Appium’s Pros, Cons & What The (Testing Framework) Future Might Look Like

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Since Perfecto is sponsoring and attending the annual Appium 2018 conference today, it’s a great time to take a look at some pros and cons, how it stacks up against the competing tools and what might be around the corner.

Benefits of Appium

What’s great about Appium:

  • It has a strong active open source community
    • Appium is by far the leading open-source test framework for cross-platform(mobile) native test automation (iOS, Android)
    • Appium is consistently backed by a large, very dynamic community, with steady support, commits, etc.
  • It has strong support for end-to-end testing in multiple programming languages
    • Appium provides support for multiple development languages through Remote WebDriver language bindings (Java, JavaScript, Perl, Python, C#)
    • Appium can cover black box end-to-end test flows including outside-the-app scenarios (e.g. initiating a call, sending a text message)

Challenges with Appium

Some areas where Appium could be better:

  • Setting up Appium locally can be a challenge: Teams are required to download, install and configure their environment which means having a local Android and iOS device available and connected.
  • Working with app objects for both iOS and Android isn’t easy, and falls into the top challenges (below) coming from practitioners. Since the Appium framework relies on iOS XCUITest and Espresso (Android’s UI automation framework), users needs to be familiar with the object structure, and know how to use the Appium object spy correctly.
  • Slow test execution. Tests can be slow due to the remote webdriver dependency, network issues and processing commands.
  • Test framework stability – Stability issues can occur when executing through CI or at scale and in parallel.
  • Test automation coverage and keeping up with latest mobile OS – Being able to fully cover gestural inputs, environment conditions, device settings and more, as well as support immediately latest Beta and GA versions of iOS and Android. Community supported solutions frequently move slower than handset vendor/mobile OS innovations.

Top Challenges from users on the Appium discussion board

Comparison of Mobile App Testing Frameworks

Despite Appium’s leadership today, DevOps teams are also adopting Espresso and XCUITest.

Since there is no perfect solution with regards to testing frameworks, the best solution for your needs might be best met by mixing various test frameworks across the DevOps pipeline.

Here’s a comparison of the leading testing frameworks:

Where is Mobile Application Testing Headed?

My testing framework intuition tells me that:

  • Appium will share more of the testing framework market with Espresso and XCUITest.
  • Functional testing using Espresso/XCUITest will become part of commit- triggered built-testing.  
  • Full end-to-end testing using Appium will be leveraged during full regression testing.
  • Appium stability will improve and execution times will shrink – it will get better & faster!
  • Hybrid test execution will become supported. Appium scripts will be able to trigger embedded Espresso/XCITests.

Conclusion

Appium is great! It’s got:

  • A strong open source community
  • Outstanding support for a number of programming languages
  • The ability to handle end-to-end test flows

Appium is weak:

  • In test performance and stability
  • In keeping up with the latest OS features (e.g. gestural)
  • In setup time

XCUITest and Espresso are also leading the market with strong user bases and helps fill in the gaps where Appium falls short – so keep an eye out for those other tools!!

It will be interesting to hear the upcoming Appium roadmap at the Appium 2018 Conference. Sign up for our live webinar to hear our take on the current and future state of testing frameworks and how Appium might fit into your DevOps toolchain.

The post Appium’s Pros, Cons & What The (Testing Framework) Future Might Look Like appeared first on Perfecto Blog.

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Edge computing: SWIM launches AI digital twins that learn

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AI startup SWIM aims to democratise both AI and digital twin technologies by placing them at the edge and within reach of everyone’s budget – without the need for large-scale number-crunching. Chris Middleton reports.

With Pure Storage and NVIDIA recently launching an ‘AI supercomputer in a box’, it is easy to believe that enterprise-grade AI is solely about throwing massive number-crunching ability at big data sets and seeing what patterns emerge. But while these technologies are notionally aimed at all types of business, the cost of optimised AI hardware that can be slotted into a data centre may be too high for many organisations, as our recent report suggested.

At the other end of the scale are technologies such as IBM’s Watson and Watson Assistant, which can be deployed as cloud services – and, of course, the numerous suite-based AI tools that are currently offered by Oracle, SAP, Salesforce, Google, Microsoft, and others. 

But for many IoT and connected-device deployments, neither data centre not cloud options are realistic, which is why many AI systems are moving elsewhere, fast.

For time-critical processing – such as when an autonomous vehicle needs to avoid a collision –  the edge environment and the distributed core are where the real number-crunching needs to take place. This is why companies such as Microsoft and Dell have announced new IoT strategies that focus principally on the edge and/or the distributed core.

