Understanding Software Architecture Erosion: A Systematic Mapping Study release_2qzmaoykjvaixm4jey3nkvdhq4

by Ruiyin Li, Peng Liang, Mohamed Soliman, Paris Avgeriou

Released as a article .

2021  

Abstract

Architecture Erosion (AEr) can adversely affect software development and has received significant attention in the last decade. However, there is an absence of a comprehensive understanding of the state of research about the reasons and consequences of AEr, and the countermeasures to address AEr. This work aims at systematically investigating, identifying, and analyzing the reasons, consequences, and ways of detecting and handling AEr. With 73 studies included, the main results are: (1) AEr manifests not only through architectural violations and structural issues, but also causing problems in software quality and during software evolution, (2) non-technical reasons that cause AEr should receive the same attention as technical reasons, and practitioners should raise awareness of the grave consequences of AEr thereby taking actions to tackle AEr related issues, (3) a spectrum of approaches, tools, and measures have been proposed and employed to detect and tackle AEr, and (4) three categories of difficulties and five categories of lessons learned on tackling AEr were identified. The results can provide researchers a comprehensive understanding of AEr and help practitioners handle AEr and improve the sustainability of their architecture. More empirical studies are required to investigate the practices of detecting and addressing AEr in industrial settings.
In text/plain format

Archived Content

There are no accessible files associated with this release. You could check other releases for this work for an accessible version.

"Dark" Preservation Only
Save Paper Now!

Know of a fulltext copy of on the public web? Submit a URL and we will archive it

Type  article
Stage   submitted
Date   2021-12-21
Version   v1
Language   en ?
arXiv  2112.10934v1
Work Entity
access all versions, variants, and formats of this works (eg, pre-prints)
Catalog Record
Revision: d0fca090-71b4-4067-bdd2-6c7f002d51b2
API URL: JSON