Architectural degeneration is an ever-present threat to software systems with no exception based on the domain or tools used. This thesis focus on the architectural degeneration in systems written in multi-paradigm run-time evaluated languages like Python. The focus on Python in this kind of investigation is to our knowledge the first of its kind; thus the thesis investigates if the methods for measuring architectural degeneration also applies to run-time evaluated languages like Python as believed by other researchers. Whom in contrast to our research have only researched this phenomenon in systems written in compiled languages such as Java, C, C++ and C#. In our research a tool PySmell has been developed to recover architectures and identify the presence of architectural smells in a system. PySmell has been used and evaluated on three different projects Django, Flask and PySmell itself. The results of PySmell are promising and of great interest but in need of further investigating and fine-tuning to reach the same level as the architectural recovery tools available for compiled languages. The thesis presents the first step into this new area of detecting architectural degeneration in interpreted languages, revealing issues such as that of extracting dependencies and how that may affect the architectural smell detection.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:liu-159652 |
| Date | January 2019 |
| Creators | Mo Eriksson, Anton, Dunström, Hampus |
| Publisher | Linköpings universitet, Institutionen för datavetenskap, Linköpings universitet, Institutionen för datavetenskap |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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