Towards a Future of Self-Testing Systems | TechWell

Towards a Future of Self-Testing Systems

Tariq King
Wednesday, January 29, 2020 - 09:00
Tariq King

Akash Anand

Tariq, can I ask for few suggestions on what techniques to think about when trying to make a test steps generator ? (Quite abstract question I know) But I am trying to think of something which can observe my test steps and learn to suggest cases around it. Any suggestions/hinds/direction, I will be thankful.

Tariq King

When you say observe your test steps are you referring to your steps via the UI

Akash Anand


Tariq King

Are you talking web, mobile, desktop? I can answer in a general way if that's better

Akash Anand

Yes, generic will be good.

Tariq King

well the first thing is that you'd need to be able to capture those steps, I would say if you are wide open and it's something like a web app then a chrome plugin could be a viable way to go

there's obviously some existing tools that can capture information but it's usually very specific to a tool

so all these record and playback tools

usually do that but then the output is very specific to a scripting language under the hood

so if you wanted something to capture your steps at a high level you'd have to first define a language that helps you express those steps

determine the level of abstraction

like is it that I clicked this element that happens to be a submit button

or is the abstraction you want in a step "to submit the form"

sounds picky but its an important distinction if you want to capture high-level vs. low level steps

Akash Anand


Tariq King

one of the projects I worked on in the past was defining a domain-specific language for testing

allowed you to express test steps

high level first and then refine them with the details

oh I should probably be threading these replies shouldn't I

well there ya go I blew up the hub already

Akash Anand

Ok, so once the steps are generated, cases can be combinations of probabilities under some constraints, right ?

Tariq King

ye it depends on what you are trying to build out... are you thinking that you would want to be able to have some sort of agent mimic your actions

or give you suggestions

guide your testing?

the way you would go about generating test cases once you have captured this information depends on your goal

Akash Anand

No no, mimicking the steps is not needed, just record and suggest cases.

Like an example would be if the step is to enter password (which obviously the recording won't understand, but at high level it knows that some text was entered) and later we can tell it at low level that it was a password, So the assistant should tell me to try different sorts of password like correct, incorrect, short long etc

Tariq King

oh ok ye like a virtual test assistant

very cool idea first of all

Akash Anand


Tariq King

somehow I remember talking about this a little with someone at a conference

Akash Anand


Can I get a link to that conference please ? would like to see or listen..would be delighted to.

Tariq King

ye so for this you could capture probabilities but also have some sort of look ahead algorithm

Akash Anand

look ahead algorithm means ?

Tariq King

one possibility is for you to build a crawler that can explore the application and build a model

and so what it does to look ahead is more that it knows that certain screens in the application exist

reachable via certain actions

and if you've run any sort of tests on that application before or other folks are testing it

then their actions can contribute to a probabilistic model

so when I say it looks ahead, it basically looks at where you are at in the application and compares your next possible actions with that probability model

and says hey, after clicking the login button most folks do this

Akash Anand

great idea !

Kevin Thomas

The probabilistic means that the actions don't necessarily lead to the same outcome each time. In other words, the submit button doesn't submit the form if you get some kind of validation warning?

Is that right?

Tariq King

or if it can't suggest anything to you at the time because it doesn't have enough data it let's you do your thing and takes your actions as input to the model

@Kevin Thomas probabilistic doesn't necessarily mean non-deterministic

what it does imply though is that it will be adaptive

in other words if most people are tending towards certain actions then it will give you the same outcome

but once that changes to the majority doing something else, it will adapt

hopefully I'm making sense here

Akash Anand

It sure does !

Tariq King

so if the test being run was a negative test that says hey it shouldn't submit

then not just the action, but all the previous actions that led to that transition would be part of the model

so the suggestions would lead him/her down a path of doing that negative test

sorry let me uncheck that send to channel deal, it was stuck

Kevin Thomas

I think I understand. I'm building a Q Learning model where we take real-world application logs to have the agent replicate the overall steps that real-world users are taking. but it makes random adjustments to the action steps once the agent has learned a "positive" test.

