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2021 | OriginalPaper | Chapter

Optimized Dependency Weights in Source Code Clustering

Authors : Tobias Olsson, Morgan Ericsson, Anna Wingkvist

Published in: Software Architecture

Publisher: Springer International Publishing

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Abstract

The chapter delves into the optimization of dependency weights in source code clustering, a crucial aspect of software architecture recovery and module mapping. It introduces a genetic algorithm to find optimal weights for various dependency types, such as MethodCall, Inheritance, and File relations, and compares these to intuitive and uniform weighting schemes. The research highlights the significant improvements in F1 scores achieved by optimized weights, particularly in systems with low modularity. Additionally, it identifies interesting patterns in the optimized weights, such as the high value of file-level dependencies and the low importance of MethodCall relations, which contrasts with previous findings. The study concludes by suggesting future work on learning-based weight derivation and comparative studies to further validate the findings.
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Metadata
Title
Optimized Dependency Weights in Source Code Clustering
Authors
Tobias Olsson
Morgan Ericsson
Anna Wingkvist
Copyright Year
2021
Book
Software Architecture

Print ISBN: 978-3-030-86043-1

Electronic ISBN: 978-3-030-86044-8

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-3-030-86044-8_16

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