An Effective Approach to Test Suite Reduction and Fault Detection Using Data Mining Techniques

Software testing is used to find bugs in the software to provide a quality product to the end users. Test suites are used to detect failures in software but it may be redundant and it takes a lot of time for the execution of software. In this article, an enormous number of test cases are created using combinatorial test design algorithms. Attribute reduction is an important preprocessing task in data mining. Attributes are selected by removing all weak and irrelevant attributes to reduce complexity in data mining. After preprocessing, it is not necessary to test the software with every combination of test cases, since the test cases are large and redundant, the healthier test cases are identified using a data mining techniques algorithm. This is healthier and the final test suite will identify the defects in the software, it will provide better coverage analysis and reduces execution time on the software.

Comparison of Prediction Programs for Short Wave Circuit Link from Iraq to Test points on Both Earth Hemispheres during Solar Minimum

This paper compare the accurecy of HF propagation prediction programs for HF circuits links between Iraq and different points world wide during August 2018 when solar cycle 24 (start 2009 end 2020) is at minimun activity and also find out the best communication mode used. The prediction programs like Voice of America Coverage Analysis Program (VOACAP) and ITU Recommendation RS 533 (REC533 ) had been used to generat HF circuit link parameters like Maximum Usable Frequency ( MUF) and Frequency of Transsmision (FOT) .Depending on the predicted parameters (data) , real radio contacts had been done using a radio transceiver from Icom model IC 7100 with 100W RF power, tuner box and homemade dipole antenna of 10 m length and 8m height above ground. From correlation between the predicted data and observed data the result was not accurate .

eXNVerify: coverage analysis for long and short-read sequencing data in clinical context

Accurate identification of genetic variants to a large extent is based on type of experimental technology, quality of the material and coverage of obtained sequencing data. Our motivation was to create a tool that will evaluate genome coverage and accelerate the introduction of long-read sequencing to medical diagnostics and clinical practice. Here we present eXNVerify: a tool for inspection of clinical data in the context of pathogenic variants. The tool calculates Clinical Depth Coverage – a measure of coverage which we introduce to evaluate loci with pathogenic germline and somatic variants reported in ClinVar. The tool additionally provides visualization options for user-defined genes of interest. Finally, we present an examples of BRCA1, TP53, CFTR application and results of a test conducted in the Extensive Sequence Dataset of Gold-Standard Samples for Benchmarking and Development.

Guagingof key performance indicators for 2G mobile networks in Calabar, Nigeria

The increase in the number of mobile subscribers, coupled with the increase in mobile services is enough reason to monitor the QoS of mobile network operators frequently. This work looks into the QoS of network operators in Calabar, Nigeria, taking into consideration some KPIs ((CSSR, DCR, CST, HOSR, and network quality and network coverage). Analysis of data obtained after a benchmarking drive test shows that Globacom network was within NCC performance threshold for all network KPIs monitored. Also, MTN network performed poorly in HOSR but met the minimum benchmark in other network KPIs. Airtel network failed in the required DCR benchmark but was within the minimum benchmark for other KPIs while 9mobile failed in CSSR and DCR performance threshold but met the performance threshold for other KPIs. This result will be useful to the regulatory body, NCC, those in academic, RF engineers, network subscribers and especially, the network operators which we expect, will optimize their networks immediately.