Machine learning code development

Machine learning is a specialized sub-field of artificial intelligence, since its inception, machine learning has used algorithms to learn and train themselves through the study of large quantities of data. While this has been beneficial for businesses by allowing the generation of accurate solutions to business scenarios even when perfect data did not exist, machine learning is seeming to provide wider benefits in terms of software automation and code development. Machine learning is already making code more efficient: Google’s Jeff Dean has reported that 500 lines of TensorFlow code has replaced 500,000 lines of code in Google Translate. Although lines of code are a questionable metric, a thousand-fold reduction is huge: both in programming effort and in the volume of code that has to be maintained.

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The increasing complexity of software systems: Over the past decade, software complexity has seen a large rise. Most modern systems contain thousands of individual components that are connected to each other via API’s, application program interfaces; even simple tasks frequently have to be handled across a whole range of different interfaces, which does not helpingly simplify the process of software development. 

Through the use of machine learning, we will look at some examples where software development can be simplified.

How machine learning can make things easier:

  • Error detection and troubleshooting: A state-of-the-art application can help you rapidly identify regular error patterns in code. Machine learning takes this further by not only detecting API usage constraints when using the standard library, but also detecting them for all other libraries – completely automatically. In addition to this, the system enables the ability to provide suitable solutions for specific problems.
  • Intelligent assistants: Developers spend up to 50% of their time reading documentation and source code. Programming assistants that are based on machine learning, enable developers to reduce this time by more than half. They do this by detecting tasks the developer is working on, and offer context-related support in real time, such as suitable code examples, usage statistics and recommendations.

Machine Learning will shape the future: Today, we can already say that Machine learning most definitely has a bright future ahead with the benefits it currently offers and looks possible to offer. Its value will depend on the additional value it can provide to companies and their value creation chains, as well as how well this value can translate into economic figures. Based on the information covered, it appears possible that machine learning can be advantageous in advancing the field of software development. Because of such advantages, there are already companies such as Kite, Source{d}, and Codota working on innovative solutions, especially for the purpose of software development. 


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