The process of software testing is of utmost importance and requires a major allocation of resources. It has a substantial influence on the quality and dependability of software products. Nevertheless, as the quantity of test cases escalates, the feasibility of executing all of them diminishes, and the accompanying expenses related to preparation, execution time, and upkeep grow excessively exorbitant. The objective of Test Redundancy Reduction (TRR) is to mitigate this issue by determining a minimal subset of the test suite that satisfies all the requirements of the primary test suite while lowering the number of test cases. In order to attain this objective, multiple methodologies have been suggested, encompassing heuristics, meta-heuristics, exact algorithms, hybrid approaches, and machine-learning techniques. This work provides a thorough examination of prior research on TRR, addressing deficiencies and making a valuable contribution to the current scholarly understanding. The literature study encompasses a comprehensive examination of the complete chronology of TRR, incorporating all pertinent scholarly articles and practitioner-authored research papers published in English. This study aims to provide managers with valuable insights into the strengths and shortcomings of different TRR methodologies, enabling them to make well-informed decisions regarding the most appropriate approach for their specific needs. The primary objective of this study is to offer a comprehensive analysis of Test Result Reduction (TRR) and its consequential impact on mitigating expenses related to software testing. This study makes a valuable contribution to extant literature by elucidating the present state-of-the-art and delineating potential avenues for future research.

An exhausted testing is one of the testing strategy that need more time taken due to test the whole test cases in the Software Under Test. Many techniques have been proposed to avoid this situation because the size of the Software Under Test is vary and need to have good testing strategy performance. One of the techniques is Adaptive Random Testing (ART). The ART is one of the enhanced random testing. Due to ART performance is better than pure random testing, it becomes motivation to implement the ART in Aspect Oriented Program (AOP). The ART and random testing are similar in which is selection the first test case with random manner. But, ART add another one characteristic which is the evenness test in domain area. Due to similar for first test case, we proposed a new strategy called StART. In StART, we use statistical testing technique to get the information before we test. This process we named it as code profiling. This code profiling helps in selection first test case in this technique. The result from this phase shows the area that we need to select for test activity.

Test case selection in software testing is one of the process that support to quality in finding bug. Decreasing number of bug may increase quality of software. Many strategies have been proposed by researcher for software testing. Specially to avoid exhausted testing which all the testers take into account which may increase time and performance. One of the strategy is StART. The code profiling is a part of StART, which is a selection test cases strategy using code profiling. The strategy is based on the adaptive random testing and support with code profiling in the strategy. The aim of this paper is to show the code profiling model. The selection of domain area to test is based on the highest probability in the code profiling result. The probability of in the code profiling is calculated and the highest value to be chosen as the first area to test. The value to be chosen as a domain area for the first to be tested in SUT. This model used AspectJ as case study to show the model can be implemented for a new programming paradigm. Tetris selected as case study to show the model flow. From the case study of Tetris, the model shows the area to be tested first is in the package Gui, for aspect menu and advice after the probability value shows the highest result. For future study, this model need to test their efficiency of their strategy.

Nowadays, many organizations deploy the database application systems in order to manage their business operation. Administrations is required to deliver up to date data to users who live distantly, thus replicated databases can be one solution to increase the business operations performance in the distributed environment. Even though data availability is increased, common existing replication strategies neglect the correlation among the different data files in a Distributed Database Systems. In this paper, Binary Vote Assignment on Grid Quorum with Association Rules (BVAGQ-AR) has been proposed to manage the database replication. This technique combines data replication and data mining approaches in order to decrease the job processing time. The result shows that BVAGQ-AR has the lowest job processing time compared to other techniques. BVAGQ-AR performs 66.548 ms to complete a transaction compared to BRS with 137.157 ms, HRS with 257.928 ms, and ROWA with 262.243 ms. From the results, it is proved that managing replication and transaction through the proposed BVAGQ-AR able to preserve data consistency with low job processing time.

This study focuses on quality in a view of usability on website for Down Syndrome Children (DSC). The website specially designed for children with Down Syndrome to gain benefit and to learn how easy to use the website. This study wants to know how easy of exist website which are focus on DSC and really easy to use with using usability principles: learnability, efficiency, memorability, errors and satisfaction. The usability principles used to evaluate the website. The result shows that the website applies usability approach successfully through games which resembles learning material in it for children with Down Syndrome to learn.