Wednesday, 3 January 2018

Some of My 2018 Learning Goals, and Free Resources to Help in Yours

With us now in January 2018 and the Christmas pies and frivolities becoming a distant memory, it is traditional to see this time as that act of penance and discipline! We enrol for the local gym, take a month off the drinking and increasingly look to improve our skills.

My efforts to eliminate the Christmas gut being beyond the scope of a software testing blog, I wish to detail with you a few of my NY resolutions to develop my skills and achieve my various goals. In the hope that you may find them useful in your learning endeavours, I list various relevant free resources I have come across.


1) Practising Programming


I am studying a part time IT graduate diploma, with the option to articulate to a Masters degree if I choose to. This is already very programming-intensive (and I have used Python, SQL, C, Java, Bash, Prolog and Perl as part of my course), however my last module done in the first half of 2017 was programming-lite and I took the second semester of 2017 off entirely. Not working in an automated testing role at the moment and not having a lot of side projects on, my programming skills are (hopefully temporarily) rusty.

In order to hit the ground running when my course restarts in late Feb, and also to develop my coding generally, I am endeavouring to devote an hour per day to learning coding - for application development and test automation (more on that later).

Whilst there are more online resources for this then I could possibly list, in just about any language existent, I am particularly fond of the professional Massive Open Online Courses (MOOCs) at Pluralsight and Edx.

Pluralsight is my personal favourite of all the various online tutorial sites, and its videos and tutorials are generally of a very high quality. It is not free, however for those with an Office Online email account it is easy to obtain a free 3 month subscription to this via registering on Microsoft's Visual Studio Dev Essentials site.

Edx, a well known academic MOOC provider, contains many courses but I recommend a truly excellent introduction to programming - MIT 6.001x Introduction to Computer Science and Programming Using Python - which is self paced and can be audited (done without certification) for free. Completing it is how I learned and got a grounding in Python. It is not an easy course and the weekly programming challenges and quizzes are quite challenging and need to be completed on time. It is however extremely rewarding. The follow-on course for those who complete the above (and which I have not completed myself), MIT 6.002x Introduction to Computational Thinking and Data Science, uses Python to apply various concepts from Computer Science such as graph optimization and dynamic programming before moving onto statistical methods such as Random Walks and Monte Carlo. I plan to return to MIT 6.002x at some point this year.

2) Test Automation


With respect to test automation resources, I am keen to devote myself to learning API testing before returning to UI automation.

In view of this, since I already have some experience of using SoapUI I will try to learn Postman API. Danny Dainton provides some great tutorials and examples on his Github project, which I plan to work through.

3) Machine Learning


I took an AI module a few years ago and was fascinated by it. It was going to study a machine learning module as part of my degree however am not able to do it this year due to missing a certain prerequisite. I therefore wish to, and coming from a strong maths background should be able to study Machine Learning is my own time this year and see how proficient I can get.

I have been avidly watching and doing a few homework exercises from two courses by Nando de Freitas, a professor of Statistics and Machine Learning at the University of Oxford and the University of British Columbia. His lecture style is engaging and easy to follow and the courses are quite entertaining.

The UBC undergraduate machine learning course from 2012, for which all lectures are on youtube and exercises and projects are available, encompasses material from basic probability theory right up to Bayesian Classification and Deep Learning. With the exercises requiring a knowledge of Python, various tutorials are linked to and included.

As a follow on, de Freitas' Oxford course in Deep Learning goes much deeper into the theory, however whilst the videos are freely available the course notes and exercises are sadly hidden to non-students. It is still worth checking out however.

Summary

The above projects are what I plan to work on for the first half of this year, my academic studies permitting. If you have any ideas of other resources or projects that I could learn from, I would be most grateful.

Tuesday, 5 December 2017

Some Trust in Models! On Simulations, HyperNormalisation and Distorted Reality in Software Teams (Part 1)


Still from Adam Curtis' 2016 documentary Hypernormalisation


Software is all about abstraction. We take an existing or desired process, model it and codify that model into a set of instructions and data that computers can read and follow.

We come up with different processes, methodologies, notional lifecycles, workflows, test strategies, measurements and quality controls to steer our immensely difficult projects to a satisfactory conclusion. For that we get teams of people with different roles and skills to work together, manage the creation and deployment of code with its own complexities and dependencies and implement what (we believe) users want is incredibly hard.

The processes we use to create software are also abstractions. The problems we face are, how much do the abstract requirements, process and methodologies we implement really reflect a desired real world outcome? In the midst of a software project, how do we maintain the link between abstraction and reality? What happens when a software team loses the ability to know about the difference between simply fulfilling the process and getting to a real world product people actually want? More dauntingly, at what point will the team stop caring?


