Abstract: Optimization is an important tool in making decisions and in analysing physical systems. In mathematical terms, an optimization problem is the problem of finding the best solution from among the set of all feasible solutions. The paper discusses the Whale Optimization Algorithm (WOA), and its applications in different fields. The algorithm is tested using MATLAB because of its unique and powerful features. The benchmark functions used in WOA algorithm are grouped as: unimodal (F1-F7), multimodal (F8-F13), and fixed-dimension multimodal (F14-F23). Out of these benchmark functions, we show the experimental results for F7, F11, and F19 for different number of iterations. The search space and objective space for the selected function are drawn, and finally, the best solution as well as the best optimal value of the objective function found by WOA is presented. The algorithmic results demonstrate that the WOA performs better than the state-of-the-art meta-heuristic and conventional algorithms.
Abstract: This paper proposes a new technique for improving
the efficiency of software testing, which is based on a conventional
attempt to reduce test cases that have to be tested for any given
software. The approach utilizes the advantage of Regression Testing
where fewer test cases would lessen time consumption of the testing
as a whole. The technique also offers a means to perform test case
generation automatically. Compared to one of the techniques in the
literature where the tester has no option but to perform the test case
generation manually, the proposed technique provides a better
option. As for the test cases reduction, the technique uses simple
algebraic conditions to assign fixed values to variables (Maximum,
minimum and constant variables). By doing this, the variables values
would be limited within a definite range, resulting in fewer numbers
of possible test cases to process. The technique can also be used in
program loops and arrays.