The teaching-learning process is complex in nature, requiring many tasks and skills to achieve success in the construction of knowledge.As per any particular kind of cognitive development, teaching and learning Computer Programming is no different in this regard: tasks must be executed, sometimes repeatedly, and skills must be developed.Despite different approaches and methodologies, exercising what has been studied is proven to be effective in pretty much any teaching-learning process.Many tools have been developed throughout time to aid in the execution of this important task, sometimes approaching the problem from the students' perspective, sometimes from the teachers'.This paper presents Goliath, a semi-automatic generator of Computer Programming exercises, whose functionality is based on Artificial Intelligence (AI) models, a Domain-Specific Language (DSL), and an online application that binds them together.Goliath's goals are directed towards teachers (and indirectly, students) by aiming to lower the burden of repeatedly constructing exercises.This is achieved through the use of templates that allow for automatic variations of an exercise to be created instantly, while relying on a common foundation.Goliath is meant to be a facilitator, raising availability of exercise lists, while avoiding repetition and the common mistakes that accompany their construction.

An ever-growing landscape of programming technologies (tools, languages, libraries and frameworks) has rapidly become the norm in many domains of computer programming-Web Development being the most noticeable example.The concurrent use of many compartmentalised technologies has advantages: it allows for flexibility in implementation, while also improving reusability.On the other hand, this proliferation tends to create convoluted development workflows that must be (painstakingly) planned, managed and maintained.The combination of multiple languages, libraries, frameworks and tools (Ingredients) in a single project effectively forms a Programming Cocktail, that can rapidly become cognitive and financially onerous.Aiming at understanding these complex situations, an ontology was created to provide a formal and structured analysis of these cocktails.It emerged from a survey of technologies that several companies are currently using to develop their systems, and aims to provide support for better understanding, classifying and characterising Programming Cocktails.This paper presents not only the ontology itself, but also the consequent knowledge that was constructed and structured through its development.