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The Value of Software Architecture Recovery for Maintenance
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In order to maintain a system, it is beneficial to know its software architecture. In the common case that this architecture is unavailable, architecture recovery provides a way to recover an architectural view of the system. Many different methods and tools exist to provide such a view. While there have been taxonomies of different recovery methods and surveys of their results along with measurements of how these results conform to expert's opinions on the systems, there has not been a survey that goes beyond an automatic comparison and instead seeks to answer questions about the viability of individual methods in given situations, the quality of their results and whether these results can be used to indicate and measure the quality and quantity of architectural changes. For our case study, we look at the results of recoveries of versions of Android and Apache Hadoop obtained by running PKG, ACDC and ARC.
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Semantic-Enhanced Automatic Refinement of Architecture Recovery Results Using LLMs
SemRef refines existing architecture-recovery outputs with LLMs and dependency analysis, reducing distance to ground truth by 17.72–43.35% RDP across five metrics on 90 recoveries.
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