SlideShare uma empresa Scribd logo
1 de 49
GayleL. McDowell | Founder/ CEO, CareerCup
gayle in/gaylemcdgayle
The Architecture of Interviews
Consistency+ Efficiency+ High Bar + Happiness
June7, 2016 | Talent42
&
candidates are
frustrated confused
gayle in/gaylemcdgayle 3Gayle Laakmann McDowell
They
Don’t
Know…
 Howmany interviews
 Who will be interviewing
 If they’ll code?How?
 What they need to know
 Howdecision gets made
 WHY?
Lotsofmyths
(andmisinformation)!
&
&
companies need
consistency efficiency
high bar happiness
Gayle Laakmann McDowell 5gayle in/gaylemcdgayle
Consistency & Efficiency
Consistency
 Outcome
 Process
 Questions
Efficiency
 Speedy process
 Able to expedite
 Minimal overhead
 Minimal false negatives
Gayle Laakmann McDowell 6gayle in/gaylemcdgayle
High Bar & Happiness
High Bar
 Minimize false positives
 Good, adaptable people
Happiness
 Enjoyable experience
 Makes company look good
 Transparency
7 gayle in/gaylemcdgayle
The Process
Resume Selection
Intro Call w/
Recruiter
Email that outlines
process
Code Assessment
Phone Interview
~4 onsite
interviews
Discussion &
Decision
“Sell” Call / Dinner
gayle in/gaylemcdgayle 8Gayle Laakmann McDowell
Stuff
I’ll
Discuss
 BarRaisersvs. Hiring Committees
 OfflineWork
 Homework vs code assessment tools
 QuestionStyle
 Knowledge, algorithms, pair programming
 Coding Platform
 Real code vs. pseudocode
 Whiteboard vs. computer
Bar Raisers or
Hiring Committees
So different, yet so similar
01
Gayle Laakmann McDowell 10gayle in/gaylemcdgayle
Bar Raisers andHC
Offer transparency
Offer consistency
Keepbar high
Facilitatechange
Can override manager
gayle in/gaylemcdgayleGayle Laakmann McDowell 11
HiringCommittee
Cons
 Overhead
 Delays
 Un-empowering
 Can feel “black box”
 Need good feedback
Pros
 Cross-company consistency
 Keeps barhigh
 Easierto improveprocess
Gayle Laakmann McDowell 12gayle in/gaylemcdgayle
Who’s it good for?
Companies that:
 See5or more devcandidatesperweek
 Wanttoimproveprocess
 Hireforcompany,notteam
 Arenotveryknowledgefocused
Easier to implement early!
gayle in/gaylemcdgayleGayle Laakmann McDowell 13
HiringCommittee: Best Practices
Meet at least 2x per week
Multiple HCs:
 Beware ofbarcreep /inconsistencies
Let interviewers observe HC
Traininterviewers to write feedback
Quality of decisions rests onfeedback
gayle in/gaylemcdgayleGayle Laakmann McDowell 14
Bar Raisers
Cons
 Need consistency across
company
 Need to scale team
Pros
 Many ofHC benefits:
 Consistency
 High bar
 Transparency
 But easierto implement
 No bottleneck
gayle in/gaylemcdgayleGayle Laakmann McDowell 15
Bar Raisers:Best Practices
 Select people who areinherently good
 Experiencedatinterviewing
 Nice, empathetic
 Smart&can challengecandidate
 Train them thoroughly
 Empowerthem
 Assign outside of team
 Watch out for scale/exhaustion!
Offline
Assessments
Homework, code assessment tools,
etc
02
Gayle Laakmann McDowell 17gayle in/gaylemcdgayle
OfflineAssessments
Homework Projects Code Assessment Tools
gayle in/gaylemcdgayleGayle Laakmann McDowell 18
Homework Projects
Big
Very Practical
Some love this
Lesscheating
 Except:algos
Too immediate
Needs eng time
Disproportionate workload
Scales poorly for candidate
gayle in/gaylemcdgayleGayle Laakmann McDowell 19
Homework: Best Practices
Show candidate
interestfirst
< 4 hours
 If >4, onsite project review
Architecture, not algorithms
Define review criteria
Avoid confusion with
company work
gayle in/gaylemcdgayleGayle Laakmann McDowell 20
Homework: Who It’s Good For
Language focused
 Low priority on algorithms / thought process
Experienced candidates (maybe)
gayle in/gaylemcdgayleGayle Laakmann McDowell 21
Code Assessment Tools
Fast, cheap eval
 Morecandidates
 Non-traditional
Sets expectations for onsite
Consistent data point
Cheating
May turn off senior
candidates
gayle in/gaylemcdgayleGayle Laakmann McDowell 22
ImplementationOptions
Everyone
Just your “maybe” candidates
Fast-Track
gayle in/gaylemcdgayleGayle Laakmann McDowell 23
