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Mining patterns in software - the FreqTals algorithm: maintenance of the python implementation

Spits, Arnaud
(2022)

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Details

Supervisors
Mens, Kim ; Nijssen, Siegfried
Faculty
Ecole polytechnique de Louvain
Degree label
Master [120] : ingénieur civil en informatique, à finalité spécialisée
Abstract
The FREQTALS algorithm, was first developed in 2019 for mining patterns in AST. This study shows that AST well captures the structure of the source code (it is a compiled version of). Patterns found in such data-structure could be analysed to enhanced our knowledge of software programming. This algorithm was first implemented in Java. However, Python was then consider as this programming language is known to be easier to learn and implement. Accordingly, a new version of the algorithm written in Python was derived of the Java version. This thesis shows how this Python implementation has been improved on different aspects. Its readability was enhanced and make the source code easier to understand. This research also bring a new structure to classes which contribute to the maintainability of this new implementation. Additionally, this new version of the FREQTALS algorithm is more efficient and allows convenient use for future researches.