By Poliakova Ksenia (kapoliakova@edu.hse.ru)
Design Patterns are tested within quite long period of time and also they are proven solutions to common problems encountered in software development. They are a kind of “building blocks” for creating flexible, scalable and maintainable systems. However, before a design pattern is considered to be useful and applicable in practice, it must undergo rigorous validation. Validation, in this context, is the process of assessing the pattern’s compliance with its stated goals and its suitability for use in real-world conditions. The talk will cover in detail two key aspects of design pattern validation: experimental and industrial validation.
Design patterns are reusable solutions to common design problems. They describe how to properly organize code so that it becomes more flexible, modular, and scalable. Some examples of the most popular design patterns: Singleton, Factory, Observer, Strategy, etc. [2].
Validation Goals:
Experimental validation is the process of evaluating design patterns under controlled conditions using specially designed experiments. The main goal is to obtain quantitative and qualitative data on the effectiveness of the template, its performance, flexibility and other important characteristics [3].
Goals of experimental validation
Experimental validation methods
Experimental validation begins with a clear definition of the experimental objectives, defining what exactly needs to be tested. Then test rig is created, including the necessary hardware, software, and test data, forming a controlled environment for conducting experiments. After that test scenarios are developed, defining a set of tests designed to validate the template. During the experimentation phase, these tests are executed and the resulting data is carefully collected. Finally, an analysis of the results is carried out, including processing and interpretation of the collected data, as well as comparison with the results of a control group (if any) to obtain objective conclusions about the functioning and effectiveness of the tested template.
Industrial validation is the process of evaluating design patterns in real conditions, on real projects, and with the participation of real developers. It allows you to evaluate the applicability of the pattern in practice and its impact on the efficiency of team development.
Goals of industrial validation:
Industrial validation methods.
Industrial validation process In the context of the study of the implementation of a development pattern, the key stage is the selection of a real project on which testing and integration will be carried out [5]. After the project is selected, the pattern is directly implemented, accompanied by training developers in its use to ensure effective application. This is followed by data collection, including observation of the development process, receiving feedback from developers and measuring key project metrics, which allows us to assess the impact of the pattern on work processes. The collected data is analyzed and interpreted to identify patterns and trends, after which conclusions are drawn about the applicability of the pattern in real conditions, as well as its advantages and disadvantages identified during practical application.
Validation of design patterns is an integral part of the software development process to ensure their effectiveness and applicability. Experimental validation provides quantitative data on the effectiveness of a pattern under controlled conditions, while industrial validation evaluates its applicability in real projects [3]. Both types of validation are important to form a complete and comprehensive understanding of the advantages, disadvantages, and limitations of using design patterns [1]. A combination of experimental and industrial validation is the most effective approach to verifying design patterns. The results of validation help developers choose the most appropriate patterns to solve specific problems and improve the quality of software.
Experimental and industrial validation of design patterns are two complementary processes that provide a comprehensive assessment of their effectiveness and applicability. Experimental validation provides quantitative data under controlled conditions, while industrial validation provides an understanding of the real context and impact of the pattern on software development. Taken together, these methods allow choosing the best solutions for building reliable, flexible and scalable systems, which is an important factor in modern development.
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