Who It’s GoodFor
Small, mid-sized, and big companies
Value algorithms / problem solving
Lots of candidates
Want to look at non-traditional candidates
gayle in/gaylemcdgayleGayle Laakmann McDowell 24
Code Assessment: Best Practices
Show candidate interest
first
Beware of cheating
 (But nobiggie!)
Clearexpectations
Pick GREAT questions
 Similar to real interviews
 Unique questions
1 – 2 hour test
Question Style
Pair programming, algorithms,
knowledge
03
Gayle Laakmann McDowell 26gayle in/gaylemcdgayle
What ToAsk
Knowledge
Algorithms
Design/Architecture
Pairprogramming
Gayle Laakmann McDowell 27gayle in/gaylemcdgayle
Knowledge Questions
Good whenyou can’t train skilleasily
Best practice:
 In-depth,ifat all
 Keepita discussion
Gayle Laakmann McDowell 28gayle in/gaylemcdgayle
Algorithm Questions
Smartmatters.
Good for everyone
Best practices:
 Clear expectations with interviewers & candidates
 Ask medium-to-hard & unusual questions
Gayle Laakmann McDowell 29gayle in/gaylemcdgayle
Design/Architecture
Great for experienced candidates
Shows communicationskills
Best practice:
 Prepcandidates.Big unknown!
gayle in/gaylemcdgayleGayle Laakmann McDowell 30
PairProgramming
 Many candidates enjoy it
 Feels fair & real world
 Assesses codestyle / structure
 Shows interpersonal interaction
 Less understood
 Not greatfor algos
 Interviewer really matters
 Biased by tools
Gayle Laakmann McDowell 31gayle in/gaylemcdgayle
PairProgramming: Best Practices
 Prep/warn candidates
 Need GREAT interviewer
 Give choice of problems
 Okay/good to pick unreasonably big problems
 Guide candidates
 (Okaytoaskquestions,notknowtools,etc.)
Coding Platform
Whiteboard vs. Computers
04
Gayle Laakmann McDowell 33gayle in/gaylemcdgayle
Why We Make Them Code
Can theyput“thoughts”into “actions”?
Do they show good structure and style?
Do they thinkabout theimpact of decisions?
Why not pseudocode?
A Game with Secret Rules
… and this is for a
simple problem
Gayle Laakmann McDowell 36gayle in/gaylemcdgayle
Don’t Allow Pseudocode
Unpredictable playing field
Detailsmatter
If “real code” is too hard for them…
gayle in/gaylemcdgayleGayle Laakmann McDowell 37
How toCode
Big Practical Stuff
Use computer
Pair Programming
Small Stuff
Algorithm-focused
Computer or
whiteboard
gayle in/gaylemcdgayleGayle Laakmann McDowell 38
Buthow to code?
whiteboard computer
gayle in/gaylemcdgayleGayle Laakmann McDowell 39
A Case for Computers
 Realistic. Allows tools.
 Candidates feel more comfortable
 (Especially experienced &diversity candidates)
 Faster to write (often)
 Morecode
gayle in/gaylemcdgayleGayle Laakmann McDowell 40
The Downsideof Computers
Oftenwrite stupid stuff
Desperate attemptfor compilation
Communicationshutsdown
Biased by tools/laptop
“Transition” betweenalgorithm & code
gayle in/gaylemcdgayle 41
z
Gayle Laakmann McDowell
Computer
Best
Practices
Let candidate bring laptop
Instruct: not every detail
Encourage communication and
thinking
Recognize the bias!
gayle in/gaylemcdgayleGayle Laakmann McDowell 42
A Case for Whiteboards
Encourages thinking & communication
More language agnostic
Consistent across candidates
 Better laptop/tools doesn’t matter
It’s “standard”
gayle in/gaylemcdgayleGayle Laakmann McDowell 43
The Downsideof Whiteboards
Slow to write
Artificial environment
Can be intimidating
gayle in/gaylemcdgayle 44
z
Gayle Laakmann McDowell
Whiteboard
Best
Practices
Encourage shorthand
Be upbeat & encouraging
Reasonable expectations
gayle in/gaylemcdgayleGayle Laakmann McDowell 45
Recommendations
If skill-focused:
then Computer
If algos-focused:
then Whiteboard
If a little of each:
then Either/or
 Both can work!
 … with proper training
 Whynot let candidate choose?
Last Remarks
05
gayle in/gaylemcdgayleGayle Laakmann McDowell 47
Thingsto Consider
 BarRaisersor Hiring Committees
 Code assessmenttools
 Pairprogramming(forpracticalstuff)
 Whiteboard(orpick-your-poison)foralgorithmsstuff
there is no
perfect system
THANK YOU
gayle@gayle.com
gayle in/gaylemcdgayle

