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You good afternoon everyone I hope you are all settled and we are ready to roll
Avinash
Good afternoon everyone and welcome to this webinar my name is Avinash and
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I really appreciate you taking your time out for this webinar
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Welcome again some of you already know about me and Pcloudy but for many of you who are attending be clouding webinar for the
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First time let me start with a quick intro as I said my name is Avinash and I am a co-founder of tequila recom which
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Is one of the fastest growing mobile app testing platform talking a bit more about pee Claudia's product it's one of its kind lifecycle application
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Testing platform for developers QA and business users Pcloudy is available in two different forms one is the public cloud which is one of
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The widely used offering from Pcloudy and the second one is for enterprises who are looking at setting up their own labs involved in
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Form of a private cloud or on print off so Pcloudy public cloud is one of the largest device cloud available today with 5000
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Plus mobile device browser combinations it's used globally by more than 50,000 users both from QN development community
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And I would I'm proud to say that more than people from more than 84 countries user platform and then pick nobody's helping them improve
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The app quality it's one of the highest-rated platforms on g2 crowd which is one of the third party platforms for crowd reviews he cloudy
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Has been covered by Gartner and foresters and has been widely covered by other media platforms as one of the upcoming and growing mobile app
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Testing platforms so with that introduction we are ready to start with a real agenda of today's session and I hope some of you joined
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Late are also settled so to be the agenda is around how do we optimize the device coverage and optimize the testing effort when it
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Comes to mobile app testing and I'm sure you must have struggled in your mobile app projects to figure out right device metrics to use
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And at the same time you must have figured out ways to optimize the device coverage by using certain methodologies
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Today my objective is to go little deeper and talk at more fundamental level why do we really find these compatibility issues and once we
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Understand why do we find these compatibility issues can be use that as an information to really predict failures and optimize effort
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So so these are the two things which are part of the core agenda of today's session and in that process we'll try to arrive
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At certain methodology to come up with right device metrics and optimize the test coverage
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So let's begin and to set some perspective and context I'm presenting some data points here which you might be familiar with so please bear
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With me for some time talking about when we talk about mobile application we talk about iOS and Android mostly so talking about iOS fragmentation
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Is in terms of number of devices is not a big challenge so there are overall 16 16 distinct iOS devices available till date in
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Terms of the versions yeah there are quite a number of versions released in the market but one good part with iOS is most of
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The users update to the latest versions so the fragmentation across the older versions are not that big a challenge so as you can see
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In this chart iOS 12 has almost 78 percent coverage as of now which is a record and Apple buy it means pushes you to
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Upgrade to the latest versions as soon as they release however for i/os 12 or 12.0 12.8 12.1 itself there are multiple devices with different
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Form factors older to newer devices which still creates fragmentation issues
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But when it comes to Android fragmentation is a nightmare and as I said you must have experienced this in your projects as well again
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Talking certain data points here so there are more than already 4000 distinct Android devices as of now and this is the devices without we
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Are talking about devices across the world and the problem which gets added is because of the number of versions which are available in the
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Market and unlike Andrew and like iOS in case of Android the older versions are still widely used and if you look at this chart
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The latest or one the latest is 9.0 but the 8.0 still has only 23% of the coverage the for the 9.0 data is still
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Not available even by Google hopefully it will be available in the next couple of months but because if you can look at the older
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Versions as well in 7.06 charts you go in fact 4.4 is still widely use and there is a 7.6 percent market coverage or or
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At for itself so you can't really ignore the older versions completely and that adds to the complexity when it comes to the employed fragmentation
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So if you if you try to do some math here in terms of the combinations which can exist so there are 16 device display
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Categories starting from 4.4 screen size or two latest higher screen sizes 20 different resolutions filtering Android versions 400 enjoyed of ice manufacturers and if
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You add to that into cellular networks that uniquely use to test the combinations are used and you can't test it on all possible combinations
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So the question arises is it really feasible to test it across such large variety of combinations and how can we optimize that so there
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Has been some traditional ways of optimizing the device coverage and I'm going to touch upon those traditional ways briefly before we kind of move
