No abstract

This article describes approaches to the use of scenarios in the automation of applied tasks within the framework of working with a software complex of optical modeling and photorealistic computer graphics. Optical modeling complex should include support for scripting, since conventional tools, such as those provided using a graphical user interface, are usually not enough to perform a variety of tasks that arise in practice. A brief overview of existing solutions is made. Methods are proposed that ensure effective bringing of scenario support into an existing optical modeling system. These methods provide full access from scripts to system modules, including computational modules, various simulator modules, etc. Both trivial scripts containing ordinary command sequences and more complex ones using the capabilities of high-level scripting languages such as Python are supported. Separately, a special high-level API is considered which is used for the interaction between of scripts written in the Python language and the optical modeling system. This API can also be used to extend the capabilities of the system with new parametric objects. The specialized software modules integrated into the optical modeling system, such as the batch interpreter, script interpreter and editor, extension class editor, are considered in detail. Examples of scenario-based modeling automation are given.

Аннотация. В статье описаны технологии автоматического тестирования программного обеспечения применительно к промышленным системам компьютерной графики и оптического моделирования. Автоматизация тестирования становится жизненно необходимой в условиях ограниченности ресурсов при частом выпуске версий, которые нередко возникают у производителей программного продукта. Представлены как методы регрессионного тестирования вычислительного ядра таких комплексов, так и способы тестирования пользовательского интерфейса. Для регрессионного тестирования используется механизм сценариев на языке Python. Рассмотрены методы его распараллеливания, которые позволяют значительно сократить время тестирования. Поскольку в оптическом моделировании широко применяются стохастические методы, результаты расчетов могут отличаться, что осложняет регрессионное тестирование. В этом случае предлагается применять некоторый порог при сравнении результатов. Автоматизированные тесты для тестирования пользовательского интерфейса разработаны на основе инструмента AutoIt. Отдельно описаны подходы к тестированию пользовательского интерфейса систем, реализованных в виде дополнений (plug-in) к существующим комплексам автоматизации проектирования, исходный код которых закрыт и недоступен для авторов автоматических тестов. Ключевые слова: тестирование ПО; автоматическое тестирование; компьютерная графика; моделирование освещенности; надежность программного продукта.

Nowadays, scripting is becoming a basic functionality in a very large number of different applications. This paper considers the experience of expanding the program capabilities of the optical modeling system using the Python scripting language. A brief overview of existing solutions is discussed. The approach based on the method of using the unified entity interface is proposed, which makes the process of expansion of the system simple and convenient for both its developers and end users. The new program modules like script interpreter,script editor and built-in parametric object libraries have been designed and integrated into the optical modeling system to work with scenarios are considered in detail. Software extension mechanism by means of adding new script-based object classes is provided. Examples of using Python API for a number of simple operations and examples of work with some simulation and automation modules based on scenarios are considered.

Bidirectional stochastic ray tracing with photon maps is a powerful method but suffers from noise. It can be reduced by the Multiple Importance Sampling which combines results of different “strategies”. The “optimal weights” minimize the noise functional thus providing the best quality of the results. In the paper we derive and solve the system of integral equations that determine the optimal weights. It has several qualitative differences from the previously investigated case of mixing two strategies, but further increase of their number beyond 3 retains the qualitative features of the system. It can be solved in a closed form i.e. as an algebraic formula that include several integrals of the known functions that can be calculated in ray tracing.