The Challenges of BIG Testing: Automation, Virtualization, Outsourcing, and More

MB Full-day Tutorial

4/29/13 8:30AM

The Challenges of BIG Testing:

Automation, Virtualization,

Outsourcing, and More

Presented by:

Hans Buwalda

LogiGear

Brought to you by:

340 Corporate Way, Suite 300, Orange Park, FL 32073

888-268-8770 ∙ 904-278-0524 ∙ [email protected] ∙ www.sqe.com

Hans Buwalda

An internationally recognized expert in testing, Hans Buwalda is a pioneer of keyword-driven test automation, an approach now widely adopted throughout the testing industry. Originally from the Netherlands, Hans is the CTO of California-based LogiGear, directing the development of the successful Action Based Testing™methodology for keyword-driven test automation and its supporting TestArchitect™ toolset. Prior to joining LogiGear, Hans served as project director at CMG (now Logica). Hans speaks frequently at international conferences on concepts such as Soap Opera Testing, Three Holy Grails of Test Development, Testing in the Cold, and Jungle Testing. Hans is coauthor of Integrated Test Design and Automation: Using the TestFrame Method.

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© 2013 LogiGear Corporation. All Rights Reserved

Hans Buwalda

LogiGear

Automation, Virtualization,

Outsourcing, and More

STAREAST 2013, Tutorial MBOrlando, Monday April 29

The Challenges of

BIG Testing


Introduction

− industries

− roles in testing

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About LogiGear

� Software testing company, around since 1994

� Testing and test automation expertise, services and tooling− consultancy, training− test development and automation services− "test integrated" development services

� Aims to be thought leader, in particular for large and complex test projects

� Products:− TestArchitect™, TestArchitect for Visual Studio™− integrating test development with test management and automation− based on modularized keyword-driven testing

www.logigear.comwww.testarchitect.com


About Hans

� Dutch guy, living and working in California since 2001, as CTO of LogiGear

� Background in math, computer science, management

� Original career in management consultancy, since 1994 focusing on testing and test automation− keywords, agile testing, big testing, . . .

www.happytester.comhans @ logigear.com

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Topics for today

� Automation

� Designing and organizing tests

� Executing tests

� Team, organization and process

� Off-shoring, globalization


What is "BIG"

� Big efforts in development, automation, execution and/or follow up

� It takes a long and/or capacity to run tests (lot of tests, lot of versions, lot of configurations, ...)

� Scalability, short term and long term

� Complexity, functional, technical

� Number and diversity of players and stakeholders− pigs, chicken, elephants, ankle biters, ...

� Various definitions of "big" possible... and relevant...− "10 machines" or "10 acres"− "1000 tests" or "1000 weeks of testing"

� Big today means: big for you− "non trivial", you need to think about it

"Windows 8 has undergone more than 1,240,000,000 hours of testing"

Steven Sinofsky, Microsoft, 2012

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Existential Questions

� Why test?

� Why not test?

� Why automate tests?

� Why not automate tests?


Why test?

� People expect us to do

� Somebody wants us to

� Increases certainty and control − Showing absence of problems

� Finds faults, saving time, money, damage− Showing presence of problems

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Why not test?

� It costs time and money

� You might find problems . . .

� We forgot to plan for it

� We need the resources for development

� It is difficult

� It's hard to manage


Why Automate Tests?

� It is more fun

� Can save time and money− potentially improving time-to-market

� Can capture key application knowledge in a re-usable way

� Consolidates a structured way of working− when established as integral part of system

development process

� Can speeds up development life cycles

� Execution typically is more reliable− a robot is not subjective

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The Power of Robot Perception

FINISHED FILES ARE THE RE

SULT OF YEARS OF SCIENTI

FIC STUDY COMBINED WITH

THE EXPERIENCE OF YEARS...


Why not Automate?

� Can rule out the human elements− promotes "mechanical" testing− might not find "unexpected" problems

� More sensitive to good practices− pitfalls are plentiful

� Creates more software to manage

� Needs/uses technical expertise in the test team

� Tends to dominate the testing process− at the cost of good test development

maintenance can crush automation...

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Olny srmat poelpe can raed tihs.I cdnuolt blveiee taht I cluod aulaclty uesdnatnrd waht I was rdanieg. The phaonmneal pweor of the hmuan mnid, aoccdrnig to a rscheearch at Cmabrigde Uinervtisy, it deosn't mttaer in waht oredr the ltteers in a wrod are, the olny iprmoatnt tihng is taht the frist and lsat ltteer be in the rghit pclae. The rset can be a taotl mses and you can sitll raed it wouthit a porbelm. Tihs is bcuseae the huamn mnid deos not raed ervey lteter by istlef, but the wrod as a wlohe.

The Power of Human Perception


About tests in big projects

� Regular tests may be activities, complex tests are products. In fact any test that you want to run more than once is a product

� Every test that is written down with sufficient detail should be automated

� Automation− No longer an option in most situations− Also a key prerequisite of most agile approaches

� How tests are written and automated can make or break large scale testing

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Keywords, essential for scalability

� Distinguish tasks for test development and for automation

� The test developer creates tests using "actions" (my term)

� Each action consists of a keyword and arguments

� The automation task focuses on automating the actions

� Each action is automated only once

number name quantity

new product P-9009 Sledge Hammer 5

number quantity

add quantity P-9009 20add quantity P-9009 3add quantity P-9009 6

number quantity

check quantity P-9009 34

number name quantity

new product P-9009 Sledge Hammer 5

number quantity

add quantity P-9009 20add quantity P-9009 3add quantity P-9009 6

number quantity

check quantity P-9009 34

actions, each with a keyword and arguments

"34" is the expected value here

read from top to bottom

fragment from a test with actions


Potential benefits of keywords

� More tests, better tests− more breadth− more depth

� Fast, results can be quickly available− the design directly drives the automation

� Separates the tests from the technical scripting language− easier to involve business subject matter experts− the action format allows for easy readability

� Less efforts for automation− "script free" in most cases

� Automation more stable and maintainable− limited and manageable impact of changes in the system under test

� Develop tests more early in the life cycle− deal with execution details later

� . . .

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Risks of keywords

� Often seen as silver bullet, complications are underestimated− often treated as a technical "trick"− testers can get squeezed and marginalized

• developers and users dictating tests• automation engineers dictating actions

− or testers get the automation responsibility, thus becoming pseudo programmers

� The method needs understanding and experience to be successful− pitfalls are many, and can have a negative effect on the outcome

� Lack of method and structure can risk manageability− maintainability not as good as hoped− results can be disappointing, approach will be blamed


Case: International Financial Project

� One of the largest projects to date with action words

� Over 10000 windows, meant for use in 85 countries

� Long development cycle (400 pp, 4 years and counting)

� Maintenance very hard

� Testing major bottleneck

� Much investment in automation techniques were needed to become successful

� Also a lot of attention for team and work environment helped the success

� Team of 35 test developers, 2 automation engineers

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Keywords need a method

� By themselves keywords don't provide much scalability− they can even backfire and make automation more cumbersome− a method can help tell you which keywords to use when, and how to

organize the process

� Today we'll look at Action Based Testing (ABT)− addresses test management, test development and automation− large focus on test design as the main driver for automation success

� Central deliveries in ABT are the "Test Modules"− developed in spreadsheets− each test module contains "test objectives" and "test cases"− each test module is a separate (mini) project, each test module can

involve different stake holders


Example of an ABT test module

� Consists of an (1) initial part, (2) test cases and (3) a final part

� Focus is on readability, and a clear scope

� Navigation details are avoided, unless they're meant to be tested

TEST MODULE Car Rental Payments

user

start system john

TEST CASE TC 01 Rent some cars

first name last name car

rent car John Doe Ford Escape

rent car John Doe Chevvy Volt

last name amount

check payment Doe 140.4

FINAL

close application

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Example of a "low level" test module

� In "low level" tests interaction details are not hidden, since they are the target of the test

� The right level of abstraction depends on the scope of the test, and is an outcome of your test design process

TEST MODULE Screen Flow

user

start system john

TEST CASE TC 01 "New Order" button

first name control

click main new order

window

check window exists new order

FINAL

close application


Re-use actions to make new actions

� In the below example we use another sheet, but if you code actions, you could do something similar

� Often low level tests are re-used into these action definitions

ACTION DEFINITION check payment

user default value

argument last name Jones

argument amount

window control value

enter main last name # last name

window control

click main view balance

window control expected

check main balance # amount

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Action Based Testing

Test Development Plan

Test Cases

Test

Objectives

Test Module 1

Test Cases

Test

Objectives

Test Module 2

Test Cases

Test

Objectives

Test Module N

Actions

. . .

