One of the significant challenges faced with meeting the development of ecommerce applications is to hire qualified candidates, onboard them quickly and retain them for the required amount of time. Any unexpected attrition during the project lifetime impacts the planning and timelines.
SAP Commerce Cloud comes out-of-box with a readily available code base and developers work on top of the same to customize and enhance as per business needs. The main goals involved in SAP Commerce Coud project implementations are to write new code, understand existing code, enhance code, write tests, fix defects, debug code, document code etc., Developers use IDES like IntelliJ, Eclipse, Visual Studio etc., to work on coding using Java, angular etc., and routinely perform these repetitive tasks on day-to-day basis. Less experienced developers often look for guidance from their seniors and rely on search engines like Google or programming question-and-answer sites like Stack Overflow for writing or understanding the code. The code quality, time taken, efforts spent differ from developer to developer because of absence of standard development approaches.
AI coding assistant tools address these challenges as they are designed to help write code, review, debug and optimize code. Their intended purpose is to assist with software development duties making the coding process easier. These tools use artificial intelligence to help developers with real-time code suggestions, auto-completions, code snippets based on natural language comments or questions. This saves time, reduces errors, suggests best practices, helps learn new coding techniques. The available tools in the market provide simple plugin integrations with IDEs usually used by ecommerce developers. The developer wouldn’t need any more to open a browser and search for guidance and would instead get suggestions within the IDE where the code is being worked upon. Few examples of popular coding assistants in the market are Github Copilot, Amazon Code Whisperer, JetBrains AI assistant etc.,
Of the various AI coding assistants, Github Copilot shows quite promising in making software development life cycle workflows easier in SAP Commerce Cloud projects. It plays the role of an AI pair programmer helping developers to code faster with less effort. It integrates as a plugin installing into an IDE which populates multiple autosuggestions of code which can be picked and used by the developer. It also comes with a Github Copilot Chat giving code suggestions inline as one type’s. Copilot Chat gives much richer pair programming experience right in the editor. Help can be asked while coding right where code is being written. Some examples of conversing in the chat by selecting a piece of code are as below
“Explain the selected code”
“Make this code more readable”
“Propose a fix for the bug in this code”
“Write a set of unit tests”
By adopting the AI coding assistant usage, developers can be relieved of the heavy lifting and can focus on developing business code instead of writing glue code. Developers using AI-based tools will get equipped to be at their best productive and can significantly improve their developer experience. Developers can also focus on creative tasks like designing, brainstorming, collaborating and planning.
Choosing the right AI coding assistant tool, which is committed to data privacy and security, creating responsible AI by design, would benefit development of SAP Commerce Cloud application in terms of release cycle agility, developer productivity and better code quality.
One of the significant challenges faced with meeting the development of ecommerce applications is to hire qualified candidates, onboard them quickly and retain them for the required amount of time. Any unexpected attrition during the project lifetime impacts the planning and timelines.SAP Commerce Cloud comes out-of-box with a readily available code base and developers work on top of the same to customize and enhance as per business needs. The main goals involved in SAP Commerce Coud project implementations are to write new code, understand existing code, enhance code, write tests, fix defects, debug code, document code etc., Developers use IDES like IntelliJ, Eclipse, Visual Studio etc., to work on coding using Java, angular etc., and routinely perform these repetitive tasks on day-to-day basis. Less experienced developers often look for guidance from their seniors and rely on search engines like Google or programming question-and-answer sites like Stack Overflow for writing or understanding the code. The code quality, time taken, efforts spent differ from developer to developer because of absence of standard development approaches.AI coding assistant tools address these challenges as they are designed to help write code, review, debug and optimize code. Their intended purpose is to assist with software development duties making the coding process easier. These tools use artificial intelligence to help developers with real-time code suggestions, auto-completions, code snippets based on natural language comments or questions. This saves time, reduces errors, suggests best practices, helps learn new coding techniques. The available tools in the market provide simple plugin integrations with IDEs usually used by ecommerce developers. The developer wouldn’t need any more to open a browser and search for guidance and would instead get suggestions within the IDE where the code is being worked upon. Few examples of popular coding assistants in the market are Github Copilot, Amazon Code Whisperer, JetBrains AI assistant etc.,Of the various AI coding assistants, Github Copilot shows quite promising in making software development life cycle workflows easier in SAP Commerce Cloud projects. It plays the role of an AI pair programmer helping developers to code faster with less effort. It integrates as a plugin installing into an IDE which populates multiple autosuggestions of code which can be picked and used by the developer. It also comes with a Github Copilot Chat giving code suggestions inline as one type’s. Copilot Chat gives much richer pair programming experience right in the editor. Help can be asked while coding right where code is being written. Some examples of conversing in the chat by selecting a piece of code are as below“Explain the selected code”“Make this code more readable”“Propose a fix for the bug in this code”“Write a set of unit tests”By adopting the AI coding assistant usage, developers can be relieved of the heavy lifting and can focus on developing business code instead of writing glue code. Developers using AI-based tools will get equipped to be at their best productive and can significantly improve their developer experience. Developers can also focus on creative tasks like designing, brainstorming, collaborating and planning.Choosing the right AI coding assistant tool, which is committed to data privacy and security, creating responsible AI by design, would benefit development of SAP Commerce Cloud application in terms of release cycle agility, developer productivity and better code quality. Read More Technology Blog Posts by Members articles
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