The ability to add AI at the edge is an increasingly important element in the IoT, avoiding the need to transfer large amounts of data to supercomputers or the cloud and back again to IoT networks.

Startup SWIM.AI aims to “turn any edge device into a data scientist”, without the need for big data sets and the enterprise-grade number crunching that goes with them. 

The company recently emerged from stealth mode and announced the release of a new AI edge product, EDX. It aims to supply business and operational insights in real time from what the company calls “grey edge data”.  

Twin solutions

The new product autonomously builds digital twins directly from streaming data in the edge environment.

The system is built for the emerging IoT world in which real-world devices are not just interconnected, but also offer offer digital representations of themselves, which can be automatically created from, and continually updated by, data from their real-world siblings.  

Digital twins are digital representations of a real-world object, entity, or system, and are created either purely in data or as 3D representations of their physical counterparts. The concept is core to platforms such as Microsoft Azure IoT and AWS.

For example, every component of the largest machine in history, the Large Hadron Collider, is stored as a digital twin in CERN’s enterprise asset management (EAM) system. This allows scientists to not only know where everything is and what it looks like, but also how well components are performing and when they need upgrade, repair, or replacement.

But for most organisations, that kind of massive, bespoke programme isn’t an option, and they need something simpler, easier to deploy, and cheaper.

Predictive twins

SWIM’s EDX system enables digital twins to analyse, learn, and predict their future states from their own real-world data, according to the company. In this way, systems can use their own behaviour to train accurate behavioural models via deep neural networks.

The important difference to other AI solutions is that this ability is offered as a service in real time, without centralised, batch-oriented big-data analysis.  

“Our digital twins encapsulate what you really need to know about current and predicted performance of instrumented assets, and the insights can be easily integrated into your ERP logic, ops processes, or workflows to help inform decision- makers, in real-time,” said SWIM in an announcement.

SWIM EDX applications include smart cities, industrial automation, utilities, and IT infrastructure optimisation. “We’ve even used SWIM EDX to power an autonomous swarm of drones, flying a complex mission”, claimed the company.

Read more: Research: NASA to explore Mars with swarm of robot bees

Twin management

Gartner views digital twins as one of the top strategic enterprise trends in 2018. However, a key challenge is how easily enterprises can implement the technology, given their investments in legacy assets.

Read more: Gartner: Four best practices for managing digital twins

SWIM believes that limited skill sets in streaming analytics, coupled with an often poor understanding of the assets that generate data within complex IoT systems, make deploying digital twins too complex for some. Meanwhile, the prohibitive cost of some digital twin infrastructures puts other organisations off.

“Digital twins need to be created based on detailed understanding of how the assets they represent perform, and they need to be paired with their real-world siblings to be useful to stakeholders on the front line,” said SWIM.

“Who will operate and manage digital twins? Where will the supporting infrastructure run? How can digital twins be married with ERP and other applications, and how can the technology be made useful for agile business decisions?”

The company claims that SWIM EDX addresses these challenges by enabling any organisation with lots of data to create digital twins that learn from the real world continuously, and to do so easily, affordably, and automatically.

Importantly, the service can be delivered without new infrastructure, skill sets or expert management, said the company.

Internet of Business says

The edge environment is critical to the success of IoT programmes, but the challenge has long been that systems generally need to be fast, simple, and low cost, which means that processing power isn’t always available locally. And when it comes to AI, IoT systems need to maintain that speed, simplicity and low cost without the need for periodical retraining.

Put simply, edge systems are optimised for proximity, so latency isn’t an option – in other words, real time needs to be real time, and not an approximation of it.

In this sense, SWIM seems to have hit upon an ideal solution with EDX. But unlike the edge systems offered by AWS (DeepLens), Microsoft, Dell, and Google (Android Things), EDX isn’t part of a vendor ecosystem that locks clients into a platform or way of working. That may be an advantage to some organisations, but not to the others that can simply extend their platform to the edge environment.

Read more: Fetch launches world’s first autonomous AI smart ledger

Read more: Mind-reader: MIT’s AlterEgo wearable knows what you’re about to say

The post Edge computing: SWIM launches AI digital twins that learn appeared first on Internet of Business.

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How to Stop Netflix from Playing the Next Episode Automatically

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How to Disable Autoplay in Netflix

Once an episode comes to an end, Netflix automatically starts playing the next one based on the sort of contents you like watching. Therefore, you don’t have to manually spend time in finding a hot show. But what if you don’t want the entertainment app to dish out movies without your approval? Not a big deal! You can choose to stop Netflix from playing episodes automatically.