Everything Was Forever Until It Was No More


A stamp featuring Pimenov's "Wedding on a Tomorrow Street", 1973

Anthropology and Sociology provide some interesting allegories that within limits help us to look at the questions above. The Russian academic Alexei Yurchak in his 2006 book "Everything Was Forever Until It Was No More: The Last Soviet Generation" discussed the paradoxical nature of life in the 70s and 80s Soviet Union. People were realising the disconnect between the ideological and propagandistic announcements of a Soviet state that saw itself as successful and immutable ("the end of history" as Marx envisaged) and the increasingly obvious fact that its economy was stagnant, its institutions were failing, events such as the War in Afghanistan were hurting its collective psyche and their quality of life was getting worse by the day. However in the absence of an alternative, whilst they understood something wasn't quite right they remained dissonant and carried on with the pretense that nothing was wrong, deluding themselves into a self-fulfilling prophecy. All the while the national discourse was piling more upon itself and becoming even more repetitive, in unwavering copying and reinforcement of earlier dogma. When the Soviet Union did collapse so quickly and dramatically, its disintegration was shocking to most Soviet citizens who had seen it as eternal. Yurchak coined this condition "Hypernormalisation".

The disconnect between the official narrative and the reality of life in the final decades of the Soviet Union gave rise to artistic protests of a satirical nature, with films such as Andrei Tarkovsky's "Stalker" describing a world that was outwardly similar to ours and could fulfill all our dreams but at a deeper level profoundly different and nightmarish.

Yurchak's book had a profound influence on the English BBC journalist and filmmaker Adam Curtis. His impressive 2016 documentary "HyperNormalisation" expressed the belief that this had been extended to the whole world. In his view, from the 1970s onwards our leaders and media figures had grown tired of struggling to articulate and tackle the complex problems of the real world, resigned themselves to managing the current order and predicting risks and created a "fake world" which trivialised long-existent complex social, economic and political issues into half-baked narratives of "Good vs Evil" with misplaced or contrived enemies. Instead of challenging themselves and the narratives told to them, people turned to virtual worlds in cyberspace that were designed to be free but had powerful hierarchies of their own - harvesting the information and activities of billions of people and and filtering the media people saw to reinforce instead of challenging their opinions.

Consequently people either grew to be dissonant of the "fake" perception-managed world and the real world, accepted the narrative as fact and opted into solipsism and self-focused activities or used the internet to create huge protests and revolutions. Those who retreated became susceptible to agents who were skilled in maintaining confusion and instability - the film uses the examples of then-candidate Donald Trump and Vladimir Putin's strategist Vladislav Surkov - turned politics and news into bewildering theatre such that facts and truth no longer became politically relevant and rumours and chaos reigned. This left them much more open towards the status quo (as in Putin's Russia) or demagoguery (as in the 2016 US Elections).

For those who revolted, in the absence of a compelling alternative direction of society these revolutions failed tragically and spectacularly, such as the protests in Egypt that were hijacked by the Muslim Brotherhood, eventually to be deposed by the military, or the Syrian Civil War that led to the rise of ISIS.


The Road to Disneyland. Simulation and Simulacra.


Pluto, Dale and Daffy Duck on a firetruck, Disneyland Anaheim, 2010

Both of the narratives above borrow from postmodernism, particularly semiotics (the study of communication with and assigning meanings to symbols and signs). The French sociologist Jean Baudrillard in his controversial 1981 treatise "Simulacra and Simulation" described the process where human culture progressively replaces our direct experience of reality with a series of signs and symbols (which he refers to as "simulations") - copies and representations of the real world with a seductive quality.

Over time the simulation is tweaked and copied to the point where it deviates from the original to the point where it is a (in his words) an "evil appearance—it is of the order of maleficence". This continues to the point where any relationship with the original reality is semantic and arbitrary at best.

The end point of this, which he calls a "simulacrum", is a simulation or copy that has been abstracted to the point where it has no relationship to an original at all - only to other signs that may themselves be simulacra. Our life experience of the simulacrum, not being based on any grounded physical object, is not even acknowledged or cared to be based on reality - yet it becomes a “truth" in its own right. This artificial existence is known as "Hyperreality".

The most common example stated, referred to by Baudrillard and Italian philosopher Umberto Eco, is Disneyland. The facades of Main Street with its allusion to an idealised past create a facade that appeals to our imaginations and desires. The Big Thunder Mountain ride is an exciting allusion to old mining rail tracks in a cowboy setting. Nevertheless, Main Street as a real street never existed and mining rail tracks of bygone times were not anything remotely like Big Thunder Mountain. Of course, Disneyland is so seductive that none of this matters. We engage with the fantasy world as if it were real. This is the definition of the Hyperreal.