ACTION AUTOMATION

Break down

Automate


Case: Stock Exchange

� Transition from floor-based to screen-based trade

� Created on basis of an existing standard package− result: very little specifications

� Consisting of four major, different, systems that need to work in real-time

� Failures and bugs are not an option:− core of the financial system of the country, 100K revenue per second− traders not necessarily following rules

� In-depth knowledge limited to four people− nicknamed "The Four Daltons", after characters in a French comic book series about the

wild west− none of the four Daltons was involved in testing, testing was in a vacuum

� Three months to go...− test development (and scripted automation) had failed− test department not cooperating well with developers and domain experts− internal and external auditors had raised the alarm− and... the Dutch Crown Prince was scheduled to put the system into use!!

The Four Daltons(French comic book characters)

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Case: Stock Exchange

� Test set:− make it comprehensive− make it in-depth and aggressive− make it easy to assess and approve

� Organization:− get the right people involved (testing, automation, etc)− use scarce resources efficiently (in particular the four Daltons)− work with stake holders to let the process be transparent

� Technical:− use of the keyword method ("action words")− use "test objectives" so auditors can see quickly what you're testing− use great test design, don't mix apples and oranges

� "Sign off lubrication":− auditors signed off on the tests, not the test results− "the test is complete", not "the system works well"

� Results:− deadline was met one day before final date− the automated tests were the only ones used for acceptance− no functional errors found afterwards


Question

� What is wrong with the following pictures?

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No Y2K Problems in Auckland Airport??


Anything wrong with this instruction ?

You should change your battery or switch to outlet power immediately to keep from losing your work.

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Why Better Test Development?

� Many tests are often mechanical now− blindly follows specs or reqs− which often suits ok, but lacks aggression− no combinations, no unexpected situations− "methodical" does not have to mean "mechanical"

� For a higher “ambition level” you need− understanding of the system under test, and the business under test− analytical understanding of what could go wrong− creativity, and the commitment to use it

� Poor test development results in− cumbersome automation due to lack of focus− tedious retest cycles, loosing the agile advantage

Are your suffering from lame tests too?


Test Design

� Effective test breakdown (into test modules)− make sure every test module has a clear focus− keep different kinds and levels of tests separate

� Right level of actions− as “high level” if possible, hiding as many details as

much as possible− but not if the details are relevant for the test

It is my believe that successful automation is not a technical challenge. It is most of all a test design challenge.

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Case: A Financial Project

� Large project, with many consultants− embraced the approach− however, they were from our competitor

� One of the first with action words

� However, the project was confident about their test development, no help needed

� Result: many very hard to maintain tests, and way too many action words− crushing complexity− almost the end of the action words method− one memo saved the day


The Three “Holy Grails” of Test Design

� Metaphor to depict three main steps in test design

� Using "grail" to illustrate that there is no one perfect solution, but that it matters to pay attention (to search)

� About quality of tests, but most of all about scalability and maintainability in BIG projects

Right approach for each test module

Proper level of detail in the test specification

Organization of tests into test modules

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Case for organizing tests in BIG projects

� Can help keep the volume down

� Isolate the complexities

� Efficient and re-usable automation

� Deal with changing requirements

� For example: much of tested subject matter is not system specific, but business specific− a mortgage is a mortgage


What's the trick...

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What's the trick...

� Have or acquire facilities to store and organize you content

� Edit your stuff

� Decide where to put what− assign and label the shelves

� Put it there

� If the organization is not sufficient anymore, add to it or change it


Properties of a good Breakdown

� Test modules are well differentiated and clear in scope

� Reflects the level of tests

� Balanced in size and amount

� Modules are mutually independent

� Fit the priorities and planning of the project

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Breakdown Criteria

� Straightforward Criteria− Architecture of the system under test (client, server, protocol, sub

systems, components, modules, ...)− Functionality (customers, finances, management information, ...)− Kind of test (navigation flow, negative tests, response time, ...)− Ambition level (smoke test, regression, aggressive, P)

� Additional Criteria− Stakeholders (like "Accounting", "Compliance", "HR", ...)− Complexity of the test (put complex tests in separate modules)− Technical aspects of execution (special hardware, multi-station, ...) − Overall project planning (availability of information, timelines, sprints, ...)− Risks involved (extra test modules for high risk areas)


Example breakdown

� Tests of user interface− does function key F4 work− does listbox xyz the right values− is the tab order correct

� Form Tests, do all the forms (dialogs, screens, pages) work:− can data be entered and is it stored well− is displayed data correct− split these from everything else

� Function tests, do individual functions work− can I count the orders

� Alternate paths in use cases− can I cancel a transaction

� End-to-end tests− do all components of a system work well together in implementing the business processes− like enter sale order, then check inventory and accounting

� Tests with specific automation needs− like multi station tests

� Tests of non-UI functions

� High ambition level tests (aggressive tests)− can I break the system under test

� If in doubt: try high level first

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What is probably not a good design

� Navigational and functional tests are mixed− for example "over checking": a test of a premium calculation also

checks the existence of a window

� You have to change all of them for every new release of the system under test

� All test modules have a similar design

� Test modules are dependent on each other

� You can’t start developing any test modules early in the life cycle


Symptoms

� Tediousness in the test and test automation process

� No sense of control

� Complaining people

� Unnecessary high test maintenance− changes in the system under test impact many tests− hard to understand which tests need to be modified

� Difficulties in running any test− teams start "debugging" tests

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Example of an application under test

� Various item types− tests− actions− interface definitions− data sets− folders− ...

� Various operations− open− cut, copy, paste− check out− ...

� Various ways to initiate an operation− context menu, with or without accelerator key− main menu, with or without accelerator key− toolbar− short cut key− function key− drag and drop− double click− ....


Defining some modules

� Test modules for operations− primary and alternate paths− various values for fields like "comment" in check-in− paste in other projects− copy and paste various groups− not necessarily on each item type

� Test modules for items− address all item types at least once− on each item type perform each operation− not necessarily each variant of each operation

� UI handling− try for UI command if it starts the intended operation− not necessarily on each item type or operation variant

� Concurrency− try concurrency sensitive operations with multiple stations− in varying concurrency scenarios, with and without local "refreshes"− not necessarily each item type or operation variant− certainly not each UI command included

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Questions for Test Design

� Does your organization make something like a high level test design?

� If yes, how do you document it?


