João Ricardo Lourenço

Choosing the right NoSQL database for the job: a quality attribute evaluation

For over forty years, relational databases have been the leading model for data storage, retrieval and management. However, due to increasing needs for scalability and performance, alternative systems have emerged, namely NoSQL technology. The rising interest in NoSQL technology, as well as the growth in the number of use case scenarios, over the last few years resulted in an increasing number of evaluations and comparisons among competing NoSQL technologies. While most research work mostly focuses on performance evaluation using standard benchmarks, it is important to notice that the architecture of real world systems is not only driven by performance requirements, but has to comprehensively include many other quality attribute requirements. Software quality attributes form the basis from which software engineers and architects develop software and make design decisions. Yet, there has been no quality attribute focused survey or classification of NoSQL databases where databases are compared with regards to their suitability for quality attributes common on the design of enterprise systems. To fill this gap, and aid software engineers and architects, in this article, we survey and create a concise and up-to-date comparison of NoSQL engines, identifying their most beneficial use case scenarios from the software engineer point of view and the quality attributes that each of them is most suited to.

NoSQL Databases: A Software Engineering Perspective

For over forty years, relational databases have been the leading model for data storage, retrieval and management. However, due to increasing needs for scalability and performance, alternative systems have started being developed, namely NoSQL technology. With increased interest in NoSQL technology, as well as more use case scenarios, over the last few years these databases have been more frequently evaluated and compared. It is necessary to find if all the possibilities and characteristics of non-relational technology have been disclosed. While most papers perform mostly performance evaluation using standard benchmarks, it is nevertheless important to notice that real world scenarios, with real enterprise data, do not function solely based on performance. In this paper, we have gathered a concise and up-to-date comparison of NoSQL engines, their most beneficial use case scenarios from the software engineer viewpoint, their advantages and drawbacks by surveying the currently available literature.

Soft Bionics Hands with a Sense of Touch Through an Electronic Skin

Integration of compliance into the Robotics hands proved to enhance the functionality of under-actuated hands for prosthetic or industrial applications. An appropriate design of the finger geometry with compliant joints allows the fingers to adapt to the shape of the object, and the soft and compliant skin allows for a higher contact area and contact friction. In this article, we describe how these properties were exploited for the development of compliant hands that are simple, efficient and easy to control. We also discuss integration of soft pressure and bending sensors into the digits of these hands.

Autonomous Selection of Closing Posture of a Robotic Hand Through Embodied Soft Matter Capacitive Sensors

Soft matter capacitive sensors are developed and integrated into the silicone skin of finger tips and palm of a robotic hand. Distributed sensing nodes are used for obtaining preliminary pre-touch information about the object that should be grasped. This includes conductive objects taking advantage of proximity sensing from changes in electric field and non-conductive objects taking advantage of pressure sensing from the deforming capacitive electrodes. We argue that this system can eventually address one important challenge in control of multi-DOF bionic hands, i.e., autonomously choosing the right closing pattern. Sensor fabrication, characterization, and integration into the hand are described. An algorithm for detection and activation of closing patterns is suggested, and results are discussed.

No SQL in Practice: A Write-Heavy Enterprise Application

The continuous information growth in current organizations has created a need for adaptation and innovation in the field of data storage. Alternative technologies such as NoSQL have been heralded as the solution to the ever-growing data requirements of the corporate world, but these claims have not been backed by many real world studies. Current benchmarks evaluate database performance by executing specific queries over mostly synthetic data. These artificial scenarios, then, prevent us from easily drawing conclusions for the real world and appropriately characterize the performance of databases in a real system. To counter this, we used a real world enterprise system with real corporate data to evaluate the performance characteristics of popular NoSQL databases and compare them to SQL counterparts. In particular, we present one of the first write-heavy evaluations using enterprise software and big data. We tested Cassandra, Mongo DB, Couchbase Server and MS SQL Server and compared their performance while handling demanding and large write requests from a real company with an electrical measurement enterprise system.

A Predictive Model for Exception Handling

The exception handling mechanism has been one of the most used reliability tools in programming languages for over four decades. Nearly all modern languages have some form of “try-catch” model for exception handling and encourage its use. Nevertheless, this model has not seen significant change, even in the face of new challenges, such as concurrent programming and the advent of reactive programming. As it stands, the current model is reactive, rather than proactive—exceptions are raised, caught, and handled. We propose an alternative exception handling model—PreX—where exceptions are no longer caught but, rather, predicted and prevented. Online Failure Prediction techniques generally work at a very high level, showing potential for prediction of program crashes. However, these techniques have never been at the hands of the programmers as an effective tool to improve software quality. By applying recent advances in Online Failure Prediction, PreX aims to fully prevent exceptions, bringing failure prediction techniques to a much more fine-grained level that the programmer can control. Predicting exceptions enables a range of preventive measures that enhance the reliability and robustness of a system, offering new revitalization strategies to developers.

3D printed endoskeleton with a soft skin for upper-limb body actuated prosthesis

The development of upper limb prostheses had a great growth with the proliferation of additive manufacturing technologies. This article suggests the design and development of a novel Bio-inspired compliant finger which is composed of a 3D printed rigid endoskeleton covered by soft matter, to apply to body actuated upper limb prostheses. We demonstrate the design and implementation of this finger and show how such finger can improve the hands functionality substantially. The hand performance is evaluated against a comprehensive grasp list that contains 33 grasps that humans perform in daily tasks. While the previous version of the body-actuated hand could perform only 5 of these 33 grasps, the updated version of the hand with soft fingers could perform 23 grasps.

PreX: A predictive model to prevent exceptions

Abstract The exception handling mechanism has been one of the most used reliability tools in programming languages in the last decades. However, this model has not changed much with time, in spite of advances in programming languages, which include concurrent programming and a shift towards more reactive paradigms, the basic principle remains the same - an exception occurs, and the mechanism reacts. We propose a new paradigm, inspired by Online Failure Prediction (OFP), to predict exceptions and possibly avert them by triggering the execution of preventive actions. The proposed model - PreX - is, thus, proactive, operating in a much finer-grained level than any other form of online failure prediction. OFP has shown promising results in predicting failures at a higher level, but has never been available to the developer, being mainly a system level technique. Thus, PreX will offer developers a new range of revitalization strategies. In this work, we describe the model and evaluate its performance by applying it to a real e-commerce solution, demonstrating how it is capable of predicting and preventing exceptions at run-time. Furthermore, we also show that PreX increases the overall availability and performance of the system under the same conditions.

Comparing NoSQL Databases with a Relational Database: Performance and Space

The continuous information growth in current organizations has created a need for adaptation and innovation in the field of data storage. Alternative technologies such as NoSQL have been heralded as the solution to the ever-growing data requirements of the corporate world, but these claims have not been backed by many real world studies. Current benchmarks evaluate database performance by executing specific queries over mostly synthetic data. These artificial scenarios, then, prevent us from easily drawing conclusions for the real world and appropriately characterize the performance of databases in a real system. To counter this, we used a real world enterprise system with real corporate data to evaluate the performance and space characteristics of popular NoSQL databases and compare them to SQL counterparts. We present one of the first write-heavy evaluations using enterprise software and big data. We tested Cassandra, MongoDB, Couchbase Server and MS SQL Server, comparing their performance and total used space while handling demanding and large write requests from a real company with an electrical measurement enterprise system.