Other stated examples of simulacra include historical fallacies that have been promoted widespread as facts, artificial substitutes for human interaction such as sex dolls and AI chatbots, films with digitally created CGI characters and backgrounds and "structured" reality TV shows.

A Postmodern Perspective on Software Delivery


I came across the work of Baudrillard along with Adam Curtis' "HyperNormalisation" at about the same time in 2016, after about nine years of working as a tester. Whilst drawing conclusions from ideas from sociology and anthropology applied to software teams without thought is a flawed and dangerous activity, I believe that they provide a lens through which our inability to deal with the inherent contradictions behind key concepts in software engineering can result in software teams falling into flawed and misused practices - and why even if they are suspected to be flawed and misused, teams fall into dissonance and fail to act right up to product catastrophe.

For this I offer perspectives on four concepts critical to software engineering and testing - quality, measurement, requirements and methodology/process.


Quality - Relative at Best, Simulacrum at Worst


The usual aim of a software team is to deliver a "quality product", however Quality is a vague and shifting target. Gerald Weinberg, seen as the "Godfather of Agile", wrote in his 2012 blog article "Agile and the Definition of Quality" on the "Relativity of Quality' - "what is adequate quality to one person may be inadequate quality to another." He states the following -

"If you examine various definitions of quality, you will always find this relativity. You may have to examine with care, though, for the relativity is often hidden, or at best, implicit.

Take for example Crosby's definition:

"Quality is meeting requirements."

Unless your requirements come directly from heaven (as some developers seem to think), a more precise statement would be:

"Quality is meeting some person's requirements."

For each different person, the same product will generally have different "quality," "

He list various statements defining quality from the point of view of specific project stakeholders.


"

a. "Zero defects is high quality."

1. to a user such as a surgeon whose work would be disturbed by those defects

2. to a manager who would be criticized for those defects


b. "Lots of features is high quality."

1. to users whose work can use those features–if they know about them

2. to marketers who believe that features sell products


c. "Elegant coding is high quality."

1. to developers who place a high value on the opinions of their peers

2. to professors of computer science who enjoy elegance

"

etc...


His ultimate definition of Quality - that it is "Value to Some Person" - has consequences to agile teams. He states that the definition of quality is "political and emotional" and thus leads to decisions on whose opinions count most. Also these decisions can be less than rational and are hidden from public view.

It is my assertion that in cases where not enough thought has been given to grappling with the contradictions above, a team’s conception of “Quality” has little in relation on the reality of the product (to the extent that the reality can be defined or measured) or the aims of the project. Quality as a symbol or concept becomes nothing more than the biased opinion or dogma of some powerful manager or stakeholder or a vague guess of the desires of some abstract “target market”. However in the perceived absence of anything better, the team acts as if it were the truth. It becomes a simulacrum.

The effect of this is we have started to give up the belief that we can make a “quality" product. James Bach, in his 2009 blog article “Quality is Dead #1", paints a despairing picture -

“A pleasing level of quality for end users has become too hard to achieve while demand for it has simultaneously evaporated and penalties for not achieving are weak…. When I say quality is dead, I don't mean that it’s dying, or that it’s under threat. What I mean is that we have collectively - and rationally - ceased to expect that software normally works well, even under normal conditions. Furthermore there is little any one user can do about it.”

Bach asserts that the result of this disillusion with the possibility of quality is that management have given up and moved towards the lowest common denominator approach - dispensing of good test teams and moving to cheaper and less capable offshoring teams.

“Top management can’t know what they are giving up or what they are getting. They simply want to spend less on testing. When testing becomes just a symbolic ritual, any method of testing will work, as long as it looks impressive to ignorant people and doesn’t cost too much.”

This “going through the motions” while publicly acting as if quality is being improved, as I see it, is a type of mini-hypernormalisation.

The Question of Measurement


Measuring an attribute that does not lend itself to precise and agreed definition and arises from human feelings and politics is evidently problematic and will lead to inconsistent and tenuous results. Rich Rogers, in his 2017 book "Changing Times: Quality for Humans in a Digital Age" writes -

"If stories and feelings tell us more about human responses than cold facts, dates and numbers, this might provide a clue as to why software development teams, and the organisations they work with, sometimes struggle with the question of quality."