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On to the approach that we use and maybe you would have used some of these traditional approaches or you would have kind of mixed
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And match and create your own but let me just quickly touch upon these approaches to set the context here so there are two primary
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There are two primary approaches which has been used widely the first one is based on market penetration and the second one is based on
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The device diversity and let's go through each here quickly what do you mean by market penetration a simple way to look at is if
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I'm going to launch my application in specific market what I can look at is what are the top devices used in the market and
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I can just focus on those devices because if my application works on those top devices I'm sure of covering maximum number of users who
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Will be using those devices so that this approach is typically typically based on the market data of uses of devices in a particular region
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So for example if say in case of a market like India oneplus and zombie has a huge market share and along with Samsung so
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Can you really afford just to test on test on Samsung or you would like to test it on one plus and zero me as
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Well and if you combine three can you cover let's say 50 60 percent of the market share so that's the kind of analysis you
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Can do and come up with your device sets so that you are covering a maximum market penetration here
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Now as part of the cloudy we have a feature called device planner which exactly does that device planner is used by customers to analyze
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The market data so as you can see in the screen here you can select country and if you select a country it gives you
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The information about the top devices which are used in the country and for each device then you can see what's the market penetration so
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For example in case of India zyo me redmi 3 years is one of the highest has one of the highest market penetration with and
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It has it is used with Android marshmallow starts you so you can if you are planning to launch your application in India market you
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Should definitely test returns are made at me three years with 6.0 and if you look at other devices which are there in the list
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Samsung Galaxy s8 Note 8 1 + 5 c4 so you can just take the top devices and test on those first before thinking about
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Anything else that's truly the approach based on the market data and device planner can be used to get the data across different countries and
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We have most of the popular countries available in the list which you can use and and look at the market penetration data
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But there are some kind of advantages and disadvantages of the the market share data the advantages are that
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You choose devices with highest market share and you can kind of minimize your effort to make sure that you are covering a maximum market
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Percentage however the disadvantage is that you might lose on devices where maximum bugs can happen because you are just focusing on the top devices
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Used in the market and the problem with apps are one bad wave you can pay your rating and then reduces the download so can
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You really afford not to test on devices which are more prone to error if you're just looking at the market penetration data right so
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You really need to mix and match and that's where the next approach comes which is the device diversity and device diversity typically
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Device diversity typically is based on an approach where you want to maximize the range of devices that you want to cover as part of
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Your testing so the way this approach works is you can divide the device ranges into three different categories high and medium and low end
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And each has certain parameters of course these parameters can be changed depending on your situation but this is one of the widely used way
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Of categorizing the devices so high end means the devices which have higher hardware configurations like quad-core high Ram high display size higher resolutions latest
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OS versions and medium devices medium and devices are following in the medium category with slightly lesser Hardware capability and the low end water are
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The older devices which are kind of having very low hardwood capacity low screen sizes and older OS etc so you can typically categorize all
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Existing devices into three different category and then you can start looking at the top devices across each of the category and then you fill
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The data that we talked about like Rams if you display OS and use an orthogonal approach to see how do I maximize the the
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Coverage that I'm getting across these four parameters because end of the way these four parameters are the critical ones which decides the compatibility issues
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So here if you look at let's say if I decide if I have taken these five phones I see that these two phones have
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Exactly the same configuration 4gb RAM octa-core 6.3 6.3 inch display and
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Android 8 version is different but I'd leave 7 hasn't already so if all the parameters are same you can ignore one of the device
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And the same approach is followed across different categories so here also you can see SS zenfone 4 and oppas oh so joy has the
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Same configuration and then one can be excluded so the idea is that you are you are removing the devices which are similar in nature
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And trying to maximize the the key parameters and increase the diversity of the devices and same approaches for group C and once you are
