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A professional Full Stack developer with extensive experience in creating websites and web applications. Specialization in JavaScript is complemented by a strong proficiency in ReactJS, Typescript, Styled Components, and Material-UI. Demonstrated capability extends to utilizing NextJS and Tailwind CSS, along with constructing APIs using Laravel, underscoring comprehensive Full Stack development expertise.

Computer Science graduate with a specialization in Artificial Intelligence and extensive experience in software development, engineering, and technology instruction. Currently holds the position of Mid-Level Backend Developer within a Data Science unit at a Fintech company. Proficient in programming languages such as Python, C++, Java, and JavaScript, and well-versed in utilizing technologies that include messaging systems, SQL, NoSQL, software architecture, design patterns, and cloud computing. Adopts a flexible approach to technology selection, recognizing that each tool offers distinct benefits and drawbacks depending on specific scenarios, and remains open to backend development opportunities across various sectors.

Back-end Programmer with over four years of experience in system development and data manipulation, proficient in GO, SQL and NoSQL databases, .NET, and C#. Demonstrates a strong enthusiasm for technology and its potential to transform the digital landscape. Recognized for a deep passion for science, a proactive approach, and exceptional self-teaching capabilities.

Software Developer specializing in Ruby on Rails, with extensive practical experience in Test-Driven Development. Proficient in using Git for version control and GitHub for repository management, operating in Linux production environments. Demonstrates expertise in maintaining code quality with tools like Rubocop and managing continuous integration and deployment through Semaphore. Skilled in both functional and unit testing, with a strong understanding of database management using MySQL. Adept at API testing with Postman and comprehensive testing using Capybara and RSpec. Proficiency in managing message queuing services with Amazon SQS and Resque, deploying applications using AWS, and containerization with Docker.

Full-stack developer specializing in e-commerce and ERP systems with a robust understanding of multiple programming languages, including Javascript, Typescript, and Java, alongside foundational knowledge in Python. Proficient in various technologies such as React.js, Next.js, Vue.js, Nuxt.js, GraphQL, Node.js, and NestJS. Additionally experienced with the Spring framework, PostgreSQL, MongoDB, and proficient in using git for version control. Familiarity with CI/CD practices ensures seamless integration and deployment processes, while the use of Linters supports code quality assurance. Also adept at using Figma for design interface planning, with an introductory understanding of Django. Employs agile methodologies in combination with clean code principles and Atomic Design to optimize development efficiency and elevate product quality.

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Software developer since 2021, specializing in creating and managing web systems using React, Angular, and Node technologies. Proficient in crafting user-centered applications with a strong adherence to agile methodologies throughout the development process.

Program Composition Notation (PCN) is a parallel programming language designed to facilitate the composition of programs from existing components. It provides constructs for defining and combining processes, enabling the development of concurrent applications by specifying how individual processes interact and communicate.

A Program Composition Notation expert must have strong skills in parallel programming, process synchronization, and inter-process communication. They should be proficient in debugging and optimizing concurrent applications, understand the underlying hardware architecture, and have experience with other parallel programming tools and libraries like MPI or PVM.

How to hire a Program Composition Notation expert

Program Composition Notation (PCN) was developed in the late 1980s to early 1990s. It was designed to simplify the creation of parallel applications by allowing developers to compose programs from existing components. The language aimed to address the complexity of parallel programming by providing clear constructs for process definition and communication.

About Program Composition Notation

Strengths of Program Composition Notation included its ability to simplify the development of parallel applications and its clear constructs for process interaction. Weaknesses involved limited adoption and a steep learning curve for some developers. Competitors included other parallel programming languages such as MPI (Message Passing Interface) and PVM (Parallel Virtual Machine).

Program Composition Notation

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About Program Composition Notation

How to hire a Program Composition Notation expert

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