Mais conteúdo relacionado

Mais procurados

Mais procurados (7)

Bear off cube action
Bear off cube actionBear off cube action
Bear off cube action
 
Backgame
BackgameBackgame
Backgame
 
LLM avalanche June 2023.pdf
LLM avalanche June 2023.pdfLLM avalanche June 2023.pdf
LLM avalanche June 2023.pdf
 
PISA matemáticas: Construyendo bloques
PISA matemáticas: Construyendo bloquesPISA matemáticas: Construyendo bloques
PISA matemáticas: Construyendo bloques
 
Mochy's 10 Backgammon Quiz in Cyprus 2014
Mochy's 10 Backgammon Quiz in Cyprus 2014 Mochy's 10 Backgammon Quiz in Cyprus 2014
Mochy's 10 Backgammon Quiz in Cyprus 2014
 
Mastering Analytical Thinking: A Comprehensive Guide to Problem-Solving and D...
Mastering Analytical Thinking: A Comprehensive Guide to Problem-Solving and D...Mastering Analytical Thinking: A Comprehensive Guide to Problem-Solving and D...
Mastering Analytical Thinking: A Comprehensive Guide to Problem-Solving and D...
 
Matlab basic and image
Matlab basic and imageMatlab basic and image
Matlab basic and image
 

Semelhante a Architecture of Tech Interviews

Gayle Laakmann McDowell - Talent42 2015
Gayle Laakmann McDowell - Talent42 2015Gayle Laakmann McDowell - Talent42 2015
Gayle Laakmann McDowell - Talent42 2015
Talent42
 
Talent42 2014 Gayle Laakmann McDowell - Interviewing A- Players (1)
Talent42 2014 Gayle Laakmann McDowell -  Interviewing A- Players (1)Talent42 2014 Gayle Laakmann McDowell -  Interviewing A- Players (1)
Talent42 2014 Gayle Laakmann McDowell - Interviewing A- Players (1)
Talent42
 
How to Get a Job at Google
How to Get a Job at GoogleHow to Get a Job at Google
How to Get a Job at Google
Evisors
 

Semelhante a Architecture of Tech Interviews (20)

Architecture of interviews gayle laakmann mcdowell
Architecture of interviews   gayle laakmann mcdowellArchitecture of interviews   gayle laakmann mcdowell
Architecture of interviews gayle laakmann mcdowell
 
How to Hire Software Engineers: Best and Worst Practices
How to Hire Software Engineers: Best and Worst PracticesHow to Hire Software Engineers: Best and Worst Practices
How to Hire Software Engineers: Best and Worst Practices
 
