Conference proceeding
Hotspot Patterns: The Formal Definition and Automatic Detection of Architecture Smells
2015 12TH WORKING IEEE/IFIP CONFERENCE ON SOFTWARE ARCHITECTURE (WICSA), pp 51-60
01 Jan 2015
Abstract
In this paper, we propose and empirically validate a suite of hotspot patterns: recurring architecture problems that occur in most complex systems and incur high maintenance costs. In particular, we introduce two novel hotspot patterns, Unstable Interface and Implicit Cross-module Dependency. These patterns are defined based on Baldwin and Clark's design rule theory, and detected by the combination of history and architecture information. Through our tool-supported evaluations, we show that these patterns not only identify the most error-prone and change-prone files, they also pinpoint specific architecture problems that may be the root causes of bug-proneness and change-proneness. Significantly, we show that 1) these structure-history integrated patterns contribute more to error-and change-proneness than other hotspot patterns, and 2) the more hotspot patterns a file is involved in, the more error- and change-prone it is. Finally, we report on an industrial case study to demonstrate the practicality of these hotspot patterns. The architect and developers confirmed that our hotspot detector discovered the majority of the architecture problems causing maintenance pain, and they have started to improve the system's maintainability by refactoring and fixing the identified architecture issues.
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Details
- Title
- Hotspot Patterns: The Formal Definition and Automatic Detection of Architecture Smells
- Creators
- Ran Mo - Drexel UniversityYuanfang Cai - Drexel UniversityRick Kazman - University of Hawaii SystemLu Xiao - Drexel University
- Contributors
- L Bass (Editor)P Lago (Editor)P Kruchten (Editor)
- Publication Details
- 2015 12TH WORKING IEEE/IFIP CONFERENCE ON SOFTWARE ARCHITECTURE (WICSA), pp 51-60
- Conference
- 2015 12TH WORKING IEEE/IFIP CONFERENCE ON SOFTWARE ARCHITECTURE (WICSA), 12th
- Publisher
- IEEE
- Number of pages
- 10
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Computer Science
- Web of Science ID
- WOS:000380388500006
- Scopus ID
- 2-s2.0-84943228098
- Other Identifier
- 991019167531104721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Computer Science, Software Engineering
- Computer Science, Theory & Methods