Case Study

� Large IT provider

� New version of one of their major web-sites

� Test scope was user acceptance test (functional acceptance)− the users were the “business owners”

� Development was off-shore

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Case Study

� Test development was done separate from automation− time-line for test development: May – Oct− time-line for automation (roughly): Jan – Feb

� All tests were reviewed and approved by the business owners− acceptance was finished by the end of the test

development cycle


Example of a Test Development Plan

Nr Module Business Owner Date to BO

1 Portal Navigation, Audience Robyn Peterson 05 / 232 Portal Navigation, Search Ted Jones 05 / 273 Membership, registration Steve Shao 06 / 034 Portal Navigation, Category Ted Jones 06 / 085 Portal Navigation, Topic and Expert Ted Jones 06 / 136 Access Control Mike Soderfeldt 06 / 177 Portal Navigation, Task Ted Jones 06 / 228 Contact DSPP Ted Jones 06 / 279 Portal search Mike Soderfeldt 07 / 0110 Membership, review and update Steve Shao 07 / 0511 Program contact assignment Alan Lai 07 / 1112 Company, registration Steve Shao 07 / 1413 Catalog, view and query Robyn Peterson 07 / 1914 Site map Ted Jones 07 / 2515 Membership, affiliation Steve Shao 07 / 2816 Learn about DSPP Ted Jones 08 / 0117 Products and services Steve Shao, Robyn Peterson 08 / 0818 What's new Ted Jones 08 / 1119 Company, life cycle Steve Shao, Alan Lai 08 / 1720 Specialized programs Ted Jones, Steve Shao 08 / 2221 Customer surveys Ted Jones 08 / 2922 Software downloads Mike Soderfeldt 09 / 0123 Newsletters Ted Jones 09 / 0624 Internationalization and localization Ted Jones 09 / 1325 Membership, life cycles Steve Shao 09 / 1926 Collaboration, forums Ted Jones 09 / 2327 Collaboration, blogs Mike Soderfeldt 09 / 2828 Collaboration, mailing lists Ted Jones 10 / 03

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Review Process with Stake Holders

Test Team sends draft Module to Stake Holder

Stake Holder reviews: - coverage

- correctness

Stake Holder returns notes:

- additions- corrections

Test Team receives and processes notes

changes needed?Stake Holder returns

notice of approval

Test Team marks the Module as "Final"

END

no

yes

START


Case Study, Results

� All tests were developed and reviewed on schedule− many notes and questions during test development phase

� The automation was 100% of the tests− all actions were automated, thus automating all test modules

� The test development took an estimated 18 person months− one on-shore resource, two off-shore resources

� The automation took between one and two months− focused on actions− most time was spent in handling changes in the interface (layout of pages

etc)

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Case: The French Director

� Mid size company

� Struggling under high pressure

� Testing of their main product, standard financial software

� Control and priority main issue

� Unfamiliar business culture

� Main instrument: module break down


Test Modules versus Test Cases

� The test module is a bigger unit in the test design− easier to identify− a chapter rather than a paragraph− easier to plan and manage, as a product (can be treated as part of product

backlog in scrum projects)

� Better flow of execution− each test case can set up for the next one− keep test modules independent, test cases can be dependent

� Test cases become creative output, rather than stifling input− avoids having to define all test cases at once early in the process

� Clear scope helps to identify cases, actions and checks− using "test objectives" to further detail scope− had a significant effect on maintainability

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"Thou Shall Not Debug Tests..."

� Large and complex test projects can be hard to "get to run"

� If they are however, start with taking a good look again at your test design...

� Rule of thumb: don't debug tests. If tests don't run smoothly, make sure:− lower level tests have been successfully executed first -> UI flow in the AUT

is stable− actions and interface definitions have been tested sufficiently with their own

test modules -> automation can be trusted− are you test modules not too long and complex?


Grail 2: Approach per Test Module

� Plan the test module:− when to develop: is enough specification available− when to execute: make sure the functionality at action level is well-

tested and working already

� Process:− do an intake: understand what is needed and devise an approach− analyze of requirements− formulate "test objectives"− create "test cases"

� Identify stakeholders and their involvement:− users, subject matter experts− developers− auditors

� Choose testing techniques if applicable:− boundary analysis, decision tables, transition diagrams, soap opera

testing, ...

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Eye on the ball, Scope

� Always know the scope of the test module

� The scope should be unambiguous

� The scope determines many things:− what the test objectives are− which test cases to expect− what level of actions to use− what the checks are about and which events should

generate a warning or error (if a “lower” functionality is wrong)


What I have seen not work

� "Over-Checking": having checks that don't fit the scope of the test

� Forcing data driven: making all tests data driven (variables, data files) without clear reason

� Combinatorial explosions: test all ... for all ... in all ...

� All actions high level (or all actions low level)

� Many tests for forms and dialogs, little tests for business processes

� Abundance of irrelevant comments, and lack of relevant comments

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Detail out the scope with test objectives

...TO-3.51 The exit date must be after the entry date...

test objective TO-3.51

name entry date exit date

enter employment Bill Goodfellow 2002-10-02 2002-10-01check error message The exit date must be after the entry date.


Examples of Testing Techniques

� Equivalence class partitioning− any age between 18 and 65

� Boundary condition analysis− try 17, 18, 19 and 64, 65, 66

� Error guessing− try Cécile Schäfer to test sorting of

a name list

� Exploratory− "Exploratory testing is

simultaneous learning, test design, and test execution", James Bach, www.satisfice.com

� Error seeding− deliberately injecting faults in a test

version of the system, to see if the tests catch them

− handle with care, don't let the bugs get into the production version

� Decision tables− define possible situations and the

expected responses of the system under test

� State transition diagrams− identify "states" of the system, and

have your tests go through each transition between states at least once

� Jungle Testing− focus on unexpected situations,

like hacking attacks

� Soap Opera Testing− describe typical situations and

scenarios in the style of episodes of a soap opera, with fixed characters

− high density of events, exaggerated

− make sure the system under test can still handle these

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"Jungle Testing"

� Expect the unexpected− unexpected requests− unexpected situations (often data oriented)− deliberate attacks− how does a generic design respond to a specific unexpected event?

� Difference in thinking− coding bug: implementation is different from what was intended/specified− jungle bug: system does not respond well to an unexpected situation

� To address− study the matter (common hack attacks, ...)− make a risk analysis− make time to discuss about it (analysis, brainstorm)− involve people who can know− use "exploratory testing" (see James Bach's work on this)− use an agile approach for test development− applies equally to testing, requirements, design

• testing should focus on the specific attacks

− consider randomized testing, like "monkey" testing


Soap Opera Testing

� Informal scenario technique to invite subject-matter experiences into the tests, and efficiently address multiple objectives

� Using a recurring theme, with “episodes”

� About “real life”

� But condensed

� And more extreme

� Typically created with a high involvement of end-users and/or subject-matter experts

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Lisa Crispin: Disorder Depot . . .

There are 20 preorders for George W. Bush action figures in "Enterprise", the ERP system, awaiting the receipt of the items in the warehouse.

Finally, the great day arrives, and Jane at the warehouse receives 100 of the action figures as available inventory against the purchase order. She updates the item record in Enterprise to show it is no longer a preorder.

Some time passes, during which the Enterprise background workflow to release preorders runs. The 20 orders are pick-released and sent down to the warehouse.

Source: Hans Buwalda, Soap Opera Testing (article), Better Software Magazine, February 2005


Then Joe loses control of his forklift and accidentally drives it into the shelf containing the Bush action figures. All appear to be shredded to bits. Jane, horrified, removes all 100 items from available inventory with a miscellaneous issue. Meanwhile, more orders for this very popular item have come in to Enterprise.

Sorting through the rubble, Jane and Joe find that 14 of the action figures have survived intact in their boxes. Jane adds them back into available inventory with a miscellaneous receipt.


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This scenario tests

• Preorder process

• PO receipt process

• Miscellaneous receipt and issue

• Backorder process

• Pick-release process

• Preorder release process

• Warehouse cancels


Vary your tests?

