Тести в СОАС та СААС

A simulator of test tasks in law for high-quality preparation for the competition for vacant positions of judges of the Specialized District Administrative Court and the Specialized Administrative Court of Appeal

Official tests in SOAS and SAAS include the following structural blocks for preparing for testing in law:
1. General knowledge in the field of law (1000 questions)
2. Questions on specialization for the Specialized District Administrative Court (1000 questions)
3. Questions on specialization for the Specialized Administrative Court of Appeal (1100 questions)

The questions are formed on the basis of official questions and answers published by the HQCJ on 03/23/2026. The test tasks used in the application are officially approved by the HQCJ and publicly available questions for candidates for judges of the Specialized District Administrative Court and the Specialized Administrative Court of Appeal

The application is a private development and is not related to the official state body - the High Qualification Commission of Judges. The developer is not responsible for the completeness and correctness of the test tasks published by the HQCJ, as well as for the relevance of the officially formed answers

You can take the tests and study the questions in full, in parts by groups of questions, in parts from random questions, in the form of working on errors on questions in which an error was made, as well as by repeating the studied questions. The answer options are shuffled each time you take the test to ensure high efficiency in memorizing answers and preventing guessing. The application controls the process of studying and memorizing each question, allows you to choose the degree of memorization and track the full progress of studying questions

The application has a special intelligent mode of automatic study of questions, in which the program itself selects questions for training, taking into account the results of the user's previous tests, ensuring the most efficient study process and optimizing repetitions