Architectural technical debt can have a huge impact on software maintainability and evolution. Hence, different architectural violations, detected as architectural smells, need to be identified and refactored. In this paper, we conducted a multiple case-study on several architectural smells detected in four industrial projects. We conducted an in-depth investigation with a questionnaire, interviews and thorough inspection of the code with the practitioners. We evaluated the negative impact of the technical debt detected by the architectural smells, their difficulty to be refactored and the usefulness of the detection tool. The results show that practitioners appreciated the help of automatic detection, and that they prioritize refactoring architectural debt that causes more negative impact despite the higher refactoring effort.

Martini, A., Fontana Arcelli, F., Biaggi, A., Roveda, R. (2018). Identifying and prioritizing architectural debt through architectural smells: A case study in a large software company. In Software Architecture (pp.320-335). Springer Verlag [10.1007/978-3-030-00761-4_21].

Identifying and prioritizing architectural debt through architectural smells: A case study in a large software company

Fontana Arcelli, F;Roveda, R
2018

Abstract

Architectural technical debt can have a huge impact on software maintainability and evolution. Hence, different architectural violations, detected as architectural smells, need to be identified and refactored. In this paper, we conducted a multiple case-study on several architectural smells detected in four industrial projects. We conducted an in-depth investigation with a questionnaire, interviews and thorough inspection of the code with the practitioners. We evaluated the negative impact of the technical debt detected by the architectural smells, their difficulty to be refactored and the usefulness of the detection tool. The results show that practitioners appreciated the help of automatic detection, and that they prioritize refactoring architectural debt that causes more negative impact despite the higher refactoring effort.
paper
Software Engineering, Technical Debt, Computer Science (all)
English
European Conference on Software Architecture, ECSA 2018
2018
Software Architecture
9783030007607
2018
2018
11048
320
335
none
Martini, A., Fontana Arcelli, F., Biaggi, A., Roveda, R. (2018). Identifying and prioritizing architectural debt through architectural smells: A case study in a large software company. In Software Architecture (pp.320-335). Springer Verlag [10.1007/978-3-030-00761-4_21].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/219091
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