One thing worth noting is that auto-play next is specific to each profile. For example, if you have multiple profiles and you wish to turn off autoplay for all of your Netflix profiles, you will need to head over to each profile to disable the post-play feature. Do note that you can’t disable post-play feature from within the entertainment app as it has to be done from Netflix’s website.

How to Disable Autoplay in Netflix

How to Turn Off Auto-Play in Netflix

Note: Post-play feature is available on the following devices:

  • Mac/Windows computer
  • Apple iPad 2 or later running Netflix app version 8.0.0 or later and streaming over Wi-Fi
  • Apple iPhone 4S or later running Netflix app version 8.0.0 or later and streaming over Wi-Fi
  • Android OS 4.0 (Ice Cream Sandwich) or later
  • Apple TV
  • Netflix App for Windows 8
  • PlayStation 4
  • PlayStation 3
  • Xbox One
  • Xbox 360
  • Chromecast
  • Most Smart TVs, Blu-ray players, and set-top boxes
  • Wii U

Step #1. Open a web browser on your device and head over to Netflix.com

Step #2. Now, you need to select the profile for which you wish to disable auto-play next.

Click on your Profile in Netflix

Step #3. Next, click on Account

Click on Account in Netflix on Mac or Windows PC

Step #4. Scroll down to the bottom and head over to Playback settings options and click on it.

Click on Playback settings in Netflix on Mac or Windows PC

Step #5. Finally, you need to uncheck the box next to Play next episode automatically. Make sure to click Save to confirm the change.

Turn Off Autoplay Video in Netflix

You will have to repeat the process for each account to turn off the auto-play feature.

Note: If you are unable to access a Kid’s profile account settings, first choose Kid account and then head over to https://www.netflix.com/YourAccount to access individual settings for that profile.

From now onwards, once an episode has ended, next one won’t play automatically. You need to use the remote to manually choose the next show.

If you ever desire to go back to the default option, follow all the steps mentioned above and check the box for Play next episode automatically in the end.

That’s done!

Stay tuned

Is there any other feature you don’t like about Netflix? Let us know that in the comments.

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Tech Deals: Power Bank With AC Port For Charging Laptops, 15% Off Nintendo Switch Pro Controller, $80 Off GoPro, More

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As always, when it reaches this time of the day, we take the liberty of presenting multiple deals to you for your consideration. Each deal is designed to instantly save you money on some of the technology that you know and love and which you have maybe been putting off buying.

[ Continue reading this over at RedmondPie.com ]

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Oppo F5 long-term review

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F5 refreshes the page in the web browser on your computer. So what’s the Oppo F5, then? Is it a refresh of sorts, too? Or maybe it’s a refreshing mid-range smartphone that’s trying to look like it’s more expensive than it actually is. Refreshing, but not niggle-free. Pretty, but not without its faults. Good in most areas, frustrating in others.

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This iPhone X App Lets You Make Vivid 3D Models of Your Head

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Are you a selfie lover who enjoys snapping pics of your pretty face? Do you own Apple’s high-end iPhone X? If your answers are yes, and yes, listen up because there’s a new app coming soon that will (literally) make your head spin. Bellus3D FaceApp is an iPhone X-exclusive created by the team at Silicon […]
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Halfbrick Studios turns Fruit Ninja into a competitive multiplayer game with the beta release of ‘Fruit Ninja Fight’

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Halfbrick Studios haven’t been having a good year. They recently laid off half of their workforce and with that sudden change have also decided to start concentrating all of their efforts on their two most successful licenses, Fruit Ninja and Jetpack Joyride. Their latest release on the Play Store is an open beta product still under development. It is called Fruit Ninja Fight, and as the name would suggest, it’s a multiplayer-focused Fruit Ninja game.

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Halfbrick Studios turns Fruit Ninja into a competitive multiplayer game with the beta release of ‘Fruit Ninja Fight’ was written by the awesome team at Android Police.

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Readdle Documents 6.3: better PDF reader, new cloud file management & smart MP3 search

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Ukrainian developer Readdle today pushed an amazing new update to Documents, a Finder-like app you’ve always wanted that lets you read, listen, view, annotate and organize almost anything you want on your iPad and iPhone…. Read the rest of this post here


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YouTube’s live TV service now streams in Firefox

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YouTube TV debuted in a limited number of markets and could only be accessed through Chrome. The video-sharing platform is making it easier and easier to access, though: after launching it in additional locations and rolling it out to Apple TV, YouTu…
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