Novel Fuzzy MCDM Model for Comparison of Programming Languages

In the last twenty years, a large number of new programming languages have emerged, along with the modernization and evolution of existing ones. The selection of an appropriate programming language to solve a specific problem is often a topic of debate among university professors and programmers. The development of new programming languages is also influenced by advancements in computer hardware, communication, and measurement equipment. This paper aims to explore methods for qualitative comparison of different programming languages. A comparative analysis is presented among four programming languages: VisualBasic, C++, Python, and VEEPro. A new extension of OPARA (Objective Pairwise Adjusted Ratio Analysis) was created for ranking programming languages, while the IMF SWARA (Improved Fuzzy Stepwise Weight Assessment Ratio Analysis) was used to determine the importance of 10 criteria. Since this involves group decision-making with the participation of 20 experts, their preferences were averaged using the Bonferroni operator. The results of the created model show that C++ is the programming language with the best performance among the set of considered alternatives and criteria. To validate the model, verification analyses were defined, confirming the initial results.