Architectural technical debt (ATD) in a software-intensive system is the sum of all design choices that may have been suitable or even optimal at the time they were made, but which today are significantly impending progress: structure, framework, technology, languages, etc. Unlike code-level technical debt which can be readily detected by static analysers, and can often be refactored with minimal or only incremental efforts, architectural debt is hard to detect, and its remediation rather wide-ranging, daunting, and often avoided. The objective of this thesis is to develop a better understanding of architectural technical debt, and determine what strategies can be used to identify and manage it. In order to do so, we adopt a wide range of research techniques, including literature reviews, case studies, interviews with practitioners, and grounded theory. The result of our investigation, deeply grounded in empirical data, advances the field not only by providing novel insights into ATD related phenomena, but also by presenting approaches to pro-actively identify ATD instances, leading to its eventual management and resolution.

Architectural Technical Debt: Identification and Management

VERDECCHIA, ROBERTO
2021

Abstract

Architectural technical debt (ATD) in a software-intensive system is the sum of all design choices that may have been suitable or even optimal at the time they were made, but which today are significantly impending progress: structure, framework, technology, languages, etc. Unlike code-level technical debt which can be readily detected by static analysers, and can often be refactored with minimal or only incremental efforts, architectural debt is hard to detect, and its remediation rather wide-ranging, daunting, and often avoided. The objective of this thesis is to develop a better understanding of architectural technical debt, and determine what strategies can be used to identify and manage it. In order to do so, we adopt a wide range of research techniques, including literature reviews, case studies, interviews with practitioners, and grounded theory. The result of our investigation, deeply grounded in empirical data, advances the field not only by providing novel insights into ATD related phenomena, but also by presenting approaches to pro-actively identify ATD instances, leading to its eventual management and resolution.
30-set-2021
Inglese
TRUBIANI, CATIA
Gran Sasso Science Institute
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14242/116479
Il codice NBN di questa tesi è URN:NBN:IT:GSSI-116479