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Done with this analysis across these three groups you can combine your device list and come up with a final one which can be optimum
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Device Cup which it could be 10 it could be 15 20
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That depends on the amount of effort that got put on testing you can although you can always mix this with the market penetration data
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To see if there are some top end devices which are not missed in this category as very high market penetration so you can always
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Mix this beta with the market penetration so these two are typically the most used
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Approaches of creating optimum device coverage right now of course you can have more parameters here to increase diversity and all but fundamentally the approach
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Means one of these two now be a bit cloudy to do it slightly differently and as you as you not now know that at
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Pcloudy we support variety of versions so anytime a new version is released for Android or iOS it impacts our platform as well so
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We ourselves have to be compatible across various versions before we can say to our customers that you can come and test your apps across
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The devices that we support so we do it slightly differently we try to predict the issues and
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And based on that we try to create our device coverage and test coverage so let's talk about that in slightly more detail here and
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To do that I think it's important to understand certain terminologies here terminologies which I am going to use when we talk about why certain
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Kind of issues or occur on a specific device across operating systems the first one is Android version and since and we are talking about
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Fragmentation which is more prevalent in Android I am taking the example of indoor but the fundamentals across Android and iOS remain same so when
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We talk about Android version there are three things one is the version name which is like Android approach 0 or 9.0 then there is
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A code name associated with it and then one of the most important data point to look at is the API level associated with that
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Version so one particular version can have multiple API levels for example sorry one particular code name can have multiple API versions for example 9.0
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Is 2850 9.1 comes it will be 29 and so on so forth
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And as I said target API level is assigned to each Android version here 10 one other important
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Terminology to understand is the manifest file which is part of the app package
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And it at a very high level consists of three three things here the first is the components of the app which are used in
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Sites all the activities services etc the second is what kind of permissions the app requires and the third which is important for us when
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We talk about compatibility is what are the hardware and software software features that the app requires so what are the low what are the
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Lowest version for which the app should work what are the highest version for the app for the app which it should work so that
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Clearly defines the range of operating systems or the kind of devices on which the app will work and based on that Google Play also
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Decides on which devices it can be downloaded or it certain devices that have to be excluded so that information comes from the manifest file
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The other key terminology to understand is the SDK versions so there are three different terms here the first is the compiled SDK version which
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You can ask from your developer if you're a developer you know but if you're part of the testing team you can ask your developer
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What is the compiled SDK version for the app because when the app is compiling the developer has to mention for which SDK version this
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App has been built so let's say if you choose 5.0 you have to build it with API level 21 which is the corresponding API
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For 5.0 which means you are using the api's of 5.0 to build your application so it might not prob and it might or might
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Not work on certain versions which are higher than PI dot 0 and same is true with the the lower versions as well however I
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Mean Android claims that there are backward compatibility but we see issues there then the other terminology to consider is the minimum SDK version which
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Is mentioned in the manifest file because you want to restrict if you want to restrict your app to be downloaded on certain kind of
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Operating system or certain range of operating system you can specify the minimum SDK version so for example I can say I don't want my
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App to be supported below 4.4 so 4.4 can become my minimum SDK version so Google Play itself will not allow the apps to be
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Downloaded on devices having below 4.4 and then the target SDK button this is important because this has to be decided based on the most
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Recent version you have used or or most recent version of the Android that you have tested on
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So for example if you're confident that I have tested my application for 8.0 the target SDK version has to be it or zero if
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You have tested on nine drugs no you can ask your developers to mention it nine dollars ago our wise there is a risk developer
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Can mention Hydrox ago if you have not tested there could become part of the key issues and this is how it's mentioned in the
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Manifest file the last line is the clear so you can see the meaning SDK version is mentioned for and the my target SDK version
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15 so this will decide on which versions the app has been on which version the app can be installed and what is the highest
