Model-driven requirements engineering: Synchronising models in an air traffic management case study

Different modelling techniques from different disciplines are needed to model complex socio-technical systems and their requirements. This paper describes the application of RESCUE, a process that integrates 4 modelling techniques to model and analyse stakeholder requirements for DMAN, a system for scheduling and managing the departure of aircraft from major European airports. It describes how human activity, use case and i* modelling were applied and integrated using synchronisation checks to model requirements on DMAN. Synchronisation checks applied at predefined stages in RESCUE revealed omissions and potential inconsistencies in the models and stakeholder requirements that, in turn, led to improvements to the models and resulting specification. The paper ends with implications for requirements model integration, and describes future work to extend and apply RESCUE

A semi-automated BPMN-based framework for detecting conflicts between security, data-minimization, and fairness requirements

Requirements are inherently prone to conflicts. Security, data-minimization, and fairness requirements are no exception. Importantly, undetected conflicts between such requirements can lead to severe effects, including privacy infringement and legal sanctions. Detecting conflicts between security, data-minimization, and fairness requirements is a challenging task, as such conflicts are context-specific and their detection requires a thorough understanding of the underlying business processes. For example, a process may require anonymous execution of a task that writes data into a secure data storage, where the identity of the writer is needed for the purpose of accountability. Moreover, conflicts not arise from trade-offs between requirements elicited from the stakeholders, but also from misinterpretation of elicited requirements while implementing them in business processes, leading to a non-alignment between the data subjects’ requirements and their specifications. Both types of conflicts are substantial challenges for conflict detection. To address these challenges, we propose a BPMN-based framework that supports: (i) the design of business processes considering security, data-minimization and fairness requirements, (ii) the encoding of such requirements as reusable, domain-specific patterns, (iii) the checking of alignment between the encoded requirements and annotated BPMN models based on these patterns, and (iv) the detection of conflicts between the specified requirements in the BPMN models based on a catalog of domain-independent anti-patterns. The security requirements were reused from SecBPMN2, a security-oriented BPMN 2.0 extension, while the fairness and data-minimization parts are new. For formulating our patterns and anti-patterns, we extended a graphical query language called SecBPMN2-Q. We report on the feasibility and the usability of our approach based on a case study featuring a healthcare management system, and an experimental user study. \ua9 2020, The Author(s)

Detecting and Explaining Conflicts in Attributed Feature Models

Product configuration systems are often based on a variability model. The development of a variability model is a time consuming and error-prone process. Considering the ongoing development of products, the variability model has to be adapted frequently. These changes often lead to mistakes, such that some products cannot be derived from the model anymore, that undesired products are derivable or that there are contradictions in the variability model. In this paper, we propose an approach to discover and to explain contradictions in attributed feature models efficiently in order to assist the developer with the correction of mistakes. We use extended feature models with attributes and arithmetic constraints, translate them into a constraint satisfaction problem and explore those for contradictions. When a contradiction is found, the constraints are searched for a set of contradicting relations by the QuickXplain algorithm.Comment: In Proceedings FMSPLE 2015, arXiv:1504.0301

Semantic-based policy engineering for autonomic systems

This paper presents some important directions in the use of ontology-based semantics in achieving the vision of Autonomic Communications. We examine the requirements of Autonomic Communication with a focus on the demanding needs of ubiquitous computing environments, with an emphasis on the requirements shared with Autonomic Computing. We observe that ontologies provide a strong mechanism for addressing the heterogeneity in user task requirements, managed resources, services and context. We then present two complimentary approaches that exploit ontology-based knowledge in support of autonomic communications: service-oriented models for policy engineering and dynamic semantic queries using content-based networks. The paper concludes with a discussion of the major research challenges such approaches raise

The case of KAO

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia InformáticaRequirements engineering aims at eliciting, analyzing, specifying, validating and managing system requirements. When eliciting system requirements, it is possible to use various approaches, including goal-oriented and aspect-oriented approaches. Although those are two well-known approaches, they are seldom used in conjunction. On the other hand, when using goal-oriented approaches, one common and usual problem is the fact that some of the goals repeat themselves all over the system. This makes goal-oriented models to have a boost in complexity because of the repeating goals, and thus, making the evolution of this model harder than necessary. This complexity could be minimized if an aspect-oriented approach would be used. The big advantage of using a hybrid approach, in our case goal-oriented and aspect-oriented one is the possibility to identify all the scattered goals and modularize them as aspects. In this way we can represent this kind of goal (now an aspect) only once in the model. This means the complexity of the model will be greatly reduced and the readability of the model will also be improved. The final result will be an evolution that could be easily controlled, thus minimizing errors. Although this seems a good idea, there are some challenges to overcome when merging goals and aspects. First of all, a notation and a set of rules must be built in order to compose the model. In order to do this we will use patterns based on roles, as these will help elaborating the model. This work will present an approach that will make possible after modeling the system with a goal-oriented approach, identify aspects and then refine the model taking into account the aspects. In order to accomplish this, the KAOS methodology will be extended with aspects