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Difference Between FORTRAN and COBOL: When it comes to programming languages, two of the most widely used languages are Cobol and Fortran. Both of these programming languages have been around for many decades and have undergone significant changes throughout their history. While they have some similarities, there are also significant differences between Cobol and Fortran.
Difference Between COBOL and FORTRAN
In this article, we will delve into the Top 50 Differences Between FORTRAN and COBOL, highlighting the unique features and characteristics of each language. Whether you are an experienced programmer or just starting in the field, understanding the differences between Cobol and Fortran can help you choose the language that best fits your needs.
FORTRAN Vs COBOL | What is the Comparision?
Acquire an understanding of the meanings of Cobol and Fortran by referring to this section.
What is FORTRAN?
FORTRAN, which stands for FORmula TRANslation, is a high-level programming language designed for scientific and engineering applications. It was developed in the 1950s by a team of programmers at IBM led by John Backus. FORTRAN was the first widely used high-level programming language and has been a significant contributor to the development of computer science and engineering over the years. One of the main strengths of FORTRAN is its ability to perform complex mathematical calculations and scientific simulations with ease, making it ideal for scientific research, engineering, and other technical fields. Additionally, FORTRAN has undergone numerous revisions and updates over the years, with the most recent version being FORTRAN 2018, which includes several new features and improvements to the language. Overall, FORTRAN has played a vital role in the development of modern computing and remains an essential programming language for many scientific and engineering applications today.
What is COBOL?
COBOL (Common Business Oriented Language) is a high-level programming language used primarily for business applications. It was first introduced in 1959 and has since become one of the most widely used programming languages in the world. COBOL was designed to be easy to read and understand, using English-like syntax and a natural language approach to programming. Its purpose was to make programming accessible to non-technical personnel, particularly those in the business world who needed to create their own software applications. COBOL’s popularity was fueled by the rise of mainframe computers in the 1960s and 1970s, which were widely used in business environments. Today, despite being over 60 years old, COBOL remains in use by many organizations worldwide, and its importance is unlikely to diminish anytime soon.
Top 50 Differences Between FORTRAN and COBOL
Fortran and Cobol are both high-level programming languages, but they have significant differences in syntax, usage, and application, which have been explored below.
| Serial Number | Fortran | Cobol |
|---|---|---|
| 1 | Developed for scientific and engineering applications. | Developed for business applications. |
| 2 | Used for numerical and scientific computations. | Used for commercial data processing. |
| 3 | Has a simpler syntax and is easier to learn. | Has a complex syntax and is harder to learn. |
| 4 | Has a higher performance in numerical calculations. | Has a slower performance in numerical calculations. |
| 5 | Provides native support for complex numbers. | Does not provide native support for complex numbers. |
| 6 | Supports array processing efficiently. | Does not support array processing efficiently. |
| 7 | Has better support for parallel processing. | Does not have as good support for parallel processing. |
| 8 | Is easier to debug due to simpler syntax. | Is harder to debug due to complex syntax. |
| 9 | Provides better optimization options for numerical code. | Does not provide as many optimization options. |
| 10 | Has better performance in scientific and engineering | Has better performance in business and commercial |
| applications. | applications. | |
| 11 | Supports dynamic memory allocation. | Does not support dynamic memory allocation. |
| 12 | Is better suited for complex mathematical operations. | Is better suited for record-oriented data processing. |
| 13 | Has better support for scientific libraries. | Does not have as good support for scientific libraries. |
| 14 | Supports modern programming paradigms such as OOP. | Does not support modern programming paradigms such as OOP. |
| 15 | Is better suited for numerical simulation. | Is better suited for data storage and retrieval. |
| 16 | Is not as widely used as Cobol. | Is widely used in legacy systems. |
| 17 | Was initially developed in the 1950s. | Was initially developed in the late 1950s. |
| 18 | Has evolved to support modern computing architectures. | Has not evolved as much as Fortran in recent years. |
| 19 | Has better support for mathematical functions. | Does not have as good support for mathematical functions. |
| 20 | Has better support for scientific notation. | Does not have as good support for scientific notation. |
| 21 | Provides better support for floating-point arithmetic. | Does not provide as good support for floating-point arithmetic. |
| 22 | Has better support for complex data structures. | Does not have as good support for complex data structures. |
| 23 | Is used in scientific and engineering research. | Is used in business and financial applications. |
| 24 | Has a smaller set of keywords and constructs. | Has a larger set of keywords and constructs. |
| 25 | Does not provide built-in file handling features. | Provides built-in file handling features. |
| 26 | Has better support for vector processing. | Does not have as good support for vector processing. |
| 27 | Has better support for optimization of scientific code. | Does not provide as many options for optimizing code. |
| 28 | Is not as widely supported as Cobol. | Is widely supported in mainframe environments. |
| 29 | Has better support for complex algorithms. | Does not have as good support for complex algorithms. |
| 30 | Supports both procedural and functional programming. | Supports procedural programming. |
| 31 | Provides better support for scientific visualization. | Does not provide as good support for scientific visualization. |
| 32 | Is better suited for scientific computing in academia. | Is better suited for business applications in industry. |
| 33 | Has better support for mathematical modeling. | Does not have as good support for mathematical modeling. |
| 34 | Has better support for sparse matrices. | Does not have as good support for sparse matrices. |
| 35 | Is more efficient in terms of memory usage. | Is less efficient in terms of memory usage. |
| 36 | Supports both static and dynamic scoping. | Supports only static scoping. |
| 37 | Is more suitable for high-performance computing. | Is more suitable for batch processing. |
| 38 | Has better support for multi-dimensional arrays. | Does not have as good support for multi-dimensional arrays. |
| 39 | Is more popular in the scientific community. | Is more popular in the business community. |
| 40 | Is better suited for matrix operations. | Is better suited for record manipulation. |
| 41 | Has better support for parallel I/O. | Does not have as good support for parallel I/O. |
| 42 | Is more suitable for numerical analysis. | Is more suitable for data processing. |
| 43 | Supports coarrays for parallel processing. | Does not support coarrays for parallel processing. |
| 44 | Is more suitable for large-scale scientific simulations. | Is more suitable for small-scale data processing. |
| 45 | Has better support for complex numbers in matrix math. | Does not have as good support for complex numbers in matrix math. |
| 46 | Is easier to read and write for scientific applications. | Is easier to read and write for business applications. |
| 47 | Supports user-defined data types. | Supports only a few built-in data types. |
| 48 | Is better suited for matrix manipulation. | Is better suited for record-oriented data manipulation. |
| 49 | Has better support for numerical integration. | Does not have as good support for numerical integration. |
| 50 | Is more suitable for numerical modeling. | Is more suitable for data manipulation and reporting. |
Conclusion: COBOL Vs FORTRAN
The differences between FORTRAN and COBOL are significant, and choosing between the two languages depends on the specific requirements of the project. Fortran’s strength lies in its scientific and mathematical applications, while Cobol’s strength lies in its business-oriented programming features. It is essential to understand the unique characteristics of each language to make an informed decision on which one to use for a particular project. While both languages have been around for decades, they continue to evolve to meet the changing needs of the industry, making them valuable tools for programmers today.
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