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React Native JavaScript framework stumbles

Once hailed as a breakthrough in mobile development, Facebook’s React Native framework is stumbling, with users reassessing their commitment to the technology and Facebook looking to overhaul it.
React Native has been used at companies like Uber to Tesla, Instagram, and Facebook itself. Late in 2015, analyst firm IDC saw React Native as offering a new paradigm for hybrid development, freeing developers from the Webview component and delivering native performance. React Native opened the native device platform to web developers, said IDC. But IDC did add the caveat that the technology was still immature at the time.
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Where low-code development works—and where it doesn’t

Suresh Sambandam is the CEO of KissFlow.
Large enterprises have traditionally faced a few core problems common to all companies. Accordingly, unified software solutions were created that could tackle these problems similarly across all organizations. Think widely used databases or customer relationship management systems.
But that still leaves the sorts of problems that are unique to each company, problems that a generic solution can’t solve. Instead, customized solutions are necessary. Consider purchase orders. Every company deals with them, but the requirements of each company are so unique that a single product that manages the entire process for every company doesn’t make sense.
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What is continuous integration (CI): Faster, better software development

Most software development today is done in teams working on one or more code repositories managed in a version-control system. Individual developers work on the areas of code that require changes and must decide when to commit their changes back into version control.
Sometimes, the code changes are easy and introduce few risks, so the developer can make the edits and commit with a low risk of interfering teammates working on the same codebase.
[ The essentials from InfoWorld: Get started with CI/CD: Automating your application delivery with CI/CD pipelines. • 5 common pitfalls of CI/CD—and how to avoid them. | Keep up with hot topics in programming with InfoWorld’s App Dev Report newsletter. ] But what if the team is working on a bigger feature that will require several days, weeks, or even months of development? When is it appropriate to check in these code changes back into version control? Furthermore, what happens when that code is checked in to ensure that the integrated code deve..

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Android SDK cozies up to Kotlin

With the August 6 production debut of the Android 9 Pie mobile OS, Google has released an Android SDK with special capabilities for development with the Kotlin language.
The SDK has nullability annotations for frequently used APIs, preserving null-safety guarantees when Kotlin code is calling into annotated APIs in the SDK. To ensure that newly annotated APIs are compatible with existing code, an internal mechanism provided by the Kotlin compiler team marks APIs as recently annotated. These APIs result in warnings instead of errors from the Kotlin compiler. Developers need to use Kotlin 1.2.60 or later.
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IDG Contributor Network: Scaling craftsmanship in an engineering organization

Craftsmanship is something that we talk about a lot at LinkedIn. We view it as essential to creating lasting and impactful products for our members; therefore, it’s something we’re always striving to improve. In my experience, there are usually two main inflection points for craftsmanship in the life of a technology company.
The first is when the engineering organization initially makes the decision to embrace craftsmanship as an important value. The earlier this happens, the easier it is to weave craftsmanship into the core DNA of the company. It’s during these early stages, when the engineering team is still relatively small, that it can help hold each other accountable to this new standard.
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IDG Contributor Network: Data is the lifeblood of AI, but how do you collect it?

When it comes to artificial intelligence (AI), there is no such thing as data overload. In fact, it’s quite the opposite—the more data, the better. Because AI systems have the ability to process enormous amounts of data, and their accuracy increases along with data volume, the demand for data continues to grow.
Consider, for example, an AI program designed to identify the cause of defective medical devices produced during the manufacturing process. As with any AI application, the software looks for patterns in the data using algorithms developed by data scientists. To try to solve this problem, suppose that the AI program receives and sorts through production data from different days of the week, times of day, machines and operators. But maybe those factors were not causing the defects, and instead they were caused by the rising temperature in the room. Only by providing as much data as possible to address different variables, can companies most effectively and efficiently determine t..

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IDG Contributor Network: Artificial intelligence will close the gap on latency in telecommunications

In the telecommunications industry, artificial intelligence already plays a lead role for marketers. For example, VoIP platforms are using IBM’s Watson to gather deep insights about callers and conversations. This data is then used to enhance and personalize the customer experience.
Inbound phone calls are a rich source of data for any company, and they are easier to mine and analyze with AI. For example, Watson transcribes conversations and converts them to text. The text can then be analyzed by software programmed to identify certain phrases and words designated as signals indicating actions. For example, the phrase, “what’s your warranty?” might indicate an intent to purchase.
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