� Automated tests have a tendency to be rigid, and predictable

� Real-world situations are not necessarily predictable

� Whenever possible try to vary:− with select other data cases that still fit the goal of tests− with randomized behavior of the test

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Generation and randomization techniques

� Model-based− use models of the system under test to create tests− see: Harry Robinson, www.model-based-testing.org, and Hans Buwalda, Better

Software, March 2003

� Data driven testing− apply one test scenario to multiple data elements− either coming from a file or produce by an automation

� "Monkey testing"− use automation to generate random data or behavior− "smart monkeys" will follow typical user behavior, most helpful in efficiency− "dumb monkeys" are more purely random, may find more unexpected issues− long simulations can expose bugs traditional tests won't find

� Extended Random Regression− have a large database of tests− randomly select and run them, for a very long time− this will expose bugs otherwise hidden− see Cem Kaner e.a.: "High Volume Test Automation", StarEast 2004


Data Driven Testing

� Separate test logic from the data

� Possible origins for the data:− earlier steps in the test− data table− randomizer, or other formula− external sources, like a database query

� Use "variables" as placeholders in the test case, instead of hard values

� Data driven is powerful, but use modestly:− value cannot be known at test time, or changes over time− having many data variations is meaningful for the test

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Variables and expressions with keywords

� This test does not need an absolute number for the available cars, just wants to see if a stock is updated

� As a convention we denote an assignment with ">>"

� The "#" indicates an expression

TEST CASE TC 02 Rent some more cars

car available

get quantity Chevvy Volt >> volts




car expected

check quantity Chevvy Volt # volts - 2


Data driven testing with keywords

� The test lines will be repeated for each row in the data set

� The values represented by "car", "first" and "last" come from the selected row of the data set

DATA SET cars

car first last value

Chevvy Volt John Doe 40000

Ford Escape Mary Kane 22500

Chrysler 300 Jane Collins 29000

Buick Verano Tom Anderson 23000

BMW 750 Henry Smyth 87000

Toyota Corolla Vivian Major 16000

TEST CASE TC 03 Check stocks

data set

use data set /cars

car available

get quantity # car >> quantity


rent car # first # last # car

car expected

check quantity # car # quantity - 1

repeat for data set

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Combinations

� Input values− determine equivalence classes of values for a variable or field− for each class pick a value (or randomize)

� Options, settings

� Configurations− operating systems, operating system versions and flavors

• Windows service packs, Linux distributions

− browsers, browser versions− protocol stacks (IPv4, IPv6, USB, ...)− processors− DBMS's

� Combinations of all of the above

� Trying all combinations will spin out of control quickly


Pairwise versus exhaustive testing

� Group values of variables in pairs (or tuples with more than 2)

� Each pair (tuple) should occur in the test at least once− maybe not in every run, but at least once before you assume "done"− consider to go through combinations round-robin, for example pick a different

combination every time you run a build acceptance test− in a NASA study:

• 67 percent of failures triggered by a single value• 93 percent by two-way combinations, and • 98 percent by three-way combinations

� Example, configurations− operating system: Windows XP,

Apple OS X, Red Hat Enterprise Linux− browser: Internet Explorer, Firefox, Chrome− processor: Intel, AMD− database: MySQL, Sybase, Oracle− 72 combinations possible, to test each pair: 10 tests

� Example of tools: − ACTS from NIST, PICT from Microsoft, AllPairs from James Bach (Perl)− for a longer list see: www.pairwise.org

� These techniques and tool are supportive only. Often priorities between platforms and values can drive more informed selection

Source: PRACTICAL COMBINATORIAL TESTING, D. Richard Kuhn, Raghu N. Kacker, Yu Lei, NIST Special Publication 800-142, October, 2010

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Grail 3: Specification Level, choosing actions

� Scope of the test determines the specification level

� As high level as appropriate, as little arguments as possible− Use default values for non-relevant arguments

� Clear names (usually verb + noun usually works well)− to standardize action names: standardize both the verbs and the nouns, so

"check customer" versus "verify client" (or vice versa)− tests are not C++ code: avoid "technical habits", like mixed case and (worse)

underlines

� Manage the Actions

� Document the Actions

� By-product of the test design


Case: American Bank

� Project for a new teller system

� Large, state of the art

� Many system releases, many adjustments

� Need for very high level of automation

� Over 1 million test lines, in over 650 test modules

� Initially little attention paid to "holy grails"− UI and functional tests in the same modules− virtually un-maintainable, came close to killing the project− test design forced upon the team by a powerful stakeholder

who did not care much for methods...

� Emergency re-organization of the test modules− after system changes the tests would run again within a day

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Example of using actionsIn this real world example the first "sequence number" for teller transactions for a given day is retrieved, using a search function• the "#" means an expression, in this case a variable• the ">>" assign to a variable for use later on in the test

key

key navigate F7

key navigate 3

page tab

locate page tab Scan Criteria

w indow

wait for controls loaded search

text

check breadcrumb general functions > search

w indow control value

select search scan direction Backward

w indow control value

enter value search business date match # bus date

source control

click search go

w indow

wait for controls loaded search results

w indow control variable

get search results sequence number >> seq num


variable

get sequence number >> seq num

Example of using actionsIn this real world example the first "sequence number" for teller transactions for a given day is retrieved, using a search function• the "#" means an expression, in this case a variable• the ">>" assign to a variable for use later on in the test

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Mid level actions

� Most tests will have low level and high level actions− low level: generic operations, know the interface, don't know the functionality

• examples: "selection menu item", "expand tree node", ...

− high level: business oriented operations, know the functionality, don't know the interface

• examples: "enter purchase order", "check inventory of article"

� For complex forms (dialog) with many input fields consider using "mid level" actions− an argument for each field− for use in high level actions

� Examples of mid-level actions: − "enter address fields" − "check address fields"

enter customer

enter address fields

enter select set . . .. . .


Mapping an interface entity (like a window)

� An interface mapping will map windows and controls to names

� When the interface of an application changes, you only have to update this in one place

� The interface mapping is a key step in your automation success, allocate time to design it well

INTERFACE ENTITY balance inquiry

interface entity setting title Balance inquiry

ta name ta class label

interface element last name text Last name:

interface element first name text First name (optional):

interface element client id text Client id (optional):

ta name ta class caption

interface element view balance button View Balance

interface element close button Close

ta name ta class global pos

interface element balance label label 5

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Some Tips to Get Stable Automation

� Make the system under test automation-friendly

� Use "active" timing

� Test your automation

� Use automation to identify differences between versions of the system under test

� Keep an eye on the test design


� Look for properties a human user can't see, but a test tool can

� This approach is a must-do for speedier and more stable automation− interface mapping is often bottleneck, and source of maintenance problems− with predefined identifying property values an interface map can be created without "spy" tools− not sensitive to changes in the system under test− not sensitive to languages and localizations

� Examples:− "id" attribute for HTML elements− "name" field for Java controls− "AccessibleName" property in .Net controls (see below)

Automation-friendly design: hidden properties

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Active Timing

� Passive timing− wait a set amount of time− in large scale testing, try to avoid passive timing altogether:

• if wait too short, test will be interrupted• if wait too long, time is wasted

� Active timing− wait for a measurable event− usually the wait is up to a, generous, maximum time− common example: wait for a window or control to appear (usually the test tool

will do this for you)

� Even if not obvious, find something to wait for...

� Involve developers if needed− relatively easy in an agile team, but also in traditional projects, give this

priority

� If using a waiting loop− make sure to use a "sleep" function in each cycle that frees up the processor

(giving the AUT time to respond)− wait for an end time, rather then a set amount of cycles


Active Timing, your situation

� How much passive timing do you have in your scripts?

� If you're not sure, find out...

� ... and let me know

"First action I took upon my return was to evaluate the percentage of passive time in our code and found passive time 68% versus active time 32%. Needless to say our automation test cases were very expensive time operations and now I know why..."

Raed Atawneh, 2012 (extract)

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Things to wait for...