Tariq King

oh ok now that is very cool

we're looking into one of the same kind of projects but at the lower level


Kevin Thomas

That sounds really interesting. With web pages, there are relatively easy constraints for the agent's action space. In services/api work, that seems hard. Am I understanding?

Tariq King

it's like the weather thing

everything is relative

the UI called the API testing hard

the API called the Unit Testing hard

Tariq King

but yes

it's hard

but so is the UI problem, however I think your approach of learning from previous actions and then deviating

is the right path

its like what we do as humans to explore an application

Kevin Thomas

It seems like a "feasible" way to go, but I still have some hard thinking' to do.

There are places the agent gets stuck for sure, and working through those is where I'm spending time right now.

Akash Anand

Thanks @Tariq King for all the inputs. Will surely help me think in some direction towards my goal.

Tariq King

@Akash Anand no problem would be great to have you share your work some time, if you are interested in sharing at a conference venue and would like my help let me know

also in general training on test cases is a great direction

like having some base set of tests as your seed data

then generating variations off of those

Akash Anand

Great direction ! Was thinking of something like this only.

Tariq King

re: @Akash Anand no problem would be great to have you share your work some time, if you are interested in sharing at a conference venue and would like my help let me know

Akash Anand

Sure @Tariq King will be happy to share what I come up with. Will keep posted.

@Tariq King can you kindly posta link here about the conference you said earlier here

Tariq King

somehow I remember talking about this a little with someone at a conference

From a thread in #testing | Yesterday at 9:15 AM | View reply

sure I believe it was at

Akash Anand

Thanks :blush:

Tariq King

however, if you are in the US then I know StarEast/West and PNSQC also have AI tracks

HUSTEF last year had quite a bit of AI talks and they are all recorded and freely available on that site

Akash Anand

Unfortunately I am not in the US. I am from India. But I try to join conferences and webinars online. Also would like to join online meetups if any. Please share any links which I can join. :blush:

Tariq King

k for sure...

one good upcoming conference that is virtual is the Automation Guild conference.... it's not free but it's not very expensive either and its great

Akash Anand

Thanks. Will check out. I got its mail today morning or may be within a few days. Thanks for recommending.

Tariq King



Hey @Tariq King! Recently there have been lots of discussion about the regulation of #ai, what is your take on whether or not AI should be regulated and what does it mean for us as testers?

Tariq King

definitely needs to be regulated, like any other technology, if we are going to make sure we are safe and protected

I think what is happening more recently is that the widespread use of this technology is causing us to really question its capabilities (as we should) and how it can be used to cause accidental or intentional harm

so we definitely needs laws, regulations, monitoring systems, and to make sure there is accountability so that these systems are used responsibly

I think for us as testers it means that there is a big opportunity for us as professionals to contribute in a big way

even take some of the jobs in these fields... last year I was at the quest for quality conference in Dublin speaking with Davar Ardalan, founder of IVOW, speaking about this very subject.

Her company focuses on making sure AI is culturally aware for example

we both agreed that the testing mindset plays a key role in the success of AI/ML systems

diversity of thoughts, backgrounds and thinking

all of the traits she mentioned just reminded me of some of the best testers I know


Hey @Tariq King the whole talk about self healing tests in UI (Specific to selectors) and solving those issues via ML. How much of actual ML is used in these places ? Or these are just a combination of text similarity, heuristics and some regex ?

Tariq King

not much ML



but have to keep it real, this whole brittle selectors thing sometimes bothers me

not that it isn't an issue because it is, but AI/ML can provide is with so much more in terms of bridging the gaps in testing that promoting it only for self-healing UI seems like a waste at times

like we have truly hard problems like test data generation, the oracle, test selection etc.

most of the self-healing UI stuff that I've checked out, when I look at it is a lot of trial and error stuff

that doesn't really use much ML

but it's promoted in that way


:slightly_smiling_face: same thoughts. You put it so well. About the brittle selectors, we kind of separate styling(CSS) and data selectors.

Tariq King

that's why for me this year I'm pushing a whole new line of thinking about these "solutions"


I understand that adding ML term to the product works well for companies.