Gayle Laakmann McDowell - Talent42 2015
Gayle Laakmann McDowell - Talent42 2015Gayle Laakmann McDowell - Talent42 2015
Gayle Laakmann McDowell - Talent42 2015
 
Creating the (Im)perfect Developer Interview
Creating the (Im)perfect Developer InterviewCreating the (Im)perfect Developer Interview
Creating the (Im)perfect Developer Interview
 
Prepping Your Engineering Candidates to Reduce Your False Negatives
Prepping Your Engineering Candidates to Reduce Your False NegativesPrepping Your Engineering Candidates to Reduce Your False Negatives
Prepping Your Engineering Candidates to Reduce Your False Negatives
 
Cracking the PM Interview
Cracking the PM InterviewCracking the PM Interview
Cracking the PM Interview
 
Cracking the Product Manager Interview
Cracking the Product Manager InterviewCracking the Product Manager Interview
Cracking the Product Manager Interview
 
Cracking the PM Interview
Cracking the PM InterviewCracking the PM Interview
Cracking the PM Interview
 
Hiring Great Product Managers
Hiring Great Product ManagersHiring Great Product Managers
Hiring Great Product Managers
 
Cracking the Coding interview (Abbreviated) - aug 2016
Cracking the Coding interview (Abbreviated) - aug 2016Cracking the Coding interview (Abbreviated) - aug 2016
Cracking the Coding interview (Abbreviated) - aug 2016
 
Conducting Effective Job Interviews.pptx
Conducting Effective Job Interviews.pptxConducting Effective Job Interviews.pptx
Conducting Effective Job Interviews.pptx
 
Talent42 2014 Gayle Laakmann McDowell - Interviewing A- Players (1)
Talent42 2014 Gayle Laakmann McDowell -  Interviewing A- Players (1)Talent42 2014 Gayle Laakmann McDowell -  Interviewing A- Players (1)
Talent42 2014 Gayle Laakmann McDowell - Interviewing A- Players (1)
 
Reverse Engineering Engineering Interviewing: How to Be a Great Interviewer
Reverse Engineering Engineering Interviewing: How to Be a Great InterviewerReverse Engineering Engineering Interviewing: How to Be a Great Interviewer
Reverse Engineering Engineering Interviewing: How to Be a Great Interviewer
 
Cracking the Coding Interview (Oct 2012)
Cracking the Coding Interview (Oct 2012)Cracking the Coding Interview (Oct 2012)
Cracking the Coding Interview (Oct 2012)
 
How to Get a Job at Google
How to Get a Job at GoogleHow to Get a Job at Google
How to Get a Job at Google
 
Why Methods Trump Methodology
Why Methods Trump MethodologyWhy Methods Trump Methodology
Why Methods Trump Methodology
 
Conversion Optimization Webninar with Peep Laja
Conversion Optimization Webninar with Peep Laja Conversion Optimization Webninar with Peep Laja
Conversion Optimization Webninar with Peep Laja
 
Conversion Optimization with Peep Laja
Conversion Optimization with Peep LajaConversion Optimization with Peep Laja
Conversion Optimization with Peep Laja
 
Tales from the Whiteboard
Tales from the WhiteboardTales from the Whiteboard
Tales from the Whiteboard
 
Greythorn Whiteboard Interview Guide
Greythorn Whiteboard Interview GuideGreythorn Whiteboard Interview Guide
Greythorn Whiteboard Interview Guide
 

Mais de Gayle McDowell

Cracking the Facebook Coding Interview
Cracking the Facebook Coding InterviewCracking the Facebook Coding Interview
Cracking the Facebook Coding Interview
Gayle McDowell
 

Mais de Gayle McDowell (7)

Cracking the Coding Interview - 7 steps - Udacity
Cracking the Coding Interview - 7 steps - UdacityCracking the Coding Interview - 7 steps - Udacity
Cracking the Coding Interview - 7 steps - Udacity
 