� Wait for a last control or elements to load− developers can help knowing which one that is

� Non-UI criteria− API function− existence of a file

� Criteria added in development specifically for this purpose, like:− "disabling" big slow controls (like lists or trees) until they're done loading− API functions or UI window or control properties

� Use a "delta" approach:− every wait cycle, test if there was a change; if no change, assume that the

loading time is over:− examples of changes:

• the controls on a window• count of items in a list• size a file (like a log file)


Alternatives to UI automation ("non-GUI")

� A GUI (Graphical User Interface) is only one example of an interface for interaction with a system under test

� Examples− HTTP and XML based interfaces, like REST− application programming interfaces (API’s)− embedded software− protocols− files, batches− databases− command line interfaces (CLI’s)− multi-media− mobile devices

� In many cases non-GUI automation is used since there simply is not GUI, but it can also often speed things up:− tends to be more straightforward technically, little effort needed to build up or maintain− once it works, it tends to work much faster and more stably than GUI automation

� In BIG testing projects routinely:− identify which non-GUI alternatives are available− as part of test planning: identify which tests qualify for non-GUI automation

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Technical Complexity

� Technology is another dimension that can make a project "complex"

� Examples:− graphics, charts, 3D, ...− hard to access systems, like embedded software, iOS, Flash,

dedicated hardware− difficult protocols, like SS7, transactions servers

� Approach: isolate the technical problems− embed in functions and actions− let experts look at them− tackle early in a project, since impact is large− once resolved, no longer center stage


The importance of innovation

� Large and complex testing projects pose many challenges

� Initial discussion of approach is a key requisite− thinking before doing− tackling technologies− agreeing on methods and practices− who does what, who needs to be involved− high level test design− debate the problems, not just the solutions

� However, also plan for continuous improvements− this is at the heart of agile thinking, and it applies very much to big testing− never stop thinking, "there is always one more trick"− share the tricks, other teams may like them too− improvements can apply to test design, to automation techniques, or even to

how to organize the work

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Tools that can help manage BIG projects

� Application Lifecycle Management (ALM)− abundant now, mainly on the wings of agile− very good for control, team cooperation, and traceability− often relate to IDE's (like Microsoft TFS and Visual Studio)− examples: Rally, Jira, TFS

� Test Managers− as separate tools on their way out− morphing into or replaced by ALM options− examples: HP Quality Center, Microsoft Test Manager

� Test development and automation tools− develop and/or automate tests

• these are not the same, automation tools are not always so good for test development− examples are HP Quick Test Pro, Borland Silk, Selenium, FitNesse, Microsoft Coded UI, and LogiGear's

TestArchitect and TestArchitect for Visual Studio (our own products)

� Build tools− succeed the traditional "make" tools− in particular "continuous build" tools combine "make" functionality with source control systems to rebuild

components that have changed, either continuously or on set times, like nightly− can very well also run related tests (unit and functional), and act on the results (stop build, report, etc)− examples: Hudson, Jenkins, TFS

� Bug trackers− not only register issues, but also facilitate their follow up, with workflow features− often also part of other tools, and tend to get absorbed now by the ALMs− Examples: BugZilla, Mantis, Trac


Tooling and Traceability

Reference item(ALM item, req, code module, ...)

Test Objective Test Case Execution Result

Test Module

Bug, issue

ALM, IDE,Project Mgr,

Req Mgr

Test Development ToolAutomation Tool

Execution ManagerContinous Build Tool

Issue TrackerALM

Testing

Trace back

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Test Execution

� Have an explicit approach for when and how to execute which tests

� Having a good high level test design will help to organize this

� Execution can be selective or integral− unit tests are typically executed selectively, possibly automatically

based on code changes in a system like SVN or TFS− for functional tests, decisions are needed:

• selective execution will be quicker and more efficient• integral execution may catch more issues ("bonus bugs")• generally extensive functional test execution will be related to releases, rather

than code check ins

− the ability to run "big testing" efficiently may determine how much can be done


Environments, configurations

� Many factors can influence details of automation− language, localization− hardware− version of the system under test− system components, like OS or browser

� Test design can reflect these− certain test modules are more general− others are specific, for example for a language

� But for tests that do not care about the differences, the automation just needs to "deal" with them− shield them from the tests

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Capture variations of the system under test in the actions and interface definitions, rather than in the tests (unless relevant there).Can be a feature in a test playback tool, or something you do with a global variable or setting.

Variation Variation Variation

"Variations"

"Master Switch"

Actions, Interface Definitions

. . .


Possible set up of variations

linked variation

keyworded variation

Specify for example in a dialog when you start an execution:

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Test Environments

� Physical• hardware• infrastructure• location• . . .

� Software• programs• data models• protocols• . . .

� Data• initial data• parameters / tables• . . .

• costs money• can be scarce

• configurations

• availability • manageability


Dealing with data

� Constructed data is easier to manage− can use automation to generate it, and to enter it in the environment− result of test analysis and design, reflecting "interesting" situations− however, less "surprises": real life situations which were not foreseen

� Real-world data is challenging to organize− make it a project, or task, in itself− make absolutely sure to deal with privacy, security and legal aspects

appropriately• study this, ask advice• apply appropriate "scrubbing"

� Consider using automation to select data for a test− set criteria ("need a male older than 50, married, living in Denver"),

query for matching cases, and select one randomly (if possible a different one each run)

− this approach will introduce variation and unexpectedness, making automated tests stronger and more interesting

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Unattended testing...

� When a test cannot pass, it can be:− a difference between expected and recorded values or behavior, as a result

of a check designed by the tester: this is a fail− the automation encounters a problem, like a window or control doesn't show,

that is not part of a check: this is an error

� An error can disrupt the test flow, and you may want to catch and handle it properly:− skip smaller or larger parts of the ongoing test− bring the system back in a known state (typically: close any open windows,

go to the main screen)− make sure the report clearly indicates these kind of problems, to avoid false

positives− example "on error action" that executes a predefined action that will do

recovery

� However, better is to avoid these situations− lots of efforts needed for unattended testing should raise questions about test

design or quality of the automation ("thou shall not debug tests")


"Known bug" problem

� Not uncommon in large scale systems− typically related to a version of the system under test

� A known bug may:− generate fails you want to ignore, also in statistics− throw off automation

� If many known bug situation occur, take another look at your high level test design

� One possible workaround, a "known bug" action:− other alternatives: conditionally ignore steps or single check points

version

known bug 1.1

...

end known bug

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Virtualization

� Virtual machines rather than physical machines− allow "guest" systems to operate on a "host" system− host can be Windows, Linux, etc, but also a specialized "hypervisor"− the hypervisor can be "hosted" or "bare metal"

� Main providers:− VMWare: ESX and ESXi− Microsoft: Hyper-V− Oracle/Sun: Virtual Box− Citrix: Xen (open source)

� Hardware support gets common now− processor, chipset, i/o− Like Intel's i7/Xeon

� For most testing purposes you need virtual clients, not virtual servers− most offerings in the market currently target virtual servers, particularly data centers

� Virtual clients will become more mainstream with the coming of VM's as part of regular operating systems− Windows 8: Hyper-V− Linux: KVM


Virtualization, a testers dream...

� In particular for functional testing

� Much easier to define and create needed configurations− you basically just need storage− managing this is your next challenge

� One stored configuration can be re-used over and over again

� The VM can always start "fresh", in particular with − fresh base data (either server or client)− specified state, for example to repeat a particular problematic automation

situation

� Can take "snap shots" of situations, for analysis of problems

� Can use automation itself to select and start/stop suitable VM's− for example using actions for this− or letting an overnight or continuous build take care of this

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Virtualization, bad dream?

� Performance, response times, capacities

� Virtual machine latency can add timing problems− see next slide− can be derailing in big test runs

� Management of images− images can be large, and difficult to store and move around

• there can be many, with numbers growing combinatorial style• configuration in the VM can have an impact, like fixed/growing virtual disks

− distinguish between managed configurations and sandboxes− define ownership, organize it− IT may be the one giving out (running) VM's, restricting your flexibility

� Managing running tests in virtual machines can take additional efforts on top of managing the VM's themselves− with the luxury of having VM's the number of executing machines can

increase rapidly− one approach: let longer running tests report their progress to a central

monitoring service (various tools have features for this)


Virtualization: "time is relative"

� Consider this waiting time loop, typical for a test script:− endTime = currentTime + maxWait− while not endTime, wait in 100 millisecond intervals

� When the physical machine overloads VM's can get slow or have drop outs, and endTime may pass not due to AUT latency− GetLocalTime will suffer from the latency− GetTickCount is probably better, but known for being unreliable on VM's

� Therefore tests that run smooth on physical machines, may not consistently do so on VM's. The timing problems are not easy to predict

� Possible approaches:− in general: be generous with maximum wait times if you can− don't put too many virtual machines on a physical box− consider a compensation algorithm, for example using both tick count and clock time

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Virtual machines, capacity

� Key to pricing is number of VM's that can run in parallel on a physical machine

� An automated test execution will typically keep a VM more busy than human use

� Factors in determining VM/PM ratio:− memory, for guest OS, AUT, test tooling− storage devices (physical devices, not disk images)− processors, processor cores− specific hardware support (becoming more common)

• processor, chipset, I/O

We started regression with 140 VMs.Very slow performance of

Citrix VM clients.