Tariq King

and trying to get folks to really think of biologically inspired testing solutions (something I am calling BITS).

gave a talk at a meet up last week in Portland trying to inspire that line of thinking

it's easy for folks to just scream AI/ML


Can you elaborate on it or post a link to that talk if available ?

Tariq King

but show me how your solution is truly something that represents a method, or way of solving a key problem using some biologically inspired solution

sure I think I can post the deck here in slack

one sec

it's pretty self-explanatory :slightly_smiling_face:


Akash Anand

I believe self healing selectors are more of uniqueness ranking of selectors and selecting a locator query which is of a lower or equivalent rank when the 1st/preferred strategy fails. Am I correct @Tariq King ?

Tariq King

yep it's just a series of fallbacks

until it finds the right "element"

and then wow, we've healed


So, the algorithm has to fallback to the next best “element”, based on similarity, element type, div region etc.

Tariq King

ye I just wondered why we're so focused on healing selectors

it's not the core problem

its like i got a cut

and i'm bleeding

let me focus on the blood

and patching it up

as opposed to like, hey why did I get cut in the first place

UI testing is complex yes, but the current tools are brittle


let's build new tools that aren't brittle

using AI and ML

instead of using AI and ML to try to patch the brittle methods using by existing tools

Kelly M

Hi Tariq! Is AI really the future of software and software testing? Or is it all just hype?

Tariq King

A bit of both... there's definitely a lot of hype as there are with new technologies, probably a bit more so with AI

but it's because the general applicability of AI makes it so useful in many different industries

so I think with that breadth there comes quite a bit of hype, marketing, fear, etc.

The truth is that AI is the present.... a lot of this technology is already part of software that we use in our day to day lives

so it's a great question, do we dismiss it as hype, I think we can't, actually I've felt over the last year some level of social responsibility to represent AI/ML well in our space and have folks understand the truth behind these things

and even learn to be able to separate it from the hype, so that we don't dismiss it and then bad things happen

Kelly M

awesome thanks!! Sorry got pulled into a meeting.

I know at one of the conferences Jason told us not to fear AI that it is here and it's coming! so thanks for this info too!

Kevin Thomas

@Tariq King , Are there areas in AI/ML that you feel the testing community could be spending more time in, or where you're just not seeing the expected interest level?

Tariq King

Not just the testing community, but in general there is not enough interesting in testing AI/ML systems

as usual we're using this technology, putting it into our products, and not considering the implications

so techniques for testing different ML approaches and models like neural networks

how do we even know we have coverage of these models

how do we deal with their dynamic nature

are there ways for us to generate edge cases or use equivalence classing to either get coverage or uncover issues with the nets, training, bias etc

even the AI/ML community still uses very primitive means for testing these models

accuracy, precision, recall, fscores

so testing community could definitely bring a lot to the table there

In terms of the vendors using AI/ML to automate testing there is also a lack of activity at the API/service and unit levels

everyone is doing UI testing

also most folks are tackling mobile at the UI level

so even there a huge gap exists for desktop web

Kevin Thomas

Wow. A lot of areas to work on and think about there!

Tariq King

ye there's more in my mind but i paused lol


Good morning @Tariq King, generally speaking.. automation and manual testing can complement one another when testing/investigating systems. Usually for strategy. How can the addition of AI compliment automation and manual testing?

Tariq King

This is a great question... there are several ways that AI can help to improve what we do both from an automated and a manual perspective

some things cross the intersection of both

for example, test prioritization and scheduling

sorry for the delay there someone was at the door :slightly_smiling_face:

so for example there is some work out there on leveraging ML for predicting which tests to run

that could be leveraged both for manual testing and automated test selection and coverage

Also a lot of the advances in image recognition can clearly help with visual testing

more stable mechanisms for automated UI testing

also for manual testing a good suggestion that came up here even earlier today was like a virtual assistant to help guide testing

maybe give suggestions as to what to test next, which techniques

coverage, and using probability to provide test information to someone who is exploring the application


Thank you too, great response. I tried to keep it general enough because the only 2 things I know (today) are manual and automation ... generally speaking since it all depends on the system. Thanks so much for this. No worries on the delay we are all busy, these answers showed that AI can compliment manual and Automation testing. Thanks @Tariq King!