"In this field, refuge is often sought in numbers.... By setting numeric quality targets - sometimes called exit criteria - a desired state can be agreed upon: a point at which the product is deemed good enough for whatever follows, including whether it is ready to be released to customers. The numbers act as a comforting security blanket, creating a sense of control. Even if the picture they paint is troubling, at least the provide a means of seeing that picture."

However as Rich Rogers continues to explain, this is an abstraction that while comforting, is limited and prone to mislead. Crude metrics such as counting of passed test cases and defects assume an equivalence between test cases that isn't likely to exist. They also hide the types of investigation and testing outside of these test cases along with defects that were resolved without the need to record.

"Quality is not measurable in the way cost or time might be measured... There is no such unit of measurement for quality."

He makes the case that metrics still have a role to play in discussions about patterns and potential issues. Reports are only useful in triggering those discussions - about what the metrics tell and do not tell.


The Illusion of Requirements


What about requirements? If one takes a list of use cases, desired functionalities and acceptance criteria - and the product contains all of these working to some agreed order - does that mean we have a quality product?

I believe that this is also tenuous at best and a comforting fantasy at worst. Requirements follow the same rules as "quality" defined by Weinberg. They depend on the judgement, political power and knowledge of the person who defined them - as filtered through project stakeholders, business analysts and the printed page.

The person who conceived the requirements, we have to assume, has a correct knowledge of the problem to be solved. Anyone with experience of software development will know of circumstances where that is a bad assumption. They may arise from a high level abstraction of an existing business process, ignorant of the day to day challenges and tacit knowledge of those implementing the process. The person who stated the requirements may be a high level manager without any experience of ever implementing the process, a slave to the reports of subordinates.

The illusion doesn't end there. Various test case management tools allow use cases and acceptance criteria to be linked to one or more test cases, generating requirements traceability. This is also flawed for the same reason that test case metrics are flawed. They make presumptions that quality in a requirement can be neatly expressed by X test cases passed in an associated matrix, or an hour's session based exploratory testing revealing no defects. This is very wrong as any tester with experience will tell you.

Methodologies and Primacy of the Process


In response to the above, there have been created many different approaches to a software development project along with practices within them. Even within Agile we have XP, Kanban, TDD, BDD, Continuous Integration, Scrum, SAFe, DevOps… Even within testing we have competing schools and methodologies. These are all simulations of how teams work in practice - very rarely do teams follow a prescribed methodology to the letter. How one team defines “agile” can have only a tenuous relationship to another even within the same company.

The danger is that the process is deemed to matter at the expense of the outcome, or implemented to provide benefits to the adherents without respect to the project. For new adherents, as Rich Rogers points out -

"The techniques and tools used in carrying out the work can seem exciting, and there is no shortage of new ideas and skills to learn. The desire to be at the forefront of change, or at the very least to demonstrate awareness and familiarity with current methods, can be a powerful motivator in this field. Adoption of new techniques, training in how to use new tools and acquisition of knowledge and skills related to new ideas, or possibly a desire to enhance a resume."

One area where the hype and impetus to learn is already causing an effect is in test automation. The drive to automate more (if not all) tests, and its effects on tester recruitment, causes testers to devote project and personal time to learning automation tools and programming - and to implement them without experience or real forethought. I know from my own experience the waste and effects of poorly implementing an automation strategy based surreptitiously on a desire to learn a new skill in a commercial context.

Another danger is that processes are defined at the company level and not the team level. Because they were believed to work before, we enforce processes and methodologies on other projects in an effort to "standardise". This may make sense at a management, resource allocation and control level, however projects with ill-considered, enforced processes risk great failure.


Leaky Abstractions in a Complex World


If we understand the flaws in defining quality, measurement and requirements, and our methodologies are idealisations, why do so many teams still persist in making critical project decisions based on their flawed understanding of them? Is it purely ignorance or something else?

Rich Rogers makes the point that metrics, however flawed, act as a comforting security blanket, providing some basis for decision making. We may not be measuring the right thing but we are measuring SOMETHING that may or may not be close to quality.

In the same way, requirements may be incomplete, flawed or at the extreme end utterly irrelevant to the problem we wish to solve, however they do exist. One can use them for contracts, resourcing, planning, development, testing and delivery. In agile methodologies we can continually add changes until (we hope) the end product approaches something the user or stakeholders might want.

In any case these, along with working definitions of quality, are all models of the "real" state of a project or product. For better or for worse they are vital in reducing a development project from something almost ineffable to something that can be planned or achieved. I treat them as "simulations" as defined by Baudrillard. Because of this, they are greatly seductive.

What matters is their relationship to the real state of the product and the development process.


