The test case prioritization (TCP) problem is defined as determining an execution order of test cases so that important tests are executed early. Different metrics have been proposed to measure importance of test cases. While coverage and fault-detection based measures have benefits and have been used in a lot of studies, mutation kill-based measures have emerged in TCP recently, since they have benefits addressing issues with other approaches. Moreover, in the TCP problem, finding the optimal solution has a complexity of the factorial of the number of test cases, making meta-heuristic algorithms a highly suitable approach. In this study, we propose an end-to-end pipeline for TCP, Mutation Kill-based Evolutionary Algorithm (MuKEA-TCP), which allows users to have fast and efficient TCP results from existing source code, or directly from the mutant kill report of a system, without the need for any coverage information or real faults. An evolutionary algorithm utilizing Average Percentage Mutant Killed (APMK) as the objective function augmented with a local search procedure enhancing is used in MuKEA-TCP. We performed our case study on five open-source Java projects, in which we compared the APMK values of the final TCP results of some well-known greedy algorithms, and MuKEA-TCP using different initialization methods. Our results have shown that providing additional method as an initial input to the proposed augmented evolutionary algorithm has improved the results and outperformed other methods for our case study. Findings of this study have shown that using an evolutionary algorithm augmented with local search with mutation kill-based APMK as the objective function enhances the commonly used greedy prioritization methods, with a minor execution time trade-off.

RTip is a tool to quantify plant root growth velocity using high resolution microscopy image sequences at sub-pixel accuracy. The fully automated RTip tracker is designed for high-throughput analysis of plant phenotyping experiments with episodic perturbations. RTip is able to auto-skip past these manual intervention perturbation activity, i.e. when the root tip is not under the microscope, image is distorted or blurred. RTip provides the most accurate root growth velocity results with the lowest variance (i.e. localization jitter) compared to six tracking algorithms including the top performing unsupervised Discriminative Correlation Filter Tracker and the Deeper and Wider Siamese Network. RTip is the only tracker that is able to automatically detect and recover from (occlusion-like) varying duration perturbation events.