Jason Arbon

@Tariq King do I need a PhD to do AI-based testing?

Tariq King

in all seriousness to answer Jason's question, it really depends :slightly_smiling_face:

if you're trying to do some really far out stuff maybe a phd can be useful

but I think it's less about the PhD and more about some of the independent thinking skills

the creativity, and thinking outside of the box, the analytics, the math sometimes when needed

and combining that with practical skills of development

lots of tools out there that are making this type of work easier as well

with things like AutoML may not even need a technical background to train models and test things that normally you would need a whole data science team to do


hey @Tariq King, what skills do you think testers should be focusing on to prepare for the future of AI driven testing?

Tariq King

Testers should focus on the things that testers do best, questioning the validity of things

Bringing that mindset to table when it comes to AI/ML and using it for testing

helping to shape what these tools do, and since we may be the ones training them and using them most, what features would accelerate our testing

I think having an understanding of AI/ML helps

but it also doesn't mean that everyone needs to become an AI expert

and that folks will need to learn python

I think these tools are becoming advanced to the point where they are easier to use and to get value from them you may not need to even care how they are built

in fact if they are built right, it will all be transparent to the user

Jason Arbon

@Tariq King how would you define ‘self-testing’ for noobs?

Tariq King

The whole idea of self-testing is just designing the system with components that can observe their own behavior as well as execute tests to verify that behavior

so rather than building a script externally to do testing

you would make testing an inherent part of the design... in other words make testing a feature

Nicholas Snogren

isn't that TDD?

Tariq King

Not quite... TDD is more about designing the code and writing tests as part of that design activity

so you write a test

it fails and then you write code to make it pass

here I'm talking about writing code that actually allows the system to do testing

so the system can test itself at runtime

better with an example

we can pick one of jason's favorite examples

Nicholas Snogren

yes thank you I'm still missing the distinction

Tariq King


imagine that you had a search engine that could be used by anyone to look for items, activities, things etc

anything on the web

now let's say that engine is built using a neural network

and it starts to see that there is part of its network that is heavily used

or maybe that the connections are changing frequently

and it could run some tests on itself to see if some of its search expectations were still the same, or now producing different results

now it may not know if the new search results are intended or malicious

but it could determine that difference at first

like hey, searching for president no longer gives me donald trump for whatever reason

or searching for peach gives me impeachment

you get the idea :slightly_smiling_face:

Dionny Santiago

With external test automation, we typically tend to run a set of tests as part of a production gate. A system that has self-testing capabilities built in is capable of executing tests against itself at runtime, when it is already in production. I think this is really useful when the system has some dynamic component that can change at any time -- e.g., an online learning algorithm, such as a neural net, like the example Tariq gave.

Nicholas Snogren

so the system self monitors in order to design new tests according to live production data

and runs the test in real time

but it needs to see something suspicious in order to trigger the design of those tests

Dionny Santiago

yes, there is usually a monitoring aspect that is built into these systems

Nicholas Snogren

so this is some mechanism which is capable at targeting specific suspicious activity and designing ways on the fly to check behavior around that activity

Tariq King


Nicholas Snogren

sounds very interesting

thank you

Tariq King

being able to have the system monitor its own behavior is a key part of it

then after that trigger, it goes into a mode where now it investigates what is going on with a series of tests

in other words it just doesn't trust its own behavior

just like we don't trust what developers did :slightly_smiling_face:

the big difference here is it's a runtime activity not a design time activity

most of our testing now happens before we ship

few advanced folks are testing in production

but still very much a human involved

here the system is testing itself in production at runtime

and has the ability to question its own models, components, behaviors

Nicholas Snogren

right so the design of the self monitoring system is key

Tariq King

and maybe in the future even truly self-heal

Nicholas Snogren

so it knows when to look and it knows how to compose relevant self checks

seems like there's a danger of setting in motion a process which creates its own definition of reality

without being able to tell if that definition is actually true

so handles for human insight and adjustment of this process seem very important

Tariq King


think about it this way

right now we're starting to build systems that do just that

not with the purpose of testing

what I'm saying is that testing should be baked in as well

because a lot of the adaptive behavior we are starting to see in ML based systems

bots chatting with other bots, creating languages, cars driving themselves

doing all of that without some major safety and testing checks at runtime

is very dangerous

and the very real worry that AI takes over will only be solved if we start designing these systems but test themselves and to explain themselves

