Services and products are often offered via the execution of processes that vary according to the context, requirements, or customisation needs. The analysis of such process variants can highlight differences in the service outcome or quality, leading to process adjustments and improvement. Research in the area of process mining has provided several methods for process variants analysis. However, very few of those account for a statistical significance analysis of their output. Moreover, those techniques detect differences at the level of process traces, single activities, or performance. In this paper, we aim at describing the distinctive behavioural characteristics between variants expressed in the form of declarative process rules. The contribution to the research area is two-pronged: the use of declarative rules for the explanation of the process variants and the statistical significance analysis of the outcome. We assess the proposed method by comparing its results to the most recent process variants analysis methods. Our results demonstrate not only that declarative rules reveal differences at an unprecedented level of expressiveness, but also that our method outperforms the state of the art in terms of execution time.

中文翻译：

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通过声明性规则检测过程变体之间的统计上显着差异

服务和产品通常通过根据上下文，要求或定制需求而变化的过程的执行来提供。对此类流程变体的分析可以突出显示服务结果或质量方面的差异，从而导致流程调整和改进。过程挖掘领域的研究提供了几种方法来进行过程变量分析。但是，其中只有极少数能解释其产出的统计显着性分析。而且，这些技术在过程跟踪，单个活动或性能的水平上检测差异。在本文中，我们旨在描述以声明性过程规则形式表达的变体之间的独特行为特征。对研究领域的贡献有两个方面：使用声明性规则来解释过程变体和结果的统计显着性。我们通过将其结果与最新的过程变量分析方法进行比较来评估所提出的方法。我们的结果不仅表明声明性规则以前所未有的表现力水平揭示了差异，而且我们的方法在执行时间方面也超过了现有技术。