Data Analytics for Technical Debt Management in Requirements Engineering

在金融领域，就某种形式的债务达成协议可以获得短期优势。此外 在偿还实际金额的同时，个人还必须偿还利息。接受技术债务可能是 优势，但也有失控的风险。同样适用于术语“技术债务”(TD)。 为软件和基于软件的系统创建。偏离“将成为”要求的状态与 “原样”的实际状态是一个潜在的风险。然而，这种偏离也可能产生潜在的(短期) 优势。 需求债务是一个新的研究领域，它着眼于业务中与需求相关的决策 透视。该项目研究了TD的建模、测量、分析和管理 面向服务的软件开发的需求工程阶段。特别是，技术债务 功能性和非功能性需求管理被认为是服务交付成功的主要因素。 ArCurve Inc.预计该项目的结果将对他们的项目管理流程产生影响。 具体地说，了解如何从当前围绕技术债务管理的定性决策转变为 量化的方法。我们希望该项目确定我们需要收集额外或更多资金的领域 准确的项目执行数据，并定义识别技术债务决策何时是 以及如何最好地做出这个决定。

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.