Automated Functional Testing based on the Navigation of Web Applications

Web applications are becoming more and more complex. Testing such applications is an intricate hard and time-consuming activity. Therefore, testing is often poorly performed or skipped by practitioners. Test automation can help to avoid this situation. Hence, this paper presents a novel approach to perform automated software testing for web applications based on its navigation. On the one hand, web navigation is the process of traversing a web application using a browser. On the other hand, functional requirements are actions that an application must do. Therefore, the evaluation of the correct navigation of web applications results in the assessment of the specified functional requirements. The proposed method to perform the automation is done in four levels: test case generation, test data derivation, test case execution, and test case reporting. This method is driven by three kinds of inputs: i) UML models; ii) Selenium scripts; iii) XML files. We have implemented our approach in an open-source testing framework named Automatic Testing Platform. The validation of this work has been carried out by means of a case study, in which the target is a real invoice management system developed using a model-driven approach.Comment: In Proceedings WWV 2011, arXiv:1108.208

Software tools for sustainable water resources management: The GIS-integrated FREEWAT platform

This paper aims at presenting the open source and public domain FREEWAT platform capabilities for water resource management, including: (i) pre-processing modules to facilitate the preparation of input data, (ii) modelling tools for the analysis of several processes aimed at supporting water resource management, and (iii) post-processing tools to present results. The FREEWAT platform is based on open source solutions to perform an integrated coupling between the QGIS desktop software, surface and subsurface model engines, mostly based on fully distributed and numerically-based codes developed by the USGS, and other software applications, and the SpatiaLite spatial database. The development of the FREEWAT platform was supported by the main needs and priorities expressed by relevant stakeholders from the water sector involved in the early stage of the project. Extensive testing on the platform is still going on and training material and six User Manuals were prepared to disseminate its use as a standard software for managing surface/sub-surface water quantity and quality dynamics under demand-driven and supply-constrained conditions. The testing phase also includes demonstration of the platform capabilities on 14 case studies at European scale and beyond, to address specific water management issues. Nine of them are devoted to the application of EU water-related Directives, while the others address water management issues in the rural environment under the requirements of EU and/or national/local regulations. Beyond software testing, this demonstration is thought as an experiment on involving stakeholders in the formation of water plans yet during the technical phase of the analysis

Gridsemble: Selective Ensembling for False Discovery Rates

In this paper, we introduce Gridsemble, a data-driven selective ensembling algorithm for estimating local false discovery rates (fdr) in large-scale multiple hypothesis testing. Existing methods for estimating fdr often yield different conclusions, yet the unobservable nature of fdr values prevents the use of traditional model selection. There is limited guidance on choosing a method for a given dataset, making this an arbitrary decision in practice. Gridsemble circumvents this challenge by ensembling a subset of methods with weights based on their estimated performances, which are computed on synthetic datasets generated to mimic the observed data while including ground truth. We demonstrate through simulation studies and an experimental application that this method outperforms three popular R software packages with their default parameter values\unicode{x2014}common choices given the current landscape. While our applications are in the context of high throughput transcriptomics, we emphasize that Gridsemble is applicable to any use of large-scale multiple hypothesis testing, an approach that is utilized in many fields. We believe that Gridsemble will be a useful tool for computing reliable estimates of fdr and for improving replicability in the presence of multiple hypotheses by eliminating the need for an arbitrary choice of method. Gridsemble is implemented in an open-source R software package available on GitHub at jennalandy/gridsemblefdr.Comment: 12 pages, 3 figures (+ references and supplement). For open-source R software package, see https://github.com/jennalandy/gridsemblefdr. For all code used in the simulation studies and experimental application, see https://github.com/jennalandy/gridsemble_PAPE

CoSMoMVPA: Multi-Modal Multivariate Pattern Analysis of Neuroimaging Data in Matlab/GNU Octave

Recent years have seen an increase in the popularity of multivariate pattern (MVP) analysis of functional magnetic resonance (fMRI) data, and, to a much lesser extent, magneto- and electro-encephalography (M/EEG) data. We present CoSMoMVPA, a lightweight MVPA (MVP analysis) toolbox implemented in the intersection of the Matlab and GNU Octave languages, that treats both fMRI and M/EEG data as first-class citizens. CoSMoMVPA supports all state-of-the-art MVP analysis techniques, including searchlight analyses, classification, correlations, representational similarity analysis, and the time generalization method. These can be used to address both data-driven and hypothesis-driven questions about neural organization and representations, both within and across: space, time, frequency bands, neuroimaging modalities, individuals, and species. It uses a uniform data representation of fMRI data in the volume or on the surface, and of M/EEG data at the sensor and source level. Through various external toolboxes, it directly supports reading and writing a variety of fMRI and M/EEG neuroimaging formats, and, where applicable, can convert between them. As a result, it can be integrated readily in existing pipelines and used with existing preprocessed datasets. CoSMoMVPA overloads the traditional volumetric searchlight concept to support neighborhoods for M/EEG and surface-based fMRI data, which supports localization of multivariate effects of interest across space, time, and frequency dimensions. CoSMoMVPA also provides a generalized approach to multiple comparison correction across these dimensions using Threshold-Free Cluster Enhancement with state-of-the-art clustering and permutation techniques. CoSMoMVPA is highly modular and uses abstractions to provide a uniform interface for a variety of MVP measures. Typical analyses require a few lines of code, making it accessible to beginner users. At the same time, expert programmers can easily extend its functionality. CoSMoMVPA comes with extensive documentation, including a variety of runnable demonstration scripts and analysis exercises (with example data and solutions). It uses best software engineering practices including version control, distributed development, an automated test suite, and continuous integration testing. It can be used with the proprietary Matlab and the free GNU Octave software, and it complies with open source distribution platforms such as NeuroDebian. CoSMoMVPA is Free/Open Source Software under the permissive MIT license. Website: http://cosmomvpa.org Source code: https://github.com/CoSMoMVPA/CoSMoMVPA