Cracking the Product Manager Interview
Cracking the Product Manager InterviewCracking the Product Manager Interview
Cracking the Product Manager Interview
 
Cracking the Algorithm & Coding Interview
Cracking the Algorithm & Coding InterviewCracking the Algorithm & Coding Interview
Cracking the Algorithm & Coding Interview
 
Cracking the Facebook Coding Interview
Cracking the Facebook Coding InterviewCracking the Facebook Coding Interview
Cracking the Facebook Coding Interview
 
Cracking the Coding Interview
Cracking the Coding InterviewCracking the Coding Interview
Cracking the Coding Interview
 
Transitioning from Engineering to Product Management
Transitioning from Engineering to Product ManagementTransitioning from Engineering to Product Management
Transitioning from Engineering to Product Management
 
Interviewing Great Developers: Reverse Engineering Interview Coaching to Crea...
Interviewing Great Developers: Reverse Engineering Interview Coaching to Crea...Interviewing Great Developers: Reverse Engineering Interview Coaching to Crea...
Interviewing Great Developers: Reverse Engineering Interview Coaching to Crea...
 

Último

Arjan Call Girl Service #$# O56521286O $#$ Call Girls In Arjan
Arjan Call Girl Service #$# O56521286O $#$ Call Girls In ArjanArjan Call Girl Service #$# O56521286O $#$ Call Girls In Arjan
Arjan Call Girl Service #$# O56521286O $#$ Call Girls In Arjan
parisharma5056
 
100%Safe delivery(+971558539980)Abortion pills for sale..dubai sharjah, abu d...
100%Safe delivery(+971558539980)Abortion pills for sale..dubai sharjah, abu d...100%Safe delivery(+971558539980)Abortion pills for sale..dubai sharjah, abu d...
100%Safe delivery(+971558539980)Abortion pills for sale..dubai sharjah, abu d...
hyt3577
 

Último (10)

Will Robots Steal Your Jobs? Will Robots Steal Your Jobs? 10 Eye-Opening Work...
Will Robots Steal Your Jobs? Will Robots Steal Your Jobs? 10 Eye-Opening Work...Will Robots Steal Your Jobs? Will Robots Steal Your Jobs? 10 Eye-Opening Work...
Will Robots Steal Your Jobs? Will Robots Steal Your Jobs? 10 Eye-Opening Work...
 
2k Shots ≽ 9205541914 ≼ Call Girls In Vinod Nagar East (Delhi)
2k Shots ≽ 9205541914 ≼ Call Girls In Vinod Nagar East (Delhi)2k Shots ≽ 9205541914 ≼ Call Girls In Vinod Nagar East (Delhi)
2k Shots ≽ 9205541914 ≼ Call Girls In Vinod Nagar East (Delhi)
 
Webinar - How to set pay ranges in the context of pay transparency legislation
Webinar - How to set pay ranges in the context of pay transparency legislationWebinar - How to set pay ranges in the context of pay transparency legislation
Webinar - How to set pay ranges in the context of pay transparency legislation
 
Arjan Call Girl Service #$# O56521286O $#$ Call Girls In Arjan
Arjan Call Girl Service #$# O56521286O $#$ Call Girls In ArjanArjan Call Girl Service #$# O56521286O $#$ Call Girls In Arjan
Arjan Call Girl Service #$# O56521286O $#$ Call Girls In Arjan
 
Perry Lieber Your Trusted Guide in the Dynamic World of Real Estate Investments
Perry Lieber Your Trusted Guide in the Dynamic World of Real Estate InvestmentsPerry Lieber Your Trusted Guide in the Dynamic World of Real Estate Investments
Perry Lieber Your Trusted Guide in the Dynamic World of Real Estate Investments
 
Cleared Job Fair Handbook | May 2, 2024
Cleared Job Fair Handbook  |  May 2, 2024Cleared Job Fair Handbook  |  May 2, 2024
Cleared Job Fair Handbook | May 2, 2024
 
RecruZone - Your Recruiting Bounty marketplace
RecruZone - Your Recruiting Bounty marketplaceRecruZone - Your Recruiting Bounty marketplace
RecruZone - Your Recruiting Bounty marketplace
 