Building up virtualization

� Pay attention to pricing:− beefed up hardware can increase VM's/box ratio, but at a price− software can be expensive depending on features, that you may not

need

� In a large organization, virtual machines are probably available− make sure to allocate timely (which can be long before you get there

with your sprints)− keep in mind the capacity requirements

� Logical and physical management− which images, the wealth of possible images can quickly become

hard to see forest through the trees− physical management of infrastructure is beyond this tutorial

� Minimum requirement: snapshots/images− freeware versions don't always carry this feature− allow to set up: OS, environment, AUT, tooling, but also: data, states

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Infrastructure

� For large scale test execution this needs attention− physical infrastructure, but also how to use it

� Also consider managing infrastructure and test execution as a separate task− in or out of the team− avoid slowing down development (of system, test and/or

automation)


Remote execution, servers

� Allowing execution separately from the machines the testers and automation engineers are working on increases scalability

� Large scale text execution, in particular with VM's, like to have:− lots of processing power, lots of cores− lots of memory

� Test execution tends to care less about:− storage− networking

� Test execution facilities tend to be a bottle neck very quickly in big testing projects− the teams can use whatever they can get

� First step up: give team members a second machine

� Second step up: use servers, users coordinate their use of them

� Third step up: major infrastructures with organized allocation

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Tower Servers

� Smaller shops (smaller companies, departments)

� Affordable, simple, first step up from clients execution

� Not very scalable when the projects get larger


Rack Servers

� Well scalable

� Pricing not unlike tower servers

� Tend to need more mature IT expertise

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Server Blades

� Big league infrastructure, high density, very scalable

� Tends to be pricey, use when space and energy matters

� Usually out of sight for you and your team


Cloud

� Cloud can be target of testing− normal tests, plus cloud specific tests

• functional, load, response times

− from multiple locations− moving production through data centers

� Cloud can be host of test execution− considerations can be economical or organizational− providers offer imaging facilities, similar to virtual machines− make sure machines are rented and returned efficiently

� Public cloud providers like EC2 offer API's, so your automation can automatically allocate and release them− be careful, software bugs can have costing consequences− for example, consider having a second automation process to double-check cloud

machines have been released after a set time

� Note: public cloud is not taking of as fast as expected, cloud services, and private clouds, taking of much faster

(Xinhua Photo)

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Cloud Providers

Source: Jack of All Clouds, January 2011http://www.jackofallclouds.com/2011/01/state-of-the-cloud-january-201/


Cloud growth

� Growth of public clouds not as big as expected

� Cost benefits not necessarily convincing− low startup cost, but long ongoing cost

� See also: news.cnet.com/8301-13556_3-20063361-61.html

source: IDC forecast, 2010

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Cloud, example pricing, hourly rates

� Source: Amazon EC2 (my interpretation, actual prices may vary)

Linux Windows

Small 0.085 0.12 1.7 GB, 1 core (32 bits)

Large 0.34 0.48 7.5 GB, 4 cores

Extra Large 0.68 0.96 15 GB, 8 cores

High memory

Extra Large 0.50 0.62 17.1 GB, 6.5 core

Double Extra Large 1.00 1.24 34.2 GB, 13 cores

Quadruple Extra Large 2.00 2.48 68.4 GB, 26 cores

High CPU

Medium 0.17 0.29 1.7 GB, 5 core (32 bits)

Extra Large 0.68 1.16 7 GB, 20 cores


Cloud, example economy

� Not counting possible use of VM's within the buy option

� Also not counting: additional cost of ownership elements for owning or cloud (like IT management, contract and usage management)

� Impressions: − cloud could fit well for bursty testing needs, which is often the case− for full continuous, or very frequent, testing: consider buying− hybrid models may fit many big-testing situations: own a base capacity, rent

more during peak use periods

small large extra

Windows $0.12 $0.48 $0.96

buy (estimate) $300 $650 $900

hours to break even 2,500 1,354 938

months (24 / 7) 3.4 1.8 1.3

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Data centers can go down

However, disruption could have been minimized by using multiple data centers



This time, it did involve multiple data centers . . .

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Service providers can occasionally go down too


Cloud, usage for special testing needs

� Multi-region testing − Amazon for example has several regions

• US East, Northern Virginia• US West, Oregon, Northern California• EU, Ireland• Asia Pacific, Singapore, Tokyo• South America, Sao Paulo

− be careful that data transfers between regions costs money (0.01/GB)

� Load generation− example: "JMeter In The Cloud"

• based on the JMeter load test tool• uses Amazon AMI's for the slave machines• allows to distribute the AMI's in the different regions of Amazon• see more here:

aws.amazon.com/amis/jmeter-in-the-cloud-a-cloud-based-load-testing-environment

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Questions for Infrastructure

� What kind of infrastructure does your organization use for testing?

� What is the role of virtualization, now or in the future?

� Are you using a private or a public cloud for testing?


Example of a cloud system under test

� source: Windows Azure reference platform

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Approaches

� Automation does not have to be black box− for very big systems, a separate black box automation effort may not

be efficient− and building and keeping lab situations might be cumbersome− some simple hooks can greatly help already− remember... this is about automation, not test design.

� Make testability part of requirements and architecture− a key question should not just be "how do I design this", but "how do I

test this" (test design, automation)− some cloud/web systems are changed frequently, and tested "live"

• "Testing in Production (TiP)"

− allow redirection of some or all traffic through another version of a component or layer

� Example: reverse proxy's enabling A/B testing

see also: Ken Johnston's chapter in the book of Dorothy Graham and Mark Fewster, and his keynote at StarWest 2012


A/B testing with a reverse proxy

� Watch your test design, easy to drown in technical solutions only

� B could be a real-life user or also a keyword driven test machine

� A/B testing means part of traffic is routed through a different server or component (see if it works, and/or how users react)

� A similar strategy could be done at any component level

A

A

B

ReverseProxy

UsersServers

A

B

newcurrent

AB

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Organization

� Much of the success is gained or lost in how you organize the process− part of the teams− who does test design− who does automation− what to outsource, what to keep in-house

� Write a plan of approach for the test development and automation− scope, assumptions, risks, planning− methods, best practices− tools, technologies, architecture− stake holders, including roles and processes for input and approvals− team− . . .

� Assemble the right resources− testers, lead testers− automation engineer(s)− managers, ambassadors, ...

Test design is a skill . . .Automation is a skill . . . Management is a skill . . .

. . . and those skills are different . . .


