技术债务优先级:分类、方法、结果和实际特点

Diogo Pina, A. Goldman, G. Tonin
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引用次数: 6

摘要

技术债务是软件开发中的捷径的隐喻,它带来了短期利益,但长期的后果阻碍了维护和开发软件的过程。管理这些技术债务项目是很重要的,因为不是所有的都需要支付。拥有一份优先债务清单是管理过程中决策的重要步骤。这项工作旨在寻找技术债务优先排序方法,并对它们进行分类。也就是说,确定是否以及何时应该偿还技术债务的方法。我们进行了系统的制图审查,以查找和分析该地区的主要论文,涵盖了主要基地。我们选择了112项研究,得出51篇独特的论文。根据不同的可能结果,我们将这些方法分为两级分类法,其中包含10个类别。此外,我们还确定了三种方法的结果:布尔值、类别和有序列表。最后,我们还确定了在实际项目中优先考虑技术债务项的方法的实际技术特征和需求。尽管在文献中发现了几种方法,但它们都不能适应上下文并且与语言无关,也不能涵盖几种技术债务类型。此外,显然缺乏使用它们的工具。因此,总而言之,技术债务优先级的研究仍然是广泛开放的。从这项研究中,可以测试和自动化这些方法中使用的技术的组合,以协助应该偿还债务的决策过程。
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Technical Debt Prioritization: Taxonomy, Methods Results, and Practical Characteristics
Technical debt is the metaphor for shortcuts in software development that bring short-term benefits, but long-term consequences hinder the process of maintaining and developing software. It is important to manage these technical debt items, as not all of them need to be paid. Having a list of prioritized debts is an essential step in decision-making in the management process. This work aims at finding technical debt prioritization methods, providing a classification of them. That is, methods to identify whether and when a technical debt should be paid off. We performed a systematic mapping review to find and analyze the main papers of the area, covering the main bases. We selected 112 studies, resulting in 51 unique papers. We classified the methods in a two-level taxonomy containing 10 categories according to their different possible outcomes. In addition, we have identified three methods results: boolean, category and ordered list. Finally, we have also identified practical technical characteristics and requirements for a method to prioritize technical debt items in real projects. Although several methods have been found in literature, none of them are adaptive to the context and are language-independent, nor cover several technical debt types. Moreover, there is a clear lack of tools to use them. So, in conclusion, the research on technical debt prioritization is still wide open. From this study, a combination of the techniques used in these methods can be tested and automated to assist in the decision-making process on which debts should be paid.
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