Hyperreality and the Failing Team


My conjecture is that in projects that are dysfunctional or fail to provide what we call a quality outcome, these simulations are so far removed as to be devoid of reality. In the same way that Disneyland is a simulacrum, so are these.

However, simulacra are greatly seductive simply because they are easier than embracing the difficult to manage real world they pretend to describe. Hyperreality is not real but its sway on team certainly is. Also, changing approaches and mindsets within teams and at the company level, especially without either the privilege of management support or a clear narrative of a better solution and how to get there, rates from difficult to impossible. The closer to the project deadline, after so much has been invested and with the probably painful consequences of a late or failed delivery, the less the team will be willing to experiment and the more the team is likely to act is if nothing is wrong. Status reports show green, problems are ignored, process and the simulacra are gospel - and then the Soviet Union collapses.

Nevertheless, as with the final decades of the Soviet Union, it is probable that a few team members at some level know that something was wrong with the system even if they could not articulate the problem and don't see an alternative. They may follow "best practice" to the letter, see great test coverage as defined by the flawed metrics above, defects resolved, requirements ticked off but their stakeholders still complain, or their clients find defects that are tangential to or don't make sense based on the requirements they worked with. Everything is said to be running smoothly but everyone and everything is stressed. This is what I regard as HyperNormalisation - hyperreality with a subtle chink in the armour.

In companies that are greatly hierarchical, have established and immutable processes and teams with egos and dominant personalities reliant on the status quo it is likely that the unnerved team members above, especially if not at senior level, will keep quiet. They may decide that "Nobody got fired for just doing their job", or patiently wait for the end of the project. They may ask to be moved to another project or if the stress becomes an issue take sick leave. They may go through the motions of work without committing fully to it. These are a protest of a sort, but all they do is accelerate the eventual collapse and slump in quality.

The unfortunate truth is that without some shock that forces the team to reflect on its assumptions and processes, most teams trapped in a seductive but vicious hyperreality are not likely to be self aware enough to change until the project suffers dramatically or collapses entirely.


Epilogue


In this text I have covered concepts of hypernormalisation, simulacra and simulation and hyperreality and suggested them as analogies to look at four key concepts in software engineering - quality, measurement and requirements and methodology/process - and their impact on software projects. I have asserted that our inability to understand that these are ultimately seductive simulations with varying levels of relationship to the real world, and the difficulties of teams to reconcile these, cause great risk of projects deluding themselves into poor products and failure.

In Part 2, to be completed shortly, I look at applying these concepts to the IT industry and our tech culture as a whole, and look into various ways suggested to prevent or rescue teams from seductive self delusion. In the meantime, I would be grateful for your comments and considerations.


Friday, 20 October 2017

I'm Paul and I'm a Failure (and it's ok!)

Every day I make one silly mistake. Be that misreading some acceptance criteria or use case, setting something to the wrong value in JIRA so that it doesn't appear in a bug report, forgetting to send a document to someone, missing my train stop on the way home, accidentally pulling out my wife's computer's power cable when disconnecting my own laptop, the large number of times I wrote a tweet that in retrospect I shouldn't have...

My life in IT has had a few pretty startling incidents of backing a losing horse. The time when as test lead I fully and excitedly backed my superior's decision to solve our automation problems by buying a licence for HP QTP for tens of thousands of dollars (buying into the logic that spending lots of money of a tool shows undying commitment) going gung ho at creating automated tests in it (my team of three being the only team to do so). When my superior left and it was sensibly decided by the tech management that we would save our money and move to Selenium, my team lost its entire automation suite overnight. I couldn't argue - it was totally the right decision.

Or the time when due to my lack of experience in development, knowledge of the relative benefits of a breadth-first search and willingness to ask for help the recursive database abstraction layer I wrote took days instead of tens of minutes to run (or more often crashed due to an out of memory error - no mean feat in a garbage collection language like C# !)  and caused severe delays to a product release. The fallout from that shattered my belief in my own programming ability for years, but I got over it slowly.

Or the time when I managed to break a database migration system I was coding a multilingual interface for due to the fact that one of the lines I (clearly in an unthinking fashion) translated into French was actually a SQL statement.

Why do I mention these potentially career-limiting paragraphs in my blog? Because whilst I suffer from self belief issues as much as the next person, I don't feel ashamed of the mistakes I made (and occasionally still do), have got over the need to be a perfectionist and slowly recognised them as opportunities for learning and self reflection. Only the most privileged and least willing to take risk of us sail through life without failing at something.

