Supporting Analysis of Technical Debt Causes and Effects with Cross-Company Probabilistic Cause-Effect Diagrams

Abstract

Understanding TD causes can support development teams in defining actions that could be taken to prevent the occurrence of debt items. Understanding the effects of TD could aid in prioritization of TD items to pay off to minimize possible negative consequences for the project. Existing work has revealed 105 causes and 85 effects of TD, and this high number can make it difficult to make practical use of this information. Without a consolidated representation, we would need to rely on a set of tables and isolated pieces of data. In this work, we propose the use of cross-company probabilistic cause-effect diagrams to represent information about TD causes and effects. We hypothesize that such diagrams can be useful to support TD cause/effect analysis sessions and empirically investigate this issue. Results from a case study performed with 72 participants indicate that the diagrams are able to positively support the management of TD, making it easier to identify its causes and the effects of its presence. Most of the participants also agreed that, by using the proposed diagrams, they gain agility, productivity, performance, and effectiveness. Finally, 89% of the participants stated that the use of the diagrams helped them to identify causes and effects of TD that they would not have identified without their support.