Showing papers in "Journal of Systems and Software in 2019"

TL;DR: The experimental results show that FogBus is comparatively lightweight and responsive, and different FogBus settings can tune the computing environment as per the situation demands.

TL;DR: This study provides a solid, rigorous, and replicable picture of the state of the art on architecting with microservices and can benefit both researchers and practitioners of the field.

TL;DR: In this paper, a systematic mapping study sheds light on how security is actually addressed when dealing with cyber-physical systems from an automatic control perspective, based on application fields, various system components, related algorithms and models, attacks characteristics and defense strategies.

TL;DR: The findings suggest that EUD, EUP and EUSE are active research topics not only in Human–Computer Interaction, but also in other research communities, as well as unifying frameworks and approaches for guiding novice designers and practitioners.

TL;DR: This paper proposes a novel resource management technique (ROUTER) for fog-enabled Cloud computing environments, which leverages Particle Swarm Optimization to optimize simultaneously, and results demonstrate a reduction of 12% network bandwidth, 10% response time, 14% latency and 12.35% in energy consumption.

TL;DR: This paper investigates to what extent commits are partially defective; then, a novel fine-grained just-in-time defect prediction model is proposed to predict the specific files, contained in a commit, that are defective; and the extent to which it decreases the effort required to diagnose a defect is evaluated.

TL;DR: A novel and effective evolutionary approach for VM allocation that can maximize the energy efficiency of a cloud data center while incorporating more reserved VMs and consolidate more VMs with fewer physical machines to achieve better energy efficiency than existing methods is proposed.

TL;DR: It is found that successfully adopting FAAS requires a different mental model, where systems are primarily constructed by composing pre-existing services, with FaaS often acting as the “glue” that brings these services to the application developers, and tooling availability and maturity remains a major difficulty.

TL;DR: It is provided evidence that collaboration is the core DevOps concern, contrasting with an existing wisdom that automation and tooling can be enough to achieve DevOps.

TL;DR: This paper analyzes bug reports of 119 popular projects belonging to three ecosystems such as Mozilla, Apache, and Eclipse with the aim of building a taxonomy of the types of reported bugs and devise and evaluate an automated classification model able to classify reported bugs according to the defined taxonomy.

TL;DR: There is a need for actionable, context-sensitive, and evaluated solutions rather than novel ones in systematic reviews, and evidence and quality need to be better used in the resulting syntheses.

TL;DR: A historical perspective and future lines of research concerning the adoption of many-objective optimisation within SBSE are provided, an emerging area that provides advanced techniques to cope with high-dimensional optimisation problems.

TL;DR: An emotion-oriented requirements engineering approach is introduced to help identifying, modeling and evaluating emotional goals and how this technique was used to develop SofiHub - a new smart home platform for elderly people.

TL;DR: The current knowledge about reducing the cost of mutation testing through a systematic literature review is summarized and analyzed, finding that cost reduction for mutation is increasingly becoming interdisciplinary, often combining multiple techniques.

TL;DR: A cuckoo optimization-based energy-reliability aware resource scheduling technique (CRUZE) for holistic management of cloud computing resources including servers, networks, storage, and cooling systems is proposed and evaluated against existing state-of-the-art solutions using the CloudSim toolkit.

TL;DR: A novel method MOFES (Multi-Objective FEature Selection), which takes two optimization objectives into account and can effectively select fewer but closely related features to construct high-quality models is proposed.

TL;DR: The results show that the proposed dataflow-driven decomposition approach can recommend microservice candidates with sound coupling and cohesion through a rigorous and easy-to-operate implementation with semi-automatic support.

TL;DR: A dynamic auto-scaling algorithm called ElasticSFC is proposed to minimize the cost while meeting the end-to-end latency of the service chain and the experimental results show that the proposed algorithm can reduce the cost of SFC deployment and SLA violation significantly.

TL;DR: A complete automated system to decompose an application into microservices, deploy the micro services using appropriate resources, and auto-scale the microservices to maintain the desired response time is proposed.

TL;DR: The issues surrounding package reuse and how to contribute to existing packages are focused on, and five recommendations for overcoming the identified issues are proposed for improving the health of the ROS ecosystem.

TL;DR: This paper surveys research work on SATD, analyzing the characteristics of current approaches and techniques for SATD detection, comprehension, and repayment, and compiling tools, resources, and data sets made available to replicate or extend current SATD research.

TL;DR: A meta-analysis to aggregate the results of the studies published in this area to provide a consolidated view on how to align SE education with industry needs, to identify the most important skills and also existing knowledge gaps.

TL;DR: The results confirm that generally existing solutions aiming at managing safety for mobile robotic systems are not yet ready to be used in everyday life and there is the need of turn-key solutions ready to deal with all the challenges.

TL;DR: A deep neural network is used with a new hybrid loss function that consists of a triplet loss to learn a more discriminative feature representation of the defect data and a weighted cross-entropy loss to remedy the imbalance issue.

TL;DR: It is found that top quartile organizations are more mature in all EA maturity areas and make more extensive use of different types of EA artifacts in the preparation of IT investment decisions, especially diagnostic and actionable artifacts.

TL;DR: A systematic review aimed at identifying the most frequently reported quality attributes and architectural tactics for Big Data Cybersecurity Analytic Systems revealed that despite the significance of interoperability, modifiability, adaptability, generality, stealthiness, and privacy assurance, these quality attributes lack explicit architectural support in the literature.

TL;DR: Character education is a growing discipline in recent times with the intent of optimizing student's ethical behaviour as mentioned in this paper. The outcome of character education has been seen in the continuous encouragement and preparation of a solid background of the leaders of tomorrow.

TL;DR: An exploratory study on identifying features, locations, and facets in two popular, variant-rich, and long-living systems: The 3D-printer firmware Marlin and the Android application Bitcoin-wallet.

TL;DR: This paper presents CVErizer, an approach able to automatically generate summaries of daily posted vulnerabilities and categorize them according to a taxonomy modeled for industry, and demonstrates the high performance of the proposed approach in correctly extracting and classifying information from CVE descriptions.

TL;DR: To explicitly capture the dependencies and consistency rules that must hold between the disparate engineering models, a dedicated graphical modeling language is proposed and by means of this language, stakeholders can specify, diagnose, and handle inconsistencies in the accompanying inconsistency management framework.