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Polyglot developers can tackle all IoT code issues
IoT code and romance languages are similar: Once you know one, you can pick up parts of others. Development teams can benefit from code generalists and specialists.
Developers are like linguists. Some know multiple languages, whereas others specialize in one. These technical linguists are highly sought after when they know multiple programming languages, especially in organizations considering integrating IoT.
IoT uses a variety of software languages and sensors, so a developer must write IoT code that is compatible with and relevant to multiple versions, products and devices. It is beneficial for developers to know the ins and outs of one specific coding language. Knowing how to code for a variety of hardware components and use cases helps in the long run, too.
What languages work best for IoT?
Most developers are proficient in one language, but those with experience can often identify similar coding across other software languages, such as Java, Python, C, C++, Ruby on Rails and R.
In IoT, Java, C++ and Go are the preferred programming languages. Go is beneficial for communications related to data streams. It requires little processing capability and is speedy to learn. Java is object-oriented, has comprehensive code and uses bytecode, which offers an extra layer of security. C++ offers portability to run the code on different OSes, is object-oriented and has memory management control.
The technology stack also plays an important role in what coding languages developers should know for IoT software programming. The sensors, actuators, IoT gateways and the IoT software all have their own requirements, but there must also be a common language or protocol that makes everything work together.
Developers must also meet application requirements. The technology stack includes code, APIs, libraries and software that all focus on the IoT device's ability to scale within a deployment, respond to required maintenance and scale up data applications; the right code ensures all these software parts run together and scale smoothly.
Specialization has its benefits
There are benefits of being proficient in one language. In any field, professionals turn to the subject matter experts -- those proficient in their field of study.
In software development, teams benefit from having a code subject matter expert. With advanced expertise in one code language, developers can more easily address legacy and third-party code issues and understand how a specific code language best supports different device types.
With deeper knowledge of a specific coding language, the developer may also know multiple ways to code a specific function, understand the limitations of what code can do within an IoT product or determine the most efficient way to write a specific piece of code.
The drawback to code specialization is that the developer might not know how to code for certain components of the IoT technology stack. They might be unaware of how to address code interoperability, or they might code a feature in a way only they can decipher.
Multiple coding languages meet IoT diversity
IoT device design is a booming field with many types of devices. With such a variety of offerings, developers might use different code languages to design, manage or troubleshoot devices.
Certain devices might require the use of a distinct programming language and there are compatibility issues between manufacturers. Knowing more than one language can help the developer create connections to increase interoperability between the IoT device's hardware and software.
The benefits of knowing multiple coding languages include more diverse feature integration as different coding languages support certain features; reduced points of failure with multiple safety features in different code types; and increased developer knowledge about the overall IoT technology stack.
If a developer knows multiple coding languages on a minimal level, they might only know basic commands for a certain language; have issues coding features depending on a language's learning curve; or introduce errors during the coding process.