Nicholas Snogren

yes keyword 'explain'

i remember from Jason's recent talk, in his answer about debugging, he mentioned tracing

but the same danger you mention in the adaptive behavior systems will be present by definition in the self monitoring system within the system

in both cases, handles built for easy human insight and control seem to be pretty important

*and insight, control, and adjustment

Tariq King

yes very much so

just looked back at Jason's question though

and he said self-testing for noobs

so I would define self-testing for noobs as this: imagine if Jason could take care of himself :slightly_smiling_face:

instead of everyone else taking care of him (like what happens today)

good definition @Jason Arbon?

Cynthia M

@Tariq King to piggyback on @Shak question - you did a talk just over a year ago about AI eliminating Manual Testing (watched it on youtube). You say that it is already here -also in that talk you touch on programs being able to "self test". Do you see the role of Software Tester going the way of say the Typesetter? and if not then how do you see the role evolving as AI/ML start to ramp up in our profession?

Tariq King

I think the role of the software tester will evolve in a number of directions

All of these talks recently about the regulation of AI etc makes me believe that folks with a testing mindset will be in great demand

and what we consider to be a role "testing software" may be a role validating AI/ML systems

making sure bad things don't happen

I do see testers moving into a place where the types of tasks they do change

and they are more using ML based systems and leveraging them to accelerate their testing

Cynthia M

Thank you, I follow what you are saying but I also have a thought that with this evolution that it (testing) may become a niche field.

Tariq King

interesting... explain more

what would be the niche it would fall into

Cynthia M

Sorry for the delay, I got pulled into something. I was actually thinking more about academia and how from a learning/training standpoint that AI/ML isn't necessarily a direct part of testing right now. Now of course as things evolve that may change but not everyone is going to be able to learn or transition from test software to validating AI/ML systems. (I hope I was able to convey that correctly)

Robin Foster

Hi @Tariq King, thanks for answering all of these questions! You touched some on ML bias and the need for human intervention in a couple of answers just now, so this is a general question for that: how does AI become biased and how can we deal with that?

Tariq King

AI doesn't become bias per se, I would say it is inherently bias

Bias for me is a part of AI being good at and used for simulating human judgement

As we know, we all have biases, and therefore all the training data, information that is out there to build these systems will have different forms and types of bias

depending on when it is sourced, where it is sourced from, how it is sourced, who sources it

so the real question is how do we deal with bias

and leverage it for god and eliminate the bad

bias can be good in many ways, but we tend to not want to call it bias

for example a good recommendation engine is very biased

it is biased towards what you like

what you want

same with search engines

but a little more clear how it can have undesired bias

if it shows me results for folks assuming a particular demographic, culture, age

and that happens to exclude my age, my culture, my demographic

then that sort of bias is unwanted

however, the key here is that bias in AI is unavoidable

because bias in our world is unavoidable

what we need to do is get back to our roots as testers and make sure that given the context of the application of AI

its bias is appropriate for its users

Jason Arbon

Booklet on this topic if I may be so bold/rude:

Tariq King

Thanks @Jason Arbon, yes great resource... you taught me a lot, think there's a video of your talk somewhere too

Robin Foster

Thank you!!

Tariq King

here it is

YouTubeYouTube | AICamp

AISF19: Testing AI and Bias, by Jason Arbon,

Tariq King

Jason when are you taking over the hub?

Jason Arbon

Not invited to fancy places, have to crash the party. I’ll take the hint ;)

Tariq King

no hint... i'm sure you're invited

they just put me first to make sure its successful

Jason Arbon

You are preproduction ...

Tariq King


and you are that one bug that slipped into production

Jason Arbon

True dat!