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Version on which the app has been tested now with this terminology contexts in place
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We are we have reached a point where we can kind of start discussing why bugs occur in a he in case of Android and
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Same kind of concept applies for iOS as well but we're talking about that here the Android clear for examples so one of the reason
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And we talked about it earlier also is the fast evolving
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Android platforms and as you can see here the table kind of lists down the different versions available and their corresponding API level so for
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An l dot for audio there are two versions of anomaly turn zero and x EK levels access rate and similar
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Data point is available for other versions also so if you can take a look at this list from 4.4 which is the last kind
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Of popular version which still has some market penetration to the latest one nine there are more there are more than fifteen API levels which
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Currently exists in the market so which means if you build an application you have to make sure that your application works across these top
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30 15 API levels and since these API levels are evolving and the guidelines are constantly changing the chances of failures across the applications are
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Very very high but how do we find out how our API level change impacts our application is what you go through in a bit
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But one of the key reason why we see bug compatibility issues or app compatibility issues is the change in the API level from
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Android ecosystem itself the second reason is and again we talked about at the beginning existence of more than 24,000 devices in the market more
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Than 400 volumes available in the market is the and I'm calling it my rate device models here now
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What happens here is to meet the market demand the manufacturers like Samsung or Sami are on + the keep in leasing new Android device
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Models with diverse hardware so a phone will have a different screen size camera quality is essential compositions etc and on top of that they
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Also customize their Android operating systems by modifying the original Android software stack right and that causes maximum number of compatibility issues and to understand
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That the table kind of lists down the typical Android apps stack which is used by OEMs and the changes that they do so they
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kind of changes here the first is the the lower level system the bottom two layer that you see which are hardware abstraction layer
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And the Linux kernel now they change these two layers to create specific drivers for a particular device and
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The change they create new drivers so that there is abstraction available to the higher-level system so for example if there is a new kind
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Of voice recognition system available in a particular kind of device model they will create those specific drivers at the hardware abstraction layer which will
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Be used by the api's in the higher-level system so that's where a device specific driver device specific hardware creation happens
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Now if those drivers are not properly created and if these drivers itself have certain bugs the API is consuming those drivers also will have
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The bugs so that's why we see lot of compatibility issues now apart from modifying the lower level system which is the hardware abstraction layer
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For specific devices these volumes also customize the higher level system so for example you see the UI design of different OEMs different from each
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Other so as Samsung has a different UI design as Iommi has a different UI design so to basically customize the higher-level systems which are
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The top three layers mentioned here to create differentiations for themselves and the devices that they are planning to sell and these changes also create
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Compatibility issues now to understand more about it let's look at certain examples and
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We have done analysis across different bugs that we have seen over a period of time and we have looked at data available on internet
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As well and this is the kind of summary of kind of compatibility issues that you will find out so the left just focus on
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The left side of the table first there are two kind of compatibility issues which exist the first category is the device specific issues which
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Are which means that these bugs are related to a specific model of a device or specific category of a device so for example certain
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Kind of bugs will only happen on a Samsung device or a specific model of a Samsung device for example Samsung Note 8 or Amazons
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Fire so that falls in the category of device specific issues but then there are large set of issues which are not device specific which
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Means these these issues are related to these can happen on any device having a specific operating system
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So these are kind of these happen because of the API levels that we were talking about so now if you look at the root
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Cause even the device specific there are three main root causes the first is problematic driver implementation so we talked about the driver creation at
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Device level and if the driver creation has certain issues it will create bugs within the applications as well just to look at one example
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Of a problematic driver implementation there was a very famous proximity sensor lesion Samsung devices which means that if you bring your phone near your
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Ear to talk idly the the touchscreen should get disabled but in certain Samsung devices was happening otherwise if you bring it near your ear
