使用价值分析值分析应用程序上的黑盒测试

Endar Nirmala, Yulianti Yulianti, Aqidatul Izzah Chairul, Ajeng Rohmatun Nazilah, Ricky Nur Oktavianto, Khairani Fadhilla
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引用次数: 0

摘要

国家统考是国家对教育家长进行评估的基准,是学生毕业的先决条件。在参加国家考试之前,学生参加一个试考,作为实际国家考试之前的基准。毕业数据的使用还不够现实和最大化。对于不知道是否通过的学生来说,这是相当困难的。为了预测通过阈值,可以利用现有数据,特别是完井数据来预测完井率。由于数据量大,需要一个时间段来预测,所以我们需要一个可以延长学生毕业阶段预估周期的系统。本研究描述了使用黑盒法对通过国家考试的预测应用程序进行测试。黑箱法包括分割等效、极限分析、比较检验、抽样检验、稳健性检验等几种方法。在这些检验中,本研究选择边际分析检验方法。边际分析是确定待测数据的基本边界和上限的测试过程。该测试使用添加到国家考试通过预测应用程序中的类功能运行。该测试的结果表明,在验证数据时存在许多弱点,数据库中存储的数据与期望的数据不匹配。该测试的结果可以作为改进应用程序的建议或证据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Pengujian Blackbox pada Aplikasi Prediksi Kelulusan Ujian Nasional (UN) Menggunakan Metode Boundary Value Analysis
The national exam is a benchmark for assessment carried out in the country for the parent of Education, which is used as a prerequisite for student graduation. Before taking the national exam, students take a trial exam which is used as a benchmark before the actual national exam. The use of graduation data is not yet realistic and maximum. This is quite difficult for students who are not known to have passed. In order to predict the pass threshold, it is possible to utilize existing data, especially completion data, to predict the completion rate. Due to the large amount of data, it requires a period to predict, so we need a system that can extend the estimated period of the student's graduation phase. This study describes the testing of prediction applications for passing the National Examination while using the black box method. The black box method consists of several methods, including splitting equivalence, limit analysis, comparison testing, sampling testing, robustness testing, and others. Among these tests, the marginal analysis test method was chosen for this study. Marginal analysis is a test procedure that determines the basic and upper bounds of the data to be tested. This test is run using the class feature added to the National Examination Pass Prediction application. The results of this test indicate that there are many weaknesses in validating the data and the data stored in the database does not match the desired data. The results of this test can be used as suggestions or evidence for application improvement.
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