Tariq King

wow the hub is hot right now... it was quiet for a while, now I feel like I can't type fast enough

if folks are interested, there are a number of events this year that will have quite a bit of talks on AI and testing

there is in the Ukraine (March)

the EPIC Experience in San Diego in April

there's always StarEast and StarWest that have ongoing track themes around it

I'll also be at TestBash Detroit and Agile Testing Days in Chicago (edited)


On the subject of AI and self-testing, how do you see it impacting holistic test strategies? Many company companies follow the test pyramid as a guideline for a test strategy and @Jason Arbon has talked about the testing layers and cake. Do you see self-testing changing how companies look at their overall test strategy?

Tariq King

@Jason Arbon just likes cake that's all

but in all seriousness, testing being a holistic activity isn't going to change

Not just levels of testing in the pyramid, but all the other dimensions of testing

AI/ML driven strategies and eventually self-testing will be . powerful because they can be applied multidimensionally

It's actually one of the problems I see now with some of the vendor approaches

they are too focused on one thing

not holistic enough

so we're still having to piece everything together

to answer the question I don't think it will necessarily change how companies view their overall testing strategy

once they have it right the strategy is the same

however how its implemented may be different

today we think of scaling a lot of these things with people right now

instead of with technology, which is inefficient

so I think at company level goal will be the same and strategy will be the same

implementation will be different


That's awesome. Especially since a lot of the AI for software testing that I have seen focus a lot, if not exclusively, on functional UI testing. I think it would be awesome to start looking at an AI for software testing solution that allows for multidimensional approach.

Tariq King


Nicholas Snogren

It seems like self-testing is only possible in systems designed and developed with it from the beginning or refactored to mate with it, which would probably be just as hard as starting over.

Do you see self testing algorithms being designed in central locations by vendors and sold to companies, or do you see it as a strategy or pattern for a company to use in its own software (presumably a rather wealthy company)?

Tariq King

I think it is actually possible to deploy self-testing outside of a system designed from scratch

I think that it's about building observability into the system first

and there are different ways to do that without the design needing to be ground up

all the work on creating seams in applications

which have also been applied to legacy

are good examples of where there are opportunities to enable self testing

I think what it takes is for someone with that type of knowledge to be able to analyze the system, the unique situation the company may be in

Nicholas Snogren

do you have a link to a good resource on 'seams' for me to get acquainted?

Tariq King

and do the work needed to build the right seams

am sure

there's a book

let me look up the link

its around legacy systems and has a chapter on seams

or a few chapters :slightly_smiling_face:

here it is

seams concept in there...

we are most familiar with object seams

doubles, mocks, etc...

but there are several other types of seems, e.g. preprocessor seams

seams in the filesystem etc

at the end of the day it's about making the system testable

of course that is better if designed in upfront

Nicholas Snogren

Thank you very much!

Tariq King

but it's not impossible either to get systems even legacy ones refactored or restructured with some seams that can help enable self-testing capabilities

no problem

Nicholas Snogren

I hope you don't mind if I ask another question now...

Nicholas Snogren

self testing seems to be more applicable for situations in which the behavior of the system is dynamic.

When the behavior is statically defined like in traditional development, why would self testing provide advantages over enabling more observability and traditional testing techniques (edited)

Tariq King

it probably wouldn't

i think your observation about it being more applicable to dynamically adaptive systems is right

one of the major things now is that with AI/ML a lot of the behavior of these are dynamic

so as more and more systems incorporate these technologies those it becomes an increasingly important subject

but for things that are more static

self-testing isn't the answer

now it's always good to have observability

but that's a separate benefit

*set of benefits

for testing in general

Nicholas Snogren

thank you, It's very helpful I think to distinguish what kinds of problems these new tools can help solve, so we don't rush towards a specific solution for any reason other than solving a defined problem

Tariq King

yes it is

otherwise we just take a shiny new tool to every problem

and waste a lot of time and money

Jason Arbon

@Tariq King , what do you think is the biggest problem in software quality today?

Tariq King

@Jason Arbon not enough people truly care about quality until it's too late

too much people talking the talk and not walking the talk

so our biggest problems are the humans

great way to close this off lol

now I'll be quoted as saying that I want to get rid of all the humans

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