Software teams are often asked to deliver new features within strict deadlines leading developers to deliberately or inadvertently serve “ not quite right code ” compromising software quality and maintainability. This non-ideal state of software is efficiently captured by the Technical Debt (TD) metaphor, which reflects the additional effort that has to be spent to maintain software. Although several tools are available for assessing TD, each tool essentially checks software against a particular ruleset. The use of different rulesets can often be beneficial as it leads to the identification of a wider set of problems; however, for the common usage scenario where developers or researchers rely on a single tool, diverse estimates of TD and the identification of different mitigation actions limits the credibility and applicability of the findings. The objective of this study is two-fold: First, we evaluate the degree of agreement among leading TD assessment tools. Second, we propose a framework to capture the diversity of the examined tools with the aim of identifying few “ reference assessments ” (or class/file profiles) representing characteristic cases of classes/files with respect to their level of TD. By extracting sets of classes/files exhibiting similarity to a selected profile (e.g., that of high TD levels in all employed tools) we establish a basis that can be used either for prioritization of maintenance activities or for training more sophisticated TD identification techniques. The proposed framework is illustrated through a case study on fifty (50) open source projects and two programming languages (Java and JavaScript) employing three leading TD tools.

中文翻译：

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评估技术债务衡量工具之间的一致性：建立技术债务负债的经验基准

软件团队经常被要求在严格的期限内交付新功能，导致开发人员有意或无意地提供“不太正确的代码”，从而影响软件质量和可维护性。技术债务 (TD) 比喻有效地捕捉了这种非理想的软件状态，这反映了必须花费额外的精力来维护软件。尽管有多种工具可用于评估 TD，但每种工具本质上都是根据特定规则集检查软件。使用不同的规则集通常是有益的，因为它可以识别更广泛的问题；然而，对于开发人员或研究人员依赖单一工具的常见使用场景，对 TD 的不同估计和不同缓解措施的识别限制了研究结果的可信度和适用性。本研究的目的有两个：首先，我们评估领先的 TD 评估工具之间的一致程度。其次，我们提出了一个框架来捕捉所检查工具的多样性，目的是确定很少的“参考评估”（或类/文件配置文件）代表类/文件在其 TD 级别方面的特征案例。通过提取与所选配置文件（例如，所有采用的工具中的高 TD 级别的配置文件）相似的类/文件集，我们建立了一个基础，可用于确定维护活动的优先级或培训更复杂的 TD 识别技术。通过对五十 (50) 个开源项目和两种编程语言（Java 和 JavaScript）使用三个领先的 TD 工具的案例研究来说明所提议的框架。