Data Analytics for Technical Debt Management in Requirements Engineering

点击翻译按钮获取中文摘要

In the world of finance, short term advantages can be achieved from agreeing on some form of debt. Besides paying back the actual amount, individuals must also pay back interest. Accepting technical debt can be of advantages, but also has a risk getting out of control. The same applies to the term "technical debt" (TD) created for software and software-based system. Deviating from the "to be" required status in comparison to the "as is" actual status is a potential risk. This deviation, however, can also generate potential (short-term) advantages. Requirements debt is a new area of research that looks at requirements related decisions from a business perspective. The project studies the modeling, measurement, analysis and management of TD in the requirements engineering phase of service-oriented software development. In particular, technical debt on functional and non-functional requirement management is considered as a main service delivery success factor. Arcurve Inc. expects the outcome of this project to effect change in their project management processes. Specifically, to understand how to shift from current qualitative decisions around technical debt management to a quantitative approach. We expect the project to identify areas where we are need to collect additional or more precise project-execution data, and to also define techniques for identifying when a Technical Debt decision is to be made and how to best make that decision.