An industrial case study for adopting software product lines in automotive industry an evolution-based approach for software product lines (EVOA-SPL)

Software Product Lines (SPLs) seek to achieve gains in productivity and time to market. Many companies in several domains are constantly adopting SPLs. Dealing with SPLs begin after companies find themselves with successful variants of a product in a particular domain. The adoption of an SPL-based approach in the automotive industry may provide a significant return on investment. To switch to an SPL-based approach, practitioners lack a reengineering approach that supports SPL migration and evolution in a systematic fashion. This paper presents a practical evolution-based approach to migrate and evolve a set of variants of a given product into an SPL and describes a case study from the automotive domain. The case study considers the need to handle the classical sensor variants family (CSVF) at Bosch Company. Using this study, we performed a contributed step toward future switch of the CSVF into the SPL. We investigated the applicability of the proposed evolution-based approach with a real variants family (using the textual requirements of the CSVF) and we evaluated our approach using several data collection methods. The results reveal that our approach can be suitable for the automotive domain in the case study.The University of Minho and Bosch Company supported this research. We thank our colleagues from the classical sensor development team at Bosch Company. Especially Andre L. Ferreira and Jana Seidel for their active collaboration and support. Special acknowledgment to the spirit of Helder Boas, who passed away after he offered the help and support to this research work

Reasoning on the usage control security policies over data artifact business process models

The inclusion of security aspects in organizations is a crucial aspect to ensure compliance with both internal and external regulations. Business process models are a well-known mechanism to describe and automate the activities of the organizations, which should include security policies to ensure the correct performance of the daily activities. Frequently, these security policies involve complex data which cannot be represented using the standard Business Process Model Notation (BPMN). In this paper, we propose the enrichment of the BPMN with a UML class diagram to describe the data model, that is also combined with security policies defined using the UCONABC framework annotated within the business process model. The integration of the business process model, the data model, and the security policies provides a context where more complex reasoning can be applied about the satisfiability of the security policies in accordance with the business process and data models. To do so, wetransform the original models, including security policies, into the BAUML framework (an artifact-centric approach to business process modelling). Once this is done, it is possible to ensure that there are no inherent errors in the model (verification) and that it fulfils the business requirements (validation), thus ensuring that the business process and the security policies are compatible and that they are aligned with the business security requirements.This work has been supported by Project PID2020-112540RB-C44 funded by MCIN/AEI/ 10.13039/501100011033, Project TIN2017-87610-R funded by MCIN/AEI/10.13039/501100011033 and FEDER “Una manera de hacer Europa”, Project 2017-SGR-1749 by the Generalitat de Catalunya, Projects COPERNICA (P20 01224) and METAMORFOSIS by the Junta de Andalucía.Peer ReviewedPostprint (published version

Measuring data‑centre workfows complexity through process mining: the Google cluster case

Data centres have become the backbone of large Cloud services and applica-tions, providing virtually unlimited elastic and scalable computational and storage resources. The search for the efficiency and optimisation of resources is one of the current key aspects for large Cloud Service Providers and is becoming more and more challenging, since new computing paradigms such as Internet of Things, Cyber-Physical Systems and Edge Computing are spreading. One of the key aspects to achieve efficiency in data centres consists of the discovery and proper analysis of the data-centre behaviour. In this paper, we present a model to automatically retrieve execution workflows of existing data-centre logs by employing process mining tech-niques. The discovered processes are characterised and analysed according to the understandability and complexity in terms of execution efficiency of data-centre jobs. We finally validate and demonstrate the usability of the proposal by applying the model in a real scenario, that is, the Google Cluster tracesMinisterio de Ciencia y Tecnología RTI2018–094283-B-C33Ministerio de Ciencia y Tecnología RTI2018-098062-A-I00Universidad de Sevilla 2018/0000052