Yet when I read the blogs of some of the other testers and thought leaders in this field (not that I would ever call myself a thought leader in anything), I am unsettled by the lack of humility or mention of the hard lessons behind the advice they give. Of course we have careers to protect, conferences to speak at and consulting gigs to apply for, however none of us were great IT consultants, devs and testers out of the womb. Not One Of Us. Rarely is a career a perfect and graceful trajectory from school, university via junior to senior. We all have mistakes we have made (some of us may well have been fired from jobs and had to bounce back) and opportunities to learn, so why don't we write about them, or talk about them at conferences, or mention them on Twitter?

Why aren't we more tolerant of the mistakes our colleagues, managers or staff make? Do we think we are above them? I once had a boss whose lack of tolerance of perfect work (or for that matter, temper) was legendary. I once heard him shout "I don't pay you to make mistakes!" Was he devoid of errors himself? Not at all.

Was his team a perfectly oiled machine as a result? Of course not, and most hated him. High performance doesn't come about through bullying and threatening people. He achieved nothing but probably high blood pressure. I have seen other attitudes in teams I have worked with that, whilst they are not quite as aggressive or extreme, were no less haughty.

Let's calm down and appreciate our fallibility. Admit our errors. State what we learned in the context of how we learned them. Let's be more tolerant of the honest failures of those work with. That is the only way we will receive forgiveness for our faults in return.

Sunday, 8 October 2017

On Testing Technocrats



The agile manifesto, written in 2001, states as one of its aims -

 "Individuals and interactions over processes and tools"

It is hard to imagine how in an agile team, where stakeholders, product managers, developers, testers, BAs and other groups work so closely together and much knowledge is tacit and undocumented, the above aim could possibly be ignored.

Software is ultimately used by people to implement solutions to problems people suffer from. It is created by people. The use cases and requirements that developers implement and testers test against are created by someone to reflect someone's (or some people's) wishes and needs. Testers test to find issues that we hope will never be discovered by people whose problems the software under test is built to solve.

...Which makes me annoyed about the idea that development/test teams can automate everything. The problems that bad software can cause for people are many and varied and the numbers and kinds of ways that a non-trivial application may fail are far greater, often more subjective than we can possibly plan for in advance. Requirements and specifications have subtle holes and areas of tacit knowledge that risk creating a product that does a wonderful job of something people don't actually want.

I am a big fan of test automation in its rightful place. As a regression tool it frees the tester from hours of tedious and often unfruitful checks to concentrate on those areas that require more exploration, analysis and thinking. It provides stubs and mocks so that the developer and tester can continue their work without the full integrated system being ready or available. It creates reams of test data of whatever attribute is necessary so that we can continue our work without laborious setup. It helps us perform checks with multitudes of simulated users to discern areas of poor performance. For all of the above however it doesn't replace the thinking mind of a competent test analyst. The kind who is adept at putting him or herself in the frame of the user, with all the complexities this involves.

But some of us feel that we can automate all of this away for 100% test coverage by automation, or that some future AI will make all non-automated test approaches redundant (not convinced that this will ever happen). I wonder, is it all about cost-cutting? The bottom line?

Or is there a type of person who thinks that the ambiguous and complex can be completely reduced to a set of checks and algorithms? That the human dimension, the outlook that human beings provide, can be abstracted away by technology? That what people see as quality can be reduced to a set of Yes and No answers. We hit the button, stand back and like the great tech sausage factory, we pump something in, our list of deviations comes out. Rinse and repeat with a few fixes and we get quality at the end...

I call these types the testing technocrats. By reducing our work to purely algorithms and checks to be done by machines - and quashing the thinking factor - they reduce the wishes and concerns of the users of our products to exactly that.

All in the hope of getting releases out faster, saving a bit of money and not to have to deal with the complex findings that a thinking human tester provides. This has been called out as wrong many times but often to deaf ears.

Test automation is an amazing thing that lets us achieve great efficiencies. It is not a replacement for the thinking human element. As testers we should be taking every effort to continue argue against those who believe it is.

10 minute blog - Our ideas don't exist in a vacuum

(The first in a series of very short, regular articles, no more than 10 minutes in conception and completion, fairly whimsical in nature and an exercise in  keeping in the habit of writing regularly and getting over short writer's blocks).

There is a school of thought that says that ideas come out of quiet and reflection. Ever since Siddhartha Gautama sat beside a tree, meditated and became Buddha, we think that we can quietly structure great ideas from base principles. Maybe if you are a philosophical genius, apart from that I don't believe a word of it.

