Requirements Specification using Qualitative Data Analysis

使用定性数据分析的需求规范

• 批准号: 508498149
• 负责人: Professor Dr. Dirk Riehle
• 金额: --
• 依托单位: Department Informatik
• 依托单位国家: 德国
• 项目类别: Research Grants
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/508498149?language=en
• 关键词: Requirements; Specification; using; Qualitative; Data

Requirements engineering is a key activity in software engineering. Eliciting requirements from stakeholders and domain experts is an error-prone process, which, if done poorly, creates significant problems for the ensuing project (or product). At its heart, in requirements engineering, requirements engineers take qualitative data as input (interviews with stakeholders, workshop notes, collateral) and turn them into a requirements specification. We propose to adapt from the social sciences the use of qualitative data analysis (QDA) methods for eliciting requirements. Used in scientific theory building, QDA methods deliver high completeness and consistency of output. In addition, all output is linked back to the original input in a clear and traceable way. We previously adopted QDA for the creation of a domain model in requirements engineering. In this proposal, we plan to develop an extended method and apply it to the creation and evolution of hierarchical natural language requirements specifications. We expect the method to deliver higher completeness and consistency of requirements than what other methods can currently achieve. In addition, we expect that our approach solves the pre-requirements specification (pre-RS) challenge, which has so far been examined only sparingly. We intend to follow a design science approach in our proposed research: We will first identify current problems, then define objectives for a solution to these problems, design an artifact (here the new method) aimed at achieving this objective, build a tool to evaluate the new method, and finally demonstrate and evaluate our method using the tool in a case study.

需求工程是软件工程中的一项关键活动。从涉众和领域专家那里获取需求是一个容易出错的过程，如果做得不好，会给随后的项目（或产品）带来严重的问题。在需求工程中，需求工程师将定性数据作为输入（与利益相关者的访谈，研讨会笔记，抵押品），并将其转化为需求规格说明。我们建议从社会科学中采用定性数据分析（QDA）方法来引出需求。在科学理论构建中，QDA方法提供了高完整性和一致性的输出。此外，所有输出都以清晰和可追溯的方式链接到原始输入。我们以前采用QDA来创建需求工程中的域模型。在这个建议中，我们计划开发一个扩展的方法，并将其应用到创建和层次自然语言需求规格说明的演变。我们希望该方法能够提供比其他方法目前所能实现的更高的完整性和一致性。此外，我们希望我们的方法解决了前需求规范（前RS）的挑战，到目前为止，这只被检查很少。我们打算遵循设计科学的方法，在我们提出的研究：我们将首先确定当前的问题，然后定义解决这些问题的目标，设计一个工件（这里的新方法），旨在实现这一目标，建立一个工具来评估新方法，最后演示和评估我们的方法使用的工具在案例研究。