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In theory, software product lines are planned in advance, using established engineering methods. However, there are cases where commonalities and variabilities between several systems are only discovered after they have been developed individually as single systems. In retrospect, this leads to the hindsight that these systems should have been developed as a software product line from the beginning to reduce costs and effort. To cope with the challenge of detecting variability early on, we propose the PREVISE method, covering domain and application engineering. Domain engineering is concerned with exploring the variability caused by entities in the environment of the software and the variability in functional and quality requirements. In application engineering, the configuration for a concrete product is selected, and subsequently, a requirement model for a concrete product is derived.

Although an intensive research attention has been paid to software evolution, there is no established approach which supports a software development and evolution round-trip between requirements, design decisions, architectural elements, and code. The ADVERT approach shall provide support for software evolution on an architectural level. AD-VERT is based on two core ideas: (1) Maintaining trace links between requirements, design decisions, and architecture elements, and (2) explicitly integrating software architecture information into the code. The expected benefits of the approach are: (1) Eased understanding of the relationship between requirements and design, and (2) assured compliance between architectural design and implementation. In this position paper we explain our envisioned approach and demonstrate it on a CoCoME-based example, which is a benchmark for component-based modelling approaches.

Existing fair exchange protocols usually neglect consideration of cost when assessing their fairness. However, in an environment with non-negligible transaction cost, e.g., public blockchains, high or unexpected transaction cost might be an obstacle for wide-spread adoption of fair exchange protocols in business applications. For example, as of 2021-12-17, the initialization of the FairSwap protocol on the Ethereum blockchain requires the selling party to pay a fee of approx. 349.20 USD per exchange. We address this issue by defining cost fairness, which can be used to assess two-party exchange protocols including implied transaction cost. We show that in an environment with non-negligible transaction cost where one party has to initialize the exchange protocol and the other party can leave the exchange at any time cost fairness cannot be achieved.

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The rapid pace with which software needs to be built, together with the increasing need to evaluate changes for end users both quantitatively and qualitatively calls for novel software engineering approaches that focus on short release cycles, continuous deployment and delivery, experiment-driven feature development, feedback from users, and rapid tool-assisted feedback to developers. To realize these approaches there is a need for research and innovation with respect to automation and tooling, and furthermore for research into the organizational changes that support flexible data-driven decision-making in the development lifecycle. Most importantly, deep synergies are needed between software engineers, managers, and data scientists. This paper reports on the results of the joint 5th International Workshop on Rapid Continuous Software Engineering (RCoSE 2019) and the 1st International Workshop on Data-Driven Decisions, Experimentation and Evolution (DDrEE 2019), which focuses on the challenges and potential solutions in the area of continuous data-driven software engineering.

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