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It used to get enable and if you take it far too it used to get disabled it was because of problematic driver implementation it
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Was returning a reverse value so that falls in the category of a problematic driver implementation and there are if you look at the percentage
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Of such issues fine I found 23 percent issues are because of problematic driver implementation which are very device specific issue the second category second
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Good cause within device specific is the OS customization which kind of covers 10% of the issue so for example Samsung came up with a
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New feature for their phones called multi window support which is not available in a lot of other models which means in in a single
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Screen you can open multiple application and you can work with multiple applications together now that feature created lot of bugs within application so that's
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A classic example of OS customizations creating certain apt specific issue and then the third one is a peculiar hardware composition so in case of
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Amazon fire there was a issue with video player itself because again it has a driver issue with omx codec so I mean I'm not
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Going to that detail but in terms of the higher understanding device specific issues are in three different categories the problematic driver implementation oils customization
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And equally an order composition so this is where he focus on testing on variety of devices is important but that this really covers almost
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40% of the compatibility issues the large part of the compatibility issues almost 6 almost 60% falls in the category of non device specific issues
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Which are because of the changes in the Android platform appearance or bugs in the core Android system itself so if you look at the
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Category here 47% of the issues are because of change in the API level so each time a new version of the Android is released
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And the level is changed it creates certain backward compatibility issues or creates certain issues with respect to the new version which was released and
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Large percentage of it falls on the disk attic so for example in case of android 8.0 which is API level 26 they change the
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Way the internationalisation on the device works the API which takes care of the internationalisation was changed and if your app works across different languages
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There was a failure right and that was a widely kind of known issue with eight nodes in a lot of application started field so
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Similarly there are multiple such issues which can happen when an API level a new API level is released and then in the last category
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Which is the original Android system once again this is a significant category where they in droid code itself is not a nation now these
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Issues get resolved quickly because as soon as these are reported Google releases a patch and these get fixed but for certain duration your applications
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Might see these kind of bug for example with 8.1 a widely known issue was reported with Bluetooth so if your application was using Bluetooth
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Or data transfer it it would fail on 8.1 so this was because there was a Bluetooth issue in the original Android itself so if
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You look at the overall table here I mean again summarizing almost 40% of issues are device-specific however 60% issues are non device-specific which are
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Related to API level combination so now if you kind of decide your device matrix you have to take both aspects in consideration one is
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How do you cover the device specific issues and how do you cover the non device classification in case of device specific things like device
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Diversity backers but in case of non device specific you have to focus more on different kind of versions and again based on the changes
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Which you are going to test and that takes us to the next stage as to how do we predict and if you
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I'm not certain that you follow the release documents which are kind of shared by Google and it's available for
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The release not clearly talks about the changes which can happen on all apps or changes which they
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Impact which will happen on the apps created for that specific version so for example this is one snapshot fraud Android 8.0 where there are
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Two categories the first one is changes for all apps and then it lists down what are the kind of changes of course it's slightly
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Technical in nature where it's more developer oriented but that is where he'll come to your help and the second category is if you are
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Developing a new app target it 48.0 then what are the changes that will have to belong now that's the and this is the Bible
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Where you if you if you go through this you'll be able to predict what should be my desk cases what should be my devices
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For which I need to plan my testing what are the functionalities that I should focus on where there are maximum chances of failure rather
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Than just blindly testing all of my application and I might miss the key areas where these changes can impact
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So this is the Bible and if you following the PETA releases and all you'll be able to plan your testing well in advance but
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What we have done with the cloudy is we have I mean our developers can understand this but we thought of creating something which is
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Very friendly to the testing community and we wanted to create some kind of handbook which the testing community can use and then start using
