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Experiences Applying Automated Architecture Analysis Tool Suites
Conference proceeding

Experiences Applying Automated Architecture Analysis Tool Suites

Ran Mo, Will Snipes, Yuanfang Cai, Srini Ramaswamy, Rick Kazman and Martin Naedele
PROCEEDINGS OF THE 2018 33RD IEEE/ACM INTERNATIONAL CONFERENCE ON AUTOMTED SOFTWARE ENGINEERING (ASE' 18), pp 779-789
01 Jan 2018

Abstract

Computer Science Computer Science, Software Engineering Computer Science, Theory & Methods Science & Technology Technology
In this paper, we report our experiences of applying three complementary automated software architecture analysis techniques, supported by a tool suite, called DV8, to 8 industrial projects within a large company. DV8 includes two state-of-the-art architecture level maintainability metrics Decoupling Level and Propagation Cost, an architecture flaw detection tool, and an architecture root detection tool. We collected development process data from the project teams as input to these tools, reported the results back to the practitioners, and followed up with telephone conferences and interviews. Our experiences revealed that the metrics scores, quantitative debt analysis, and architecture flaw visualization can effectively bridge the gap between management and development, help them decide if, when, and where to refactor. In particular, the metrics scores, compared against industrial benchmarks, faithfully reflected the practitioners' intuitions about the maintainability of their projects, and enabled them to better understand the maintainability relative to other projects internal to their company, and to other industrial products. The automatically detected architecture flaws and roots enabled the practitioners to precisely pinpoint, visualize, and quantify the "hotspots" within the systems that are responsible for high maintenance costs. Except for the two smallest projects for which both architecture metrics indicated high maintainability, all other projects are planning or have already begun refactorings to address the problems detected by our analyses. We are working on further automating the tool chain, and transforming the analysis suite into deployable services accessible by all projects within the company.

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27 citations in Scopus

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Industry collaboration
Domestic collaboration
International collaboration
Web of Science research areas
Computer Science, Software Engineering
Computer Science, Theory & Methods
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