Industrial Organization

� Large scale testing can move from a "design" to a "production" focus− mostly applies to test execution, but also seen for test development− this not black and white, both paradigms can occur in the same projects− this is often more easy to outsource than development

� A production organization is different a development organization− this is not unique for software− different professional culture− emphasis more on delivery and scale, "thinking big"− discipline rather than creativity, "get stuff done"− activities are like planning, control, logistics, information

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Task in "production" (test execution)

� Keeping the tests running

� Allocating resources

� Respond to hick-ups

� Analyze and address automation issues

� Address fails or other testing outcomes− including dealing with "known bugs"− part of a bigger team


Stake Holders

Test Development

Test Automation

Technology/Infrastructure

ProductionMarketing/Sales

System Development

End User Departments

Quality Assurance

Management

After Sales/Help Desk

Customers

Vendors

GovernmentAgencies

Publicity

EXTERNAL INTERNAL

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Team roles, examples

� Test development

� Automation

� Planning and managing the test runs

� Managing environments

� Managing infrastructure

� Dealing with stakeholders

� Analysis of results, and follow up

� Reporting


Test Development and Automation in sprints

Test ModuleDefinition(optional)

Test Module Development

Interface Definition

Action Automation

Test Execution

Sprint ProductsProduct Backlog

Test re-use

Automation re-use

product owner

teamprod owner & team

User storiesDocumentation

Domain understanding

Acceptance CriteriaPO Questions

SituationsRelations

Agile life cycle

Test development

Main Level Test Modules

Interaction Test Modules

Cross over Test Modules

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Test automation in sprints

� Try keep the main test modules at a similar level as the user stories and acceptance criteria

� Aim for "sprint + zero", meaning: try to get test development and automation "done" in the same sprint, not the next one− next one means work clutters up, part of team is not working on the

same sprint, work is done double (manually and automated), ...

� Make sure you can do the interface mapping by hand (using developer provided identifications)− can do earlier, before UI is finalized, and − recording of actions (not tests) will go better

� Also plan for additional test modules:− low-level testing of the interaction with the system under test (like

UI's)− crossing over to other parts of the system under test


Fitting in sprints

� Agree on the approach:− questions like does "done" include tests developed and automated?− do we see testing and automation as distinguishable tasks and

skillsets− is testability a requirement for the software

� Create good starting conditions for a sprint:− automation technology available (like hooks, calling functions, etc)− how to deal with data and environments− understanding of subject matter, testing, automation, etc

� Make testing and automation part of the evaluations

� Address tests and automation also in hardening sprints

� Just like for development, use discussions with the team and product owners to deepen understanding:− also to help identify negative, alternate and unexpected situations

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Testing as a profession

� "Do thorough acceptance testing, but not only by the customer"− source: "Agile Software Testing in a Large-Scale Project", Israeli Air

Force

� Focus on tests, not development:− what can be consequences of situations and events− relieve developers

� Knowledge and experience with testing techniques and principles

� The challenge for the tester in the new era is to become a more credible professional tester, − not a pseudo programmer− part of the team

� Forcing a nontechnical tester to become a programmer may lose a good tester and gain a poor programmer


Automation is a profession too

� Overlaps with regular system development, but not same

� Less concerned with complex code structures or algorithms

� More concerned with navigating through other software efficiently, dealing with control classes, obtaining information, timing, etc− if you would compare developers to "creators", automation engineers might

be likened to "adventurers"...

� The automation engineering role can also be a consultant:− for test developers: help express tests efficiently− for system developers: how to make a system more automation friendly − important player in innovation in the automated testing

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Questions for Organization

� How is your testing currently organized (who is doing what)?− test design− test development− automation− execution− assessment of release readiness

� Do you use agile? If yes, is there a role for a test professional? And for an automation professional?


Reporting

� Aim at needs:− avoid lengthy automated reports, have bottom line numbers− reports for stake holders− reporting for the team

� Reporting for a big testing project is about:− test and automation progress− production (running the tests)− results (aimed at system under test)

� Teams need (relevant) details− what happened, reproducibility, ...− either the tests, the automation, or the system under test− overall situations, with an ability to "drill down" to problem areas

� Management needs:− status, expectations, issues (realistic! bad news matter, you get punished for not telling)− bottom lines, plan versus reality confrontation− dates, efforts, used resources, costs, run times, ...− never allow planned numbers or dates to be "updated"

� Also for reporting, test organization is a key driver

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War rooms

� Helpful if response times are critical, and a need for cooperation, towards the same goal− similar grounds as for agile scrum rooms

� Set up at critical times, like before important deadlines, or during critical releases

� Can temporarily bring together multiple parties, that normally are not co-workers− like competitor vendors

� Pay attention to physical conditions− machines, monitors, white boards, meeting places, headsets, ...− food, drinks, ...

� The test execution cycle should match the needs of the war room approach− fast turnarounds− effortless− completeness− selective or integral

See also: "Your Game is Live, Now What?", Jane Fraser, Electronic Arts


Globalization....

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Main Challenges

� Other countries

� Distances

� Time differences


Globalization

� Three Challenges:− another countries, other cultures− geographic distances− time differences

� Seven "Patterns":− "Solution"− "Push Back"− "Time Pressure"− "Surprises"− "Ownership"− "Mythical Man Month"− "Cooperation"

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Challenge: Other Country


Other Country

� Differences in culture− more on the next slide...

� Different languages, and accents

� Differences in education− style, orientation and contents− position of critical thinking, factual knowledge, practice, theory,...− US, British, French, Asian, ...

� Differences in circumstances− demographics− economy, infrastructure− politics

� Apprehension on-shore and off-shore about job security doesn't help in projects− management responsibility: understand your strategic intentions, and their consequences, and clarify

them− be realistic in cost and benefit expectations

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More on Culture...

� Regional culture. There are numerous factors:− very difficult to make general statements

• many anecdotes, stories and perceptions, some are very helpful, some have limited general value

• not sure on impact of regional culture (see also [Al-Ani])− numerous factors, like history, religion, political system

• e.g. valuing of: critical thinking, theory, bottom-line, relations, status, work-ethic, bad news, saying 'no'

• entertaining guests, eating habits, alcohol, meat, humor, etc• position of leaders, position of women managers• mistakes can be benign and funny, but also damaging, visibly or hidden, in particular perceived

disrespect hurts

� Organizational culture− can be different from country to country, sector to sector, company to company, group to group− I feel this to be at least as strong than regional culture (see for example [Al-Ani])− you can have at least some control over this

� Professional cultures− for example engineers, QA, managers, ...

� Some ideas to help:− get to know each other (it helps, see for example [Gotel])− study the matter, and make adaptations


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Challenge: Distance

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Distance

� Continuous logistical challenges

� Lots of costs, and disruptions, for traveling

� Distance creates distrust and conflict− could be "normal" behavior, inherent to humans

� Complex coordination can create misunderstandings− on technical topics− on actions, priorities, and intentions


Challenge: Time difference

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Challenge: Time difference

� Additional complication for communication and coordination

� Places a major burden on both on-shore and off-shore staff− having to work evenings and/or early mornings− potential for exhaustion, lack of relaxation, mistakes, irritation

� Can easily lead to loss of time at critical moments

� Some solutions:− manage this actively− constantly seek to optimize task and responsibility allocation− build the on-shore and off-shore organizations to match− seek ways to save meeting time, like optimal information handling


Effect of time difference

Test Module: “Segment Y, Default Settings”

Windows Linux

TestArchitect 5 ~ 4:16 m ~ 4:28 m

TestArchitect 6 ~ 11:00 m ~ 8:00 m

Report from the team to the US management . . .