In the last few months, as some have probably noticed, I have spent a fairly large (non-work hours if my boss is reading this 0:-) ) time on Twitter, reading and tweeting in the various testing threads and chats. I really enjoy doing it. I'm not sure I add much to the debate - I am anything but an expert or guru in testing - however if I didn't do it then I would struggle to have any ideas to write about. This blog would die a quiet death. Very few people will come up with a truly original idea - most articles are just variations on a theme - however the best ideas you will see these days are formed in and survive the cauldron of debate.

How can we risk our ideas being repudiated, shot down, publicly ridiculed, called out for BS? I don't think we can avoid it. Many of my ideas have been shot down or ignored - and that's fine because on retrospect some of them were shit anyway. However the alternative is not saying anything, and you miss all of the shots you don't take.

Saturday, 16 September 2017

On Testing this Pen

I am currently flying to Wellington, NZ to attend the WeTest 2017 Conference. I have just had two interviews last week for another placement with clients of my employer. It was while reflecting on this that a memory about one of my most early interview experiences came to me.

Years ago when I was a young, uncouth and very poor university graduate, I spent a year doing quite unglamourous jobs in Manchester, UK. The first of these was as an outbound telesales person "selling" credit cards over the phone. Suffice to say that I was a woeful salesman and after two weeks of utter mediocrity someone took pity on me and I was allowed move to a much less stressful data entry position with the same company.

What makes this story testing-blog worthy is the interview. The interviewer took a Bic biro and held it up in the air, asking me that most common of sales interview questions "Sell me this pen!"
I had never done sales before but the recruitment consultant who placed me had given me a primer on just this question. One isn't supposed to try to market the pen immediately. The interviewer hasn't yet stated what he or she wants in a pen and you may sell it all wrong. You ask questions about the interviewers' needs and circumstances - what documents will they write with it? What is their pen budget? How long do they want it to last? Will it be used on a paper surface, and what type? Does the interviewer like pen lids and clips that fit over a top pocket? ..and so on.

The candidate then looks at the pen's qualities with respect to the answers to the above and tries to find selling points in the pen that match the interviewer's needs. "You say you like pens cheap - nothing cheaper than a Bic".. "You don't want any of that leakage and filling up with ink hassle - not much of that with this biro!"... "You have a penchant for blue - here is a lovely blue pen!" etc..

Years later when I first started working in testing in London and meeting other testers at meetups, I did hear from others that it was common for a while for testing interviewers to take out a biro or ballpen and ask "(How would you) test this pen?" Nobody liked this question as it seemed obtuse and somewhat demeaning to ask this to an IT professional. It appears to have gone out of fashion and I have never been asked it and known of anyone else ask it in recent years. Nevertheless, as it does for the mindset of a salesperson, it does give the interviewer to gauge the approach and mindset of a candidate tester - especially a relatively inexperienced one.

How do candidate testers approach this question? Do they attack the pen with scenarios immediately - without knowing what the interviewer values in or wants to do with a pen or do they ask the right questions? Maybe the interviewer only likes things with the colour blue - the red biro you were given would be a severe no! Maybe there are multiple interviewers each with conflicting expectations of what their ideal pen would be lie - this could be explored further until some consensus. For writing signatures to formal letters to clients a fountain pen in order. To scribble notes into a notepad whilst exploratory testing, a biro or cheaper ballpen would do the job.

Does the tester then start scripting a set of test scenarios before testing? If the pen turns out to have no ink in it or the lid doesn't come off then most other tests will be blocked and it may be largely wasted effort. What about if the damn fickle interviewers want to change the pen requirements or don't have many requirements at all? Maybe a tester more inclined to an exploratory approach will have more luck. How would one approach that?

What sort of risks does the tester come up with? A terrible leakage accident? We could have a risk of that in your top pocket or in that vital signed release document! How about running out of ink at the worst moment? How about the lid being lost and ink drying up - maybe a clickbutton pen might be better!

What does the candidate suggest regarding edge cases? Can we test the pen on parchment? How about writing out the pen on a huge roll of paper until the ink runs out? How about subjecting it to 35-40 degree heat for those days when the air conditioning beaks - some pens may fail or leak in this temperature.

The interviewer may ask how the pen test result will be reported. A full test summary document? A simple set of pass/fail results? An extract from HPQC? A simple review meeting? What tools does the candidate say are required?

These are all largely facetious examples - however pondering on the points above is a huge part of what we testers do. A simple question, largely forgotten, can reveal so much....

Maybe it's time we started asking about how we test our pens again....