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That handbook to plan their testing and plan prediction of their failures prediction of failures in their applications so we we have created the handbook
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For in toward zero and we are kind of in process of creating handbook for other versions as well which will be available soon and
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I hope you would have got the upload here which you can probably download pilgrim to download what you see here is a snapshot but
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If you see the document it covers the full list of changes and the kind of test case that you should focus on if you
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Are planning to test your application on 8.0 and just to kind of summarize it here or give you a sense of what this document
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Talks about so this screenshot covers two test case so if you look at the app column it says if your app has a functionality
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Then you should focus on this test case so for some of the first test case says if your application uses current location of the
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User then 8.0 change has an impact view because Android has restricted the number of location updates when app uses the background service and that's
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One of the reason why you would have seen recently that in case of Ola no word the location updates are not very accurate compared
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To what it used to be earlier because Android has restricted the number of updates that they can get within a certain duration so they
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Have changed their implementation if they have to get the latest updates that frequently and if your application also has the similar functionality you will
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Have an impact on that function in terms of the the user experience or if you might get some errors as well so we have
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Mentioned the test case as well and this is a generate test case because you're not talking about one specific app it's just a guideline
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For you to understand how can I use this test case in my application functionality but the first row talks about if your application has
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A location feature you need to test on it dot zero thoroughly because there is a change in it dot zero which will impact the
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Second one is a similar change background execution limit again to improve the performance and the battery life Android has restricted the number of background
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Executions that you can do for your services so here you'll have to talk to your development team to understand ha where your app are
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Which of your app functionalities are using the background services and if you know those functionalities you can start testing those functionalities specifically rather than
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Testing everything at one go and we have seen so many failures with with this change there are exceptions coming in we also faced this
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As soon as this change came and we had to correct this so if your application using certain background services and if they're using our
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Older API and if your application has to be supported on a toward zero it will fail and and if you don't want to failure
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The change has to be done by the developers so similarly if you look at the document it has P each as all the changes
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Mentioned I'll just open the document for you to kind of give you a full overview but I hope you have got it - got
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It for download and feel free to share your feedback and thoughts here if you have anything else to be added quickly to let us
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Know so you can see here I mean there are almost 10 different impact areas that we have covered and each impact area has multiple
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Test cases which you need to consider so this is one way to start predicting or
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Start planning your test cases to be executed and also on the kind of devices that you should plan for testing rather than just blindly
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Testing it on the approach that we had discussed earlier which I'm calling it the traditional approach this is the approach that we're kind of
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Using it to predict the failures beforehand rather than wait for the failure to happen and then take corrective action so we'll be leasing this
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Kind of document for all versions so we are releasing it for 8.1 and then 9.0 within a couple of days and you'll be able
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To get an update on these changes easy the and easiest way to get those updates is if you are following our LinkedIn page we
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Are releasing all these updates as and when it's available so best way to get it is to start following that page so coming back
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To the end of session here my orthopods that we are following is let's not test let's predict and there are scientific ways to predict
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We talked about certain data points if you know more if you want to know more information about those data points we more than happy
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To talk about it but if you look at that scientific approach you'll be able to optimize your test cases as well as the kind
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Of devices that you should plan for your testing so with this thought I'll end this session thank you so much for joining and hope
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You had hope you are able to take out something from this session we can now open it for question or answer to drop in
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Your question in the chat window we will be happy to take few of the questions and
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If there are more questions we'll answer it individually over emails thank you so much it was pleasure talking to all of you so
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There is a question here what is the basis of device plan I mean from where you get painful from the market penetration so yeah
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That's how I mean there is a way to get the data there are analytics portals that we use to gather that data and there
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Are analysts who are constantly analyzing that data to make sure that this data is correct so there is a well-defined there's a well-defined process
