Avoiding coincidental correctness in boundary value analysis

In partition analysis we divide the input domain to form subdomains on which the system's behaviour should be uniform. Boundary value analysis produces test inputs near each subdomain's boundaries to find failures caused by incorrect implementation of the boundaries. However, boundary value analysis can be adversely affected by coincidental correctness---the system produces the expected output, but for the wrong reason. This article shows how boundary value analysis can be adapted in order to reduce the likelihood of coincidental correctness. The main contribution is to cases of automated test data generation in which we cannot rely on the expertise of a tester

The PLATO Dome A Site-Testing Observatory : instrumentation and first results

The PLATeau Observatory (PLATO) is an automated self-powered astrophysical observatory that was deployed to Dome A, the highest point on the Antarctic plateau, in 2008 January. PLATO consists of a suite of site-testing instruments designed to quantify the benefits of the Dome A site for astronomy, and science instruments designed to take advantage of the unique observing conditions. Instruments include CSTAR, an array of optical telescopes for transient astronomy; Gattini, an instrument to measure the optical sky brightness and cloud cover statistics; DASLE, an experiment to measure the statistics of the meteorological conditions within the near-surface layer; Pre-HEAT, a submillimeter tipping radiometer measuring the atmospheric transmission and water vapor content and performing spectral line imaging of the Galactic plane; and Snodar, an acoustic radar designed to measure turbulence within the near-surface layer. PLATO has run completely unattended and collected data throughout the winter 2008 season. Here we present a detailed description of the PLATO instrument suite and preliminary results obtained from the first season of operation

Force-Control for the Automated Footwear Testing System

The Automated Footwear Testing System (AFTS) is a robotic system designed to replicated the movement and loading of a shoe as it contacts the ground during common human movements. By doing so, the AFTS can serve as a system for the functional testing of different footwear designs in a manner that is difficult to achieve by standard testing systems. The AFTS consists of four main components: a robotic Stewart platform, a rigid fixed frame, a load cell and a prosthetic foot. Motion of the foot relative to the ground is created by rigidly fixing the foot to the frame and moving the platform relative to the foot. The Stewart platform has six degrees of kinematic freedom and can reproduce the required complex three-dimensional motion path within the limitations of its range of motion. While the platform is in contact with the footwear, the six-axis load cell measures the three-dimensional forces and moments acting on the prosthetic foot. For the AFTS, a movement path is specified, translated into platform coordinates and executed on the machine. During the execution, the load cell measures the forces and moments that act on the prosthetic foot. We wish to find the particular movement path of the Stewart platform that will generate the target force profile. Thus, we are interested in solving an inverse problem. The main goal of the workshop was to investigate potential solution methods for this ‘force-control’ problem, including looking into its feasibility

Performance Boundary Identification for the Evaluation of Automated Vehicles using Gaussian Process Classification

Safety is an essential aspect in the facilitation of automated vehicle deployment. Current testing practices are not enough, and going beyond them leads to infeasible testing requirements, such as needing to drive billions of kilometres on public roads. Automated vehicles are exposed to an indefinite number of scenarios. Handling of the most challenging scenarios should be tested, which leads to the question of how such corner cases can be determined. We propose an approach to identify the performance boundary, where these corner cases are located, using Gaussian Process Classification. We also demonstrate the classification on an exemplary traffic jam approach scenario, showing that it is feasible and would lead to more efficient testing practices.Comment: 6 pages, 5 figures, accepted at 2019 IEEE Intelligent Transportation Systems Conference - ITSC 2019, Auckland, New Zealand, October 201

Using formal methods to support testing

Formal methods and testing are two important approaches that assist in the development of high quality software. While traditionally these approaches have been seen as rivals, in recent years a new consensus has developed in which they are seen as complementary. This article reviews the state of the art regarding ways in which the presence of a formal specification can be used to assist testing