Wednesday, 13 September 2017

On Blogging - the Fears and the Inspiration

Whilst I don't write as many blog articles as I would like - and it sometimes takes a lot to get me started, I do immensely enjoy the act of writing tech and testing blog articles. The act that any tester, even someone as ordinary and relatively unknown as I, could write and self-publish (unedited by others) something that expresses personal thoughts and experiences related to tech - and yet without cost to me could be read by and stimulate thought and conversation for anybody in the world as soon as one posts it - is the kind of marvel that the great writers and philosophers of the past would have killed for. We take it for granted.

Nevertheless, it took me ages to overcome my fears about putting my thoughts out to the world. I had written blogs about other things that seemed more trivial in nature (My Another Sydney Blog about less touristy areas of Sydney was a good example) but writing out about Testing?!?

Fears I Had....

1) What about if I write something awful and contentious or get something wrong and end up vilified on Twitter?

2) What about if my current or future employer took offence at it?

3) Testing is still a landmine of arguments and fierce debate even today. What about if my experience didn't match up with some perceived glorious vision of modern testing practice - I'd look like some old fossil!

4) What do I have to say that the testing experts and gurus haven't already said? I'm just an average journeyman tester who had never spoken at a conference (at the time) or written a bestselling tech book, studied CS at Oxbridge or MIT or worked at Google. Who cares what I think?

5) I don't know how to write like a pro. Will people be interested?

...and others I have probably forgotten.

Of the fears above, some can be real issues whilst some are laughable and more indicative of my own issues with imposter syndrome at the time, however I am sure that they do put off others from sharing their thoughts and experience online.

So how did I get started? By chance actually. I went to a talk many years ago by the testing expert and prodigious blogger James Bach at Google Sydney - not long after reading his great book "Secrets of A Buccaneer Scholar", then having the pleasure of talking with him afterwards in person and by email about writing articles. He was extremely encouraging on the topic of blogging and if I hadn't met him it is quite likely that I would have never got started. I asked him what a tester should write about that hadn't already been said. His answer "Write about your experiences!" Perfect...

My first efforts were tentative and not great. I wrote a rather muddled and unsatisfactory article about ISO29119 - the impending software testing standard that ended up widely hated and disappeared. My next article, taking the de Montaigne approach, was a very personal article about my own Imposter Syndrome.

From my first few tentative blog articles I entered a period of fear and procrastination that lasted for over two years until I started writing again in early 2017. The last several months has been a period of experimenting with different writing styles and finding my own "voice" - which I am nowhere close to yet, however there has been improvement and an encouraging reception.

What about the fears I mentioned above, which caused so much hesitation and procrastination? None of them have materialised at all (thankfully).

1) I have made mistakes and written about contentious subjects but the feedback received has been overwhelmingly positive. Where criticism has been levelled, it has always been polite and constructive. I presume that for most new testing bloggers not writing controversy for its own sake, their feedback will also be civil.

2) Of course it is possible that your employer could take an issue with your blog article, however I think companies are generally supportive of their staff blogging as long as some details remain confidential. My employer has generally liked the blog and @TestingRants twitter handle and I have had likes and retweets from its social media (much appreciated).

3) Testing is a large enough field with diversity of practice for all types of experiences to be shared. For all the companies practicing agile, exploratory, devops, continuous integration, various levels of automation etc. there are still lots of companies taking traditional waterfall/V-Model approaches doing scripted manual tests (prepared, matched carefully with requirements, stored in HPQC to be approved by a BA or stakeholder beforehand). My last project was very similar to this. I do expect this to diminish over time however - even so, with the incredible rate of change in IT the future of testing and QA is unwritten. We can all write about our experiences without embarrassment.

4) This is probably the most laughable and mostly indicative of my struggle with imposter syndrome at the time. My experience is that if you put your thoughts out in a blog and make considered and rational points, people will read it and appreciate it - if only because the act of writing honestly about one's work is challenging. However we all have something others can learn from and nobody started off a testing expert. This was developed through years of experience and reflection. Also, whilst prestige does matter in IT to a degree the vast majority of dev and testing bloggers have never studied CS at Oxbridge or MIT or worked at Google and do just fine!

5) The reality is that your first set of articles will be woeful to middling. Everyone starts off like that and the chances we will ever truly write like a great a very slim anyway, however don't let that put you off. You will be struggling to find a writing style that suits you, and many times something to write about. Your content may be inspired or random more than considered - mine tends to be. You may look back at it and think "What the F**k was that?", however the reality is that when written from a position of personal experience and thinking about the field, your article will be interesting and useful to someone - and over time your following will grow as your confidence and skill grow.

So if you haven't yet started a blog, come and join us! We don't bite, and sometimes we even offer kind words and encouragement! Get started!

And one final note - Thanks James Bach for your kind words and encouragement at the beginning. They meant a lot.