Springer Science and Business Media LLC

High-quality requirements minimize the risk of propagating defects to later stages of the software development life cycle. Achieving a sufficient level of quality is a major goal of requirements engineering. This requires a clear definition and understanding of requirements quality. Though recent publications make an effort at disentangling the complex concept of quality, the requirements quality research community lacks identity and clear structure which guides advances and puts new findings into an holistic perspective. In this research commentary, we contribute (1) a harmonized requirements quality theory organizing its core concepts, (2) an evaluation of the current state of requirements quality research, and (3) a research roadmap to guide advancements in the field. We show that requirements quality research focuses on normative rules and mostly fails to connect requirements quality to its impact on subsequent software development activities, impeding the relevance of the research. Adherence to the proposed requirements quality theory and following the outlined roadmap will be a step toward amending this gap.

Construction projects involve multidisciplinary and multi-actor collaborations that generate massive amounts of data over their lifecycle. Data are often sensitive and embody rights, ownership, and intellectual property of the creator. Managing project information raises concerns about security, inconsistency, and loss of data. Conventional approach of dealing with the complexities of data management involves the adoption of BIM-based solutions that lack suitable means for the governance of collaboration, and access and archival of managed data. To overcome the limitations of BIM, cloud-based governance solutions have been suggested as a way forward. However, there is a lack of understanding of construction Information and Communication Technology (ICT) practices from the perspectives of data management and governance. This paper aims to fill this gap: first, by exploring barriers related to BIM adoption and collaboration practices, in particular, issues related to data management and governance that can potentially be ameliorated with cloud technologies, and second, by identifying key requirements for cloud-based BIM governance solutions. A structured questionnaire was conducted among informed construction practitioners in this study. The findings reveal several barriers to BIM adoption alongside ICT and collaboration issues with an urgent need to develop a BIM governance solution underpinned by cloud technology. Further, a number of important requirements for developing BIM governance solutions have been identified.

Designing Unmanned Aircraft Systems (UASs) for optimal autonomy while meeting user requirements is quite challenging. Researchers have focused on improving autonomy algorithms and verification methods to ensure safe and reliable autonomous behavior in UASs, but little research has been conducted on requirements engineering for UASs to answer design questions and explore the trade space for using autonomy to satisfy user requirements. This paper introduces a method to determine an optimal set of autonomous capabilities that satisfies UAS user requirements in the early stages of conceptual design. The method uses a modified Autonomy Requirements Engineering (ARE) process that applies quantitative measures and statistical analysis to Goal-Oriented Requirements Engineering (GORE). We demonstrate this method in a case study of a “disaster robot,” i.e., a hazard response UAS for which the autonomy requirements were optimized using a goal model developed in the Goal-oriented Requirement Language (GRL), as implemented in the modeling tool jUCMNav. The high-level goals of the hazard response UAS—system performance, cost, and safety—were evaluated using the formula-based GRL strategy evaluation algorithm resident in jUCMNav version 6.0. An autonomy trade space study was conducted through a Design and Analysis of Simulation Experiments (DASE). Our designed simulation experiment inserted the number of trials (evaluation strategies) and inputs into the goal model, and evaluation data were analyzed to optimize design factors based on user weightings of the response variables. This paper presents a structured method of ARE for UASs, which could be adopted more broadly across other domains, demonstrating how to optimize autonomous capabilities for different design conditions.

The paper deals with the problem of building an inventory of information systems for the public administration, with reference to an ongoing project in Italy. We describe the investigation techniques defined for collecting information and the techniques developed for a systematic analysis of the large set of conceptual schemas resulting from the investigation. These schemas describe the data used by the public administration work processes. In particular, we describe the conceptual schema of the inventory, which is the basis for discussing the methodology of investigation, the choice of units of investigation, the data collection and merging, and the access to information. Then, we present the schema analysis techniques developed to analyse semi-automatically the large set of conceptual schemas resulting from the investigation. In particular, we illustrate indexing techniques for identifying representative descriptors of schemas and similarity techniques to compare schemas for their classification into families. Finally, the tool developed to support the storage, analysis and classification of schemas is described and experimentation results are discussed.

Many modern software-intensive systems consist of multiple components interacting together to deliver the intended functionality. Often, these systems come in many variants (products) and are managed together as a software product line. This variability is the source of additional complexity which can cause inconsistencies and offset the economies of scale promised by product line engineering. Engineers thus need intuitive, yet precise means for specifying requirements and require tools for automatically detecting inconsistencies within these requirements. In recent work, we proposed a technique for the scenario-based specification of interactions in product lines by a combination of Modal Sequence Diagrams and Feature Diagrams. Furthermore, we elaborated an efficient consistency-checking technique based on a dedicated model-checking approach especially tailored for product lines. In this paper, we report on further evaluations that underline significant performance benefits of our approach. We describe further optimizations and detail on how we encode the consistency-checking problem for a model-checker.