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Behind the scene which goes to gather this data and I mean we have been using it for almost two years now and most of
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Our customers have benefited from it so there is a scientific way I can kind of get into detail Oh from where do we get
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This data there's another question regarding UFT integration of teacher event can we expect that
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Okay so this is slightly different from the topic that we were discussing probably I will come back to you directly over email there is
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A way to use ult with Pcloudy using the device that will give you more information on that over
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There is another question all the three groups will have seen four parameters
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The sender question we will connect with you to get more detail about that question
Avinash
There is another question from the book Mart how can we get to know that which version of androids are mostly used so that data
Avinash
Is publicly available the best source is Google developer portal itself which updates the market percentage of a particular operating system version on a regular
Avinash
Basis so the data that you saw in our PPT was a data till October 2018 very soon probably by
Avinash
Next month or so the data should get updated with the addition of latest 9.0 version as well so the source is Google here the
Avinash
Best source is good there's a question from Pankaj Android release cycle is shipped periodically so how does that factor in our testing of the
Avinash
App on latest versions if I understand the question correctly
Avinash
For any new versions that comes in the market how do you plan your testing is if that's the question as I said for each
Avinash
Version there is a beta release also available before the release that the main release happens so you can always track the beta release to
Avinash
Know what are the changes that are coming in the main version of the release and based on those changes if you can analyse and
Avinash
He'll be sharing the cheat code for those beta versions as well so that will help you kind of plan what are the kind of
Avinash
Changes which are coming in the version and you can customize your test cases accordingly and you can plan your devices if opening
Avinash
There is another question from Shaam can you kindly tell me where you get the iOS and it's fragmentation chart is it available on Apple
Avinash
Portal so unfortunately Apple does not release this kind of data publicly in the market but there are other portals using which you can get
Avinash
This data and as I said we have analysts in place who were looking at this data on a continuous basis so you can always
Avinash
Look at the device planner that we are providing and kind of use that data to plan testing on Apple devices per se but as
Avinash
I said earlier the advantage with Apple is majority of the users of grid to the latest versions so your your target should always be
Avinash
To test on all devices on the latest version and then probably one version less for show so if you're following the latest and latest
Avinash
Minus one you will be able to cover maximum of fragmentation for iOS specifically
Avinash
So you talked about three groups of Android devices so I'll be considering same parameters for all groups Ram et Cie yes so if you
Avinash
Are taking the device diversity approach yeah these are the four key parameters Ram CPU display an operating system to be considered and across each
Avinash
Category you can maximize the diversity across these four parameters so you can use thoughtful approach to see that you're not taking the same parameters
Avinash
Across different devices so yeah these are the four main parameters that you can use
Avinash
Another question from gopinatha speaker a platform similar to testing solution from expected app games tool you so fundamentally yes both are noble testing platforms
Avinash
And the wheels I mean Pcloudy is an end-to-end platform so you can use it for both your app testing and variety of
Avinash
Devices you can use it for creating your automation scripts and you can use it to run your existing automation scripts like aptiom espresso etc
Avinash
We also have another integration with crowd testing so if you want real use of three backs again you can use Pcloudy and one
Avinash
Of the key differentiator that we have is our autonomous testing so you can use our bots to test your application completely on its own
Avinash
So you just upload the application and what we'll do the end-to-end testing for you and it generates insightful data for you to analyze so
Avinash
That's one of the major differentiator between P Claudian on the platform's
Avinash
How does the so one question from Pankaj gee how does the functional and non functional testing impacted by the release of new versions Android
Avinash
And iOS and the corresponding EPA developed it's a very interesting question I think that's a good of in fact feedback also we didn't include
Avinash
That in our handbook yes it impacts the performance as well for example in case of Android L or zero itself there have been many
Avinash
Changes done at the HTTP and network level which which can impact the application performance for example we have seen because of the network change
Avinash
If you if you switch off switch on your Wi-Fi the application takes time to again connect back to the network and if you're let's
Avinash
Say if you have some timeouts in your client-server communication it can impact the application behavior
Avinash
So there are quite a number of performance issues as well which can happen because of APA changes but that support point will include that
Avinash
Specifically in the ad another question from Mandy's how to predict non device-specific issues so I think the handbook is designed to predict non device
Avinash
Specific issue so if you follow that it kind of takes care of all the changes which are part of every API level change or
Avinash
Every new version release and it it has listed all the impact areas so now you have to map it with your application if those
Avinash
Impact areas are relevant for us relevant for you and if if those are relevant for you you should consider those test cases first before
Avinash
Testing anything else there are some more questions coming in
Avinash
But for the time consideration we will come back on those questions individually will share the responses over email I will respond to you over
Avinash
Your email id thank you so much thanks for sharing your questions and your feedbacks and go through the handbook and if you come across
Avinash
Any other things to be included with your any situation you find out something is missed point out we want the community to participate in
Avinash
This exercise we want the testing community to use it as effectively as they can so that you can help everyone minimize their testing effort
Avinash
With respect to their mobile apps thank you so much thanks for being part of this webinar and
Avinash
Do follow our LinkedIn page to get the latest updates we'll be releasing more of these handbooks very soon thank you so much
