An Automated Testing Approach For Pxi Chassis Software Driver

PXI chassis is a multi-vendor interoperable device, it can interconnect with many chassis, module and computer type. To make sure the device driver is able to function in specific configuration it must go through a series of testing. The complexity of PXI software testing has increased when it need to cover multiple configuration for single driver. Majority of the automated test system will execute test without have a mechanism to verify the test environment. The current trend of automated software test only execute on single test configuration, to improve the PXI chassis IVI driver test duration a test software with the capability of execute multi test configuration is developed. In order to develop this tool, a server-client concept is adopted. The advantage of server-client is to centralize the testing when multiple test system perform test at same time. The software tool client will start once completely boot in to operating system, the test system will connect to server and wait for further action from server. When server detected incoming client connection it will automatically verify and fix the testing environment, if the client fulfilled the test suite requirement it will start execute test. All clients test summary result will be feedbacked to server. The results show an average of 17.1% test duration reduction on the planned test configuration when the automated software tool applied on testing. Besides that the results suggest that execute the test on higher controller hardware performance can reduce the test duration as well

Z39.50 broadcast searching and Z-server response times: perspectives from CC-interop

This paper begins by briefly outlining the evolution of Z39.50 and the current trends, including the work of the JISC CC-interop project. The research crux of the paper focuses on an investigation conducted with respect to testing Z39.50 server (Z-server) response times in a broadcast (parallel) searching environment. Customised software was configured to broadcast a search to all test Z-servers once an hour, for eleven weeks. The results were logged for analysis. Most Z-servers responded rapidly. 'Network congestion' and local OPAC usage were not found to significantly influence Z-server performance. Response time issues encountered by implementers may be the result of non-response by the Z-server and how Z-client software deals with this. The influence of 'quick and dirty' Z39.50 implementations is also identified as a potential cause of slow broadcast searching. The paper indicates various areas for further research, including setting shorter time-outs and greater end-user behavioural research to ascertain user requirements in this area. The influence more complex searches, such as Boolean, have on response times and suboptimal Z39.50 implementations are also emphasised for further study. This paper informs the LIS research community and has practical implications for those establishing Z39.50 based distributed systems, as well as those in the Web Services community. The paper challenges popular LIS opinion that Z39.50 is inherently sluggish and thus unsuitable for the demands of the modern user

Software test automation : a design and tool selection approach for a heterogeneous environment

textThis report describes a design approach for implementing a software test automation solution that can accommodate existing test processes in an organization. The process of implementing a software test automation solution is a large undertaking and requires careful planning to avoid unsuccessful implementations. This report outlines a design that can integrate with existing business and development processes in an organization, and recommends automation and development frameworks for achieving the test automation goals. Considerations for a heterogeneous test environment with varying types of supported operating systems, such as Windows and Linux, and multiple test execution environments, such as Java and .NET, have been made in this design and in the tool selections for the system implementation. The report also describes some of the challenges and caveats of automation in a heterogeneous environment along with recommended solutions to these challenges.Electrical and Computer Engineerin

Online cooperation learning environment : a thesis presented in partial fulfillment of the requirements for the degree of Master of Science in Computer Science at Massey University, Albany, New Zealand

This project aims to create an online cooperation learning environment for students who study the same paper. Firstly, the whole class will be divided into several tutorial peer groups. One tutorial group includes five to seven students. The students can discuss with each other in the same study group, which is assigned by the lecturer. This is achieved via an online cooperation learning environment application (OCLE), which consists of a web based J2EE application and a peer to peer (P2P) java application, cooperative learning tool (CLT). It can reduce web server traffic significantly during online tutorial discussion time

DiPerF: an automated DIstributed PERformance testing Framework

We present DiPerF, a distributed performance testing framework, aimed at simplifying and automating service performance evaluation. DiPerF coordinates a pool of machines that test a target service, collects and aggregates performance metrics, and generates performance statistics. The aggregate data collected provide information on service throughput, on service "fairness" when serving multiple clients concurrently, and on the impact of network latency on service performance. Furthermore, using this data, it is possible to build predictive models that estimate a service performance given the service load. We have tested DiPerF on 100+ machines on two testbeds, Grid3 and PlanetLab, and explored the performance of job submission services (pre WS GRAM and WS GRAM) included with Globus Toolkit 3.2.Comment: 8 pages, 8 figures, will appear in IEEE/ACM Grid2004, November 200

Client Selection for Federated Learning with Heterogeneous Resources in Mobile Edge

We envision a mobile edge computing (MEC) framework for machine learning (ML) technologies, which leverages distributed client data and computation resources for training high-performance ML models while preserving client privacy. Toward this future goal, this work aims to extend Federated Learning (FL), a decentralized learning framework that enables privacy-preserving training of models, to work with heterogeneous clients in a practical cellular network. The FL protocol iteratively asks random clients to download a trainable model from a server, update it with own data, and upload the updated model to the server, while asking the server to aggregate multiple client updates to further improve the model. While clients in this protocol are free from disclosing own private data, the overall training process can become inefficient when some clients are with limited computational resources (i.e. requiring longer update time) or under poor wireless channel conditions (longer upload time). Our new FL protocol, which we refer to as FedCS, mitigates this problem and performs FL efficiently while actively managing clients based on their resource conditions. Specifically, FedCS solves a client selection problem with resource constraints, which allows the server to aggregate as many client updates as possible and to accelerate performance improvement in ML models. We conducted an experimental evaluation using publicly-available large-scale image datasets to train deep neural networks on MEC environment simulations. The experimental results show that FedCS is able to complete its training process in a significantly shorter time compared to the original FL protocol