Performance comparison TestArchitect 5 and 6

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Patterns

� Experiences seem to follow patterns− at least our own experiences do− variations are numerous, but seem to follow similar lines− following are examples, not limitative

� It can help to recognize patterns quickly, and act upon them

� Resolutions have side-effects, can introduce new issues− for example strengthening local management means less direct

contact with the project members doing the work

� Just about every pattern occurs in every direction− from your perspective regarding "them"− their perspective on you, or each other− sometimes equaling, sometimes mirroring


Pattern: "The Solution"

� Typical sequence of events:− the team finds a problem in running a test− the team discusses it and comes up with a "solution"− the solution: (1) creates issues, and (2) hides the real

problem

� Better way:− define as an issue− discuss with project manager and customer

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Pattern: "Push Back"

� US side, or customer, gives bad direction

� Team doesn't like it, but feels obliged to follow orders

� The result is disappointing

� Team is blamed− and will speak up even less next time

� Better way:− discuss with the principal/customer at multiple levels

• strategic about direction, operational day-to-day

− empower and encourage the team to speak up− write plans of approach, and reports


Pattern: "Time Pressure"

� Deadline must be met− no matter what− use over-time− "failure is not an option"

� Deadlines are sometimes real, sometimes not− become a routine on the US side− easy to pressure over the email− very difficult for a non-empowered team to push back− risk: inflation of urgency

� Better way:− good planning− proper weighing of deadlines and priorities− frequent reporting− local management

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Pattern: "Surprises"

� Good news travels better than bad news...− should be the other way around− the "cover up": "let's fix, no need to tell...."− over time: needing bigger cover ups to conceal

smaller ones− not unique for off-shoring, but more difficult to

detect and deal with

� Once a surprise happens:− you will feel frustrated, and betrayed− fix the problems, point out the consequences of

hiding, avoid screaming and flaming

� Better ways:− agree: NO SURPRISES!!− emphasize again and again− train against this− continuously manage, point out− the magic word: transparency

SUPRISES


Pattern: "Ownership"

� Shared responsibility is no responsibility

� Effort-based versus result-based

� On-shore players feel the off-shore team has a result responsibility

� Off-shore team members feel an effort-based responsibility ("work hard")

� Better way:− clear responsibilities and expectations− on-shore ownership for quality control of system under test

• and therefore the tests

− off-shore ownership of producing good tests and good automation− empower according to ownership

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Pattern: "Mythical Man Month"

� Fred Brooks classic book, "Mythical man month":− "Assigning more programmers to a project running behind schedule

will make it even later"− "The bearing of a child takes nine months, no matter how many

women are assigned"

� In test automation, there must be clear ownership of:− test design (not just cranking out test cases)− automation, this is different skill and interest

� Assign at least the following roles:− project lead, owns quality and schedule− test lead: owns test design, coaches and coordinates the other testers− automation: make the actions work (assuming ABT, not the test

cases)

� Define distinct career paths in: testing, automation, management


Pattern: "Cooperation"

� Communication is tedious, takes a long time

� Questions, questions, questions, ...− reverse: questions don't get answered

� For at least one side in private time, extra annoying

� Misunderstandings, confusion, actions not followed up− double check apparent "crazy things" with the team before jumping to conclusions, and

actions (assume the other side is not "nuts" or "dumb"...)

� Please understand: distance fosters conflicts− we're born that way, be ready for it

� Better ways:− prioritize training, coaching, preparation and planning. Saves a lot of questions...− write stuff down, use briefs, minutes− define workflows and information flows

• buckets, reporting, select and use good tools

− specialize meetings• table things for in-depth meetings• ask to meet internally first

− be quick, no more than 30 mins

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Cooperation


Training, some ideas

� Many areas, big pay-offs:− system under test− subject matter under test, domain knowledge− methods, best practices− technologies, tools, ...− processes− soft skills, like creativity, critical thinking, management, ...− language− cross-cultural

� Have exams− think about the consequences of passing and failing− teams pay more attention when they know they will get tested− you will know whether you were understood

� Also have coaching and train-the-trainers− more experienced people help newbie's− also runs a risk: bad habits can creep in and procreate− "Tribal knowledge", learning by osmosis, water cooler conversations, encourage it− consider "special interest groups (SIG's)"

� Rule of thumb for off-shore teams: hire for technical knowledge, train for business knowledge

� The on-shore staff needs training and coaching too

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Additional ideas

� Go there, be with the team, experience yourself how "your side" is doing− I go about twice per year

� Manage ownership, is it you or them− the distinction between efforts and results

� Provide clear direction, constant attention and coaching

� Supervise, supervise, supervise− but don't micromanage if the other side has ownership

� Ask to create example products (like ABT test modules and actions), review them carefully, and use as direction for subsequent work

� Leadership style: participative styles seem most common (as opposed to consensus or authoritative, see also [Al-Ani])

� Organize informal/fun events, provide a good environment− solidify the group, improve retention− include visiting US staff, this tends to do a lot of good ("priceless")

� Manage expectations− stuff takes time and energy− differences can be addressed, but not 100%

cake...


Outsourcing and Agile

� If done well, can provide relieve to a lot of the patterns

� Several models possible

� Model 1: Full team outsourcing− development, testing and automation

� Model 2: "2nd unit"− off-shore team works under control of sprint team members

� Model 3: Part of integrated team:− needs online tool like Jira or Rally− you must have shared meetings− advantage: more project time

� Large scale test development and automation might be easier to outsource than development

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Summary

� Not all "big project" challenges are the same

� Think before you do. Best results come from planning well, and combining effective concepts, tricks and tools

� Consider tests and automation as products

� Team work is a key for short term and long term success

� There are many options for infrastructure, but keep an eye on economy and planning

� Off-shoring can help scale up, but needs attention to do it right, in particular communication

Repeat of initial invitationFocus today was on overview and concepts, not always on details. Please see me in person for any discussion you would like on your situation that I didn't cover. We're also exhibiting here, probably easiest to reach me there.


Homework . . .

1. Testing Computer Software, Cem Kaner, Hung Nguyen, Jack Falk, Wiley

2. Lessons Learned in Software Testing, Cem Kaner, James Bach, Bret Pettichord, Wiley

3. Experiences of Test Automation, Dorothy Graham, Mark Fewster, Addison Wesley, 2012

4. Automating Software Testing, Dorothy Graham, Mark Fewster, Addison Wesley

5. "Build a Successful Global Training Program", Michael Hackett, www.logigear.com

6. Action Based Testing (overview article), Hans Buwalda, Better Software, March 2011

7. Action Figures (on model-based testing), Hans Buwalda, Better Software, March 2003

8. Integrated Test Design & Automation, Hans Buwalda, Dennis Janssen and Iris Pinkster, Addison Wesley

9. Soap Opera Testing (article), Hans Buwalda, Better Software Magazine, February 2005

10. Testing with Action Words, Abandoning Record and Playback, Hans Buwalda, Eurostar 1996

11. QA All Stars, Building Your Dream Team, Hans Buwalda, Better Software, September 2006

12. The 5% Solutions, Hans Buwalda, Software Test & Performance Magazine, September 2006

13. Happy About Global Software Test Automation, Hung Nguyen, Michael Hackett, e.a., Happy About

14. Testing Applications on the Web, Hung Nguyen, Robert Johnson, Michael Hackett, Wiley

15. Practical Combinatorial Testing, Richard Kuhn, Raghu Kacker, Yu Lei, NIST, October, 2010

16. Agile Software Testing in a Large-Scale Project, David Talby, Arie Keren, Orit Hazzan, Yael Dubinsky, IEEE Software, July/August 2006

17. JMeter in the Cloud, Jörg Kalsbach, http://aws.amazon.com/amis/2924

18. Using Monkey Test Tools, Noel Nyman, STQE issue January/February 2000

19. High Volume Test Automation, Cem Kaner, Walter P. Bond, Pat McGee, StarEast 2004

20. Descriptive Analysis of Fear and Distrust in Early Phases of GSD Projects, Arttu Piri, Tuomas Niinimäki, Casper Lassenius, 2009 Fourth IEEE International Conference on Global Software Engineering [Piri]

21. Quality Indicators on Global Software Development Projects: Does 'Getting to Know You' Really Matter?Olly Gotel, Vidya Kulkarni, Moniphal Say, Christelle Scharff, Thanwadee Sunetnanta, 2009 Fourth IEEE International Conference on Global Software Engineering [Gotel]

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Thanks...

� Please fill out the evaluation form, from the back of the book

� Let me know any questions or concerns:

� We're at the expo, questions welcome− I will be there myself too quite a bit

TESTING FOR SALE

Supersize your testsfor less...

email: hans @ logigear.com

articles: www.happytester.com

company: www.logigear.com

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The Challenges of BIG Testing: Automation, Virtualization, Outsourcing, and More

Technology

Transcript of The Challenges of BIG Testing: Automation, Virtualization, Outsourcing, and More