application of such a methodology in practice. Modelling is an effective solution to reduce problem complexity and, as a consequence, to enhance time-to-market and properties of the final product.
Modern web applications can often be described in terms of cooperation and sharing, both on the level of the users of the application and on the level of the application and the service providers. This course covers the most prevalent security challenges of web applications, from a theoretical and practical perspective.
The course will give insights in fundamental concepts of machine learning and actionable forecasting using predictive analytics. It will cover the key concepts to extract useful information and knowledge from big data sets for analytical modeling