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Abstract. [Context & motivation]Requirements prioritization is typically applied in order to determine which requirements or features should be included in a certain release or implemented first. While most requirements prioritization approaches prescribe a fixed set of prioritization criteria that have to be assessed during the prioritization process, there is often a need for criteria that are customized to the specific project situation. [Question/problem] However, determining customized prioritization criteria is a time-consuming and laborious task. Instead of an in-depth analysis, criteria are often identified by gut feeling, which is error-prone and bears the risk of choosing misleading criteria. [Principal ideas/results] This paper aims at identifying and categorizing prioritization criteria discussed in the vast body of prioritization literature for software development. We describe a systematic literature review and, as a result, present a consolidated prioritization criteria model. [Contribution] Besides a comprehensive overview of prioritization criteria discussed in the literature, this paper introduces a classification schema that allows researchers and practitioners to identify prioritization criteria and related literature in a time-saving manner.

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Non-functional characteristics of products can be essential for business success and are a key differentiator between a company and its competitors. This paper presents the application of a systematic, experience-based method to elicit, document, and analyze non-functional requirements. The objective of the method is to achieve a minimal and sufficient set of measurable and traceable non-functional requirements. The method gives clear guidance for the requirements elicitation, using workshops for capturing the important quality aspects and eliciting the non-functional requirements. This paper shows its application in three different settings, reporting the experience and lessons learned from industrial case studies that applied our NFR method. As the case studies were applied in different domains and performed with companies of various maturity, and since different quality attributes were considered, a set of interesting results has emerged. Therefore, each case study tells its own story about how the elicitation of NFR in industry can work. The paper discusses the different settings and gives a comparison of the different lessons we learned from the case studies

Abstract. [Context and motivation]Stakeholders who are highly distributed form a large, heterogeneous online group, the so-called "crowd". The rise of mobile, social and cloud apps has led to a stark increase in crowd-based settings. [Question/problem] Traditional requirements engineering (RE) techniques face scalability issues and require the co-presence of stakeholders and engineers, which cannot be realized in a crowd setting. While different approaches have recently been introduced to partially automate RE in this context, a multi-method approach to (semi-)automate all RE activities is still needed. [Principal ideas/results]We propose "Crowd-based Requirements Engineering" as an approach that integrates existing elicitation and analysis techniques and fills existing gaps by introducing new concepts. It collects feedback through direct interactions and social collaboration, and by deploying mining techniques.[Contribution] This paper describes the initial state of the art of our approach, and previews our plans for further research. IntroductionOffering services and applications online opens the way to a potentially large market, but competition is high in this field. This pressures developers and service providers into continuously exciting their customers with positive interactions and innovations in order to prevent them from switching to competitive solutions. Requirements engineering (RE) plays a pivotal role in mapping and anticipating the stakeholders' needs. However, traditional RE techniques depend on co-presence (i.e., on the analyst(s) and stakeholder(s) gathered at the same time and place) and therefore do not scale well to settings with many distributed stakeholders [1]. As online users are physically distributed, remote RE techniques are required that allow the analyst(s) and the many stakeholders to be active in different places and at different times [2]. Existing techniques in the area of remote RE techniques rely on (semi-)automating aspects of RE (e.g., [2,3]), but the greatest challenge is to bridge the gaps between them in an integrated approach. We argue in this paper that research has so far focused on particular sub-domains and has not approached this field holistically

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The Internet of Things (IoT) connects a variety of small devices, via gateways, to the cloud. Use-cases often require IoT devices to run logic that is not pre-determined before deployment, and that must be updated during the life-time of the device. In this paper, we explore the potential of over-the-air scripting and updatable runtime containers hosting application logic on heterogeneous low-end IoT devices. Based on RIOT and Javascript, we provide a proof-of-concept implementation of this approach for a building automation IoT scenario. A preliminary evaluation shows our prototype runs on common off-the-shelf low-end IoT hardware with as little as 32kB of memory.

Providing high-quality software within budget is a goal pursued by most software companies. Incomplete requirements specifications can have an adverse effect on this goal and thus on a company's competitiveness. Several empirical studies have investigated the effects of requirements engineering methods on the completeness of a specification. In order to increase this body of knowledge, we suggest using an objective evaluation scheme for assessing the completeness of specification documents, as objectifying the term completeness facilitates the interpretation of evaluations and hence comparison among different studies. This paper reports experience from applying the scheme to a student experiment comparing a use case with a textual approach common in industry. The statistical analysis of the specification's completeness indicates that use case descriptions lead to more complete requirements specifications. We further experienced that the scheme is applicable to experiments and delivers meaningful results. Completerequirement, incomplete requirement, completeness, experiment, use case, embedded systems, automotive