Requirements Engineering Challenges of Supporting Agile Teams in System Development

Licentiate thesis, 2018

Context: Agile methods have attracted many companies due to their reported benefits of short time-to-market and improved quality outputs. In the systems development context, additional constraints apply e.g. as a result of scale or parallel development of hardware and software. Traditionally, stage-gate processes with a focus on up-front requirements analysis are common in large- scale systems engineering. These processes clash with the companies’ desire to become more agile.

Objective: The aim of this thesis is to discover challenges that new requirements engineering approaches should address to enable agile system devel- opment at scale (RE4Agile). With a focus on value and building system understanding, we explore these challenges from the perspective of the agile development teams.

Method: To meet our aim, we conducted a series of empirical studies based on case studies, and a secondary review to explore the problem domain while deriving challenges and potential solutions from industry and literature respectively.

Findings: Our findings show that there are numerous challenges of conducting requirements engineering in agile development especially where systems development is concerned. These challenges relate to user value and overall system understanding. However, there are some cross-cutting concerns, e.g safety- critical development, that have generated much interest both from practitioners and academicians at large.

Conclusions: The challenges discovered sprout from an integration problem of working with agile methods while using the already existing processes as well. However, solution candidates exist and our future research aims to validate some of the solution candidates in the view of deriving new RE approaches. This thesis contributes to such future research, by establishing a holistic map of challenges that allows to assess whether a given solution is beneficial in the larger context or whether it over-optimizes only one area.