Enabling Performance Evaluation beyond 10 Gbps

Despite network monitoring and testing being critical for computer networks, current solutions are both extremely expensive and inflexible. This demo presents OSNT (www.osnt.org), a community-driven, high-performance, open-source traffic generator and capture system built on top of the NetFPGA-10G board which enables flexible network testing. The platform supports full line-rate traffic generation regardless of packet size across the four card ports, packet capture filtering and packet thinning in hardware and sub-msec time precision in traffic generation and capture, corrected using an external GPS device. Furthermore, it provides a software APIs to test the dataplane performance of multi-10G switches, providing a starting point for a number of different test cases. OSNT flexibility is further demonstrated through the OFLOPS-turbo platform: an integration of OSNT with the OFLOPS OpenFlow switch performance evaluation platform, enabling control and data plane evaluation of 10G switches. This demo showcases the applicability of the OSNT platform to evaluate the performance of legacy and OpenFlow-enabled networking devices, and demonstrates it using commercial switches

Extracting individual trees from lidar point clouds using treeseg

Recent studies have demonstrated the potential of lidar-derived methods in plant ecology and forestry. One limitation to these methods is accessing the information content of point clouds, from which tree-scale metrics can be retrieved. This is currently undertaken through laborious and time-consuming manual segmentation of tree-level point clouds from larger-area point clouds, an effort that is impracticable across thousands of stems. Here, we present treeseg, an open-source software to automate this task. This method utilises generic point cloud processing techniques including Euclidean clustering, principal component analysis, region-based segmentation, shape fitting and connectivity testing. This data-driven approach uses few a priori assumptions of tree architecture, and transferability across lidar instruments is constrained only by data quality requirements. We demonstrate the treeseg algorithm here on data acquired from both a structurally simple open forest and a complex tropical forest. Across these data, we successfully automatically extract 96% and 70% of trees, respectively, with the remainder requiring some straightforward manual segmentation. treeseg allows ready and quick access to tree-scale information contained in lidar point clouds. treeseg should help contribute to more wide-scale uptake of lidar-derived methods to applications ranging from the estimation of carbon stocks through to descriptions of plant form and function

Web Application Performance Testing

Web application performance testing is an emerging and important field of software engineering. As web applications become more commonplace and complex, the need for performance testing will only increase. This paper discusses common concepts, practices and tools that lie at the heart of web application performance testing. A pragmatic, hands-on approach is assumed where applicable; real-life examples of test tooling, execution and analysis are presented right next to the underpinning theory. At the client-side, web application performance is primarily driven by the amount of data transmitted over the wire. At the server-side, selection of programming language and platform, implementation complexity and configuration are the primary contributors to web application performance. Web application performance testing is an activity that requires delicate coordination between project stakeholders, developers, system administrators and testers in order to produce reliable and useful results. Proper test definition, execution, reporting and repeatable test results are of utmost importance. Open-source performance analysis tools such as Apache JMeter, Firebug and YSlow can be used to realise effective web application performance tests. A sample case study using these tools is presented in this paper. The sample application was found to perform poorly even under the moderate load incurred by the sample tests.Siirretty Doriast

Towards a robust parallel solver for large-scale industrial flow simulations

In this work a CFD analysis is done on incompressible viscous flows using Finite Volume schemes implemented in the open-source software OpenFOAM. The objective of this study is twofold: to gain experience with the software and to define a set of best practices when running large-scale cases in OpenFOAM using parallel architectures. The first objective is obtained by testing three academic benchmarks, namely the lid- driven cavity, the flow over a backward facing step, and flow past a circular cylinder. The validation of these results is made by contrasting them to the data available in the literature. The second objective was fulfilled by studying two large-scale industrial problems, laminar flow inside an S-bend and turbulent external flow around a car. For the latter, the DriveAer geometry has been used. The analysis of these high- performance computing studies has been defined in terms of the relative efficiency and speed up for the two problems. The studied cases have been scaled up until 84 CPUs for the S-bend, and until 224 CPUs for the vehicle geometry. Furthermore, the performance of three partitioners, namely the simple, hierarchical, and scotch decomposers have been evaluated