We present here an exploratory and investigatory study of the requirements, design, and implementation of two opensource software systems: the Distributed Modular Audio Recognition Framework (DMARF), and the General Intensional Programming System (GIPSY). The inception, development, and evolution of the two systems have overlapped and in terms of the involved developers, as well as in their applications. DMARF is a platform independent collection of algorithms for pattern recognition, identification and signal processing in audio and natural language text samples, become a rich platform for the research community in particular to use, test, and compare various algorithms in the broad field of pattern recognition and machine learning. Intended as a platform for intensional programming, GIPSY's inception was intended to push the field of intensional programming further, overcoming limitations in the available tools two decades ago. In this study, we present background research into the two systems and elaborate on their motivations and the requirements that drove and shaped their design and implementation. We subsequently elaborate in more depth about various aspects their architectural design, including the elucidation of some use cases, domain models, and the overall class diagram of the major components. Moreover, we investigated existing design patterns in both systems and provided a detailed view of the involved components in such patterns. Furthermore, we delve deeper into the guts of both systems, identifying code smells and suggesting possible refactorings. Patchsets of implementations of selected refactorings have been collected into patchsets and could be committed into future releases of the two systems, pending a review and approval of the developers and maintainers of DMARF and GIPSY.