Regression testing is a part of the software testing activity, which is an important activity of ... more Regression testing is a part of the software testing activity, which is an important activity of the software development life cycle and the maintenance process. It is carried out to ensure that changes made in the fixes or any enhancement changes are not influencing the previously working functionality. Regression testing is mostly done by re-running existing test cases against the modified code to determine whether the changes affect anything. This requires a lot of cost and time, which increases as the size and the complexity of the software increases. Instead of re-running all the test cases, a number of different approaches were studied to solve regression-testing problems. There has been an explosion in the use of data mining techniques in the exploration and analysis of large quantities of data in order to discover meaningful patterns and rules. Data mining models were introduced for software testing to design a minimal set of regression tests. This helps solving regression t...
Enormous heterogeneous sensory data are generated in the Internet of Things (IoT) for various app... more Enormous heterogeneous sensory data are generated in the Internet of Things (IoT) for various applications. These big data are characterized by additional features related to IoT, including trustworthiness, timing and spatial features. This reveals more perspectives to consider while processing, posing vast challenges to traditional data fusion methods at different fusion levels for collection and analysis. In this paper, an IoT-based spatiotemporal data fusion (STDF) approach for low-level data in–data out fusion is proposed for real-time spatial IoT source aggregation. It grants optimum performance through leveraging traditional data fusion methods based on big data analytics while exclusively maintaining the data expiry, trustworthiness and spatial and temporal IoT data perspectives, in addition to the volume and velocity. It applies cluster sampling for data reduction upon data acquisition from all IoT sources. For each source, it utilizes a combination of k-means clustering for...
Regression testing is a part of the software testing activity, which is an important activity of ... more Regression testing is a part of the software testing activity, which is an important activity of the software development life cycle and the maintenance process. It is carried out to ensure that changes made in the fixes or any enhancement changes are not influencing the previously working functionality. Regression testing is mostly done by re-running existing test cases against the modified code to determine whether the changes affect anything. This requires a lot of cost and time, which increases as the size and the complexity of the software increases. Instead of re-running all the test cases, a number of different approaches were studied to solve regression-testing problems. There has been an explosion in the use of data mining techniques in the exploration and analysis of large quantities of data in order to discover meaningful patterns and rules. Data mining models were introduced for software testing to design a minimal set of regression tests. This helps solving regression t...
Enormous heterogeneous sensory data are generated in the Internet of Things (IoT) for various app... more Enormous heterogeneous sensory data are generated in the Internet of Things (IoT) for various applications. These big data are characterized by additional features related to IoT, including trustworthiness, timing and spatial features. This reveals more perspectives to consider while processing, posing vast challenges to traditional data fusion methods at different fusion levels for collection and analysis. In this paper, an IoT-based spatiotemporal data fusion (STDF) approach for low-level data in–data out fusion is proposed for real-time spatial IoT source aggregation. It grants optimum performance through leveraging traditional data fusion methods based on big data analytics while exclusively maintaining the data expiry, trustworthiness and spatial and temporal IoT data perspectives, in addition to the volume and velocity. It applies cluster sampling for data reduction upon data acquisition from all IoT sources. For each source, it utilizes a combination of k-means clustering for...
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