Mercer Global Talent Trends 2024 - Human Resources
Mercer Global Talent Trends 2024 - Human ResourcesMercer Global Talent Trends 2024 - Human Resources
Mercer Global Talent Trends 2024 - Human Resources
 
Mastering Vendor Selection and Partnership Management
Mastering Vendor Selection and Partnership ManagementMastering Vendor Selection and Partnership Management
Mastering Vendor Selection and Partnership Management
 
100%Safe delivery(+971558539980)Abortion pills for sale..dubai sharjah, abu d...
100%Safe delivery(+971558539980)Abortion pills for sale..dubai sharjah, abu d...100%Safe delivery(+971558539980)Abortion pills for sale..dubai sharjah, abu d...
100%Safe delivery(+971558539980)Abortion pills for sale..dubai sharjah, abu d...
 

Architecture of Tech Interviews

  • 1. GayleL. McDowell | Founder/ CEO, CareerCup gayle in/gaylemcdgayle The Architecture of Interviews Consistency+ Efficiency+ High Bar + Happiness June7, 2016 | Talent42
  • 3. gayle in/gaylemcdgayle 3Gayle Laakmann McDowell They Don’t Know…  Howmany interviews  Who will be interviewing  If they’ll code?How?  What they need to know  Howdecision gets made  WHY? Lotsofmyths (andmisinformation)!
  • 5. Gayle Laakmann McDowell 5gayle in/gaylemcdgayle Consistency & Efficiency Consistency  Outcome  Process  Questions Efficiency  Speedy process  Able to expedite  Minimal overhead  Minimal false negatives
  • 6. Gayle Laakmann McDowell 6gayle in/gaylemcdgayle High Bar & Happiness High Bar  Minimize false positives  Good, adaptable people Happiness  Enjoyable experience  Makes company look good  Transparency
  • 7. 7 gayle in/gaylemcdgayle The Process Resume Selection Intro Call w/ Recruiter Email that outlines process Code Assessment Phone Interview ~4 onsite interviews Discussion & Decision “Sell” Call / Dinner
  • 8. gayle in/gaylemcdgayle 8Gayle Laakmann McDowell Stuff I’ll Discuss  BarRaisersvs. Hiring Committees  OfflineWork  Homework vs code assessment tools  QuestionStyle  Knowledge, algorithms, pair programming  Coding Platform  Real code vs. pseudocode  Whiteboard vs. computer
  • 9. Bar Raisers or Hiring Committees So different, yet so similar 01
  • 10. Gayle Laakmann McDowell 10gayle in/gaylemcdgayle Bar Raisers andHC Offer transparency Offer consistency Keepbar high Facilitatechange Can override manager
  • 11. gayle in/gaylemcdgayleGayle Laakmann McDowell 11 HiringCommittee Cons  Overhead  Delays  Un-empowering  Can feel “black box”  Need good feedback Pros  Cross-company consistency  Keeps barhigh  Easierto improveprocess
  • 12. Gayle Laakmann McDowell 12gayle in/gaylemcdgayle Who’s it good for? Companies that:  See5or more devcandidatesperweek  Wanttoimproveprocess  Hireforcompany,notteam  Arenotveryknowledgefocused Easier to implement early!
  • 13. gayle in/gaylemcdgayleGayle Laakmann McDowell 13 HiringCommittee: Best Practices Meet at least 2x per week Multiple HCs:  Beware ofbarcreep /inconsistencies Let interviewers observe HC Traininterviewers to write feedback Quality of decisions rests onfeedback
  • 14. gayle in/gaylemcdgayleGayle Laakmann McDowell 14 Bar Raisers Cons  Need consistency across company  Need to scale team Pros  Many ofHC benefits:  Consistency  High bar  Transparency  But easierto implement  No bottleneck
  • 15. gayle in/gaylemcdgayleGayle Laakmann McDowell 15 Bar Raisers:Best Practices  Select people who areinherently good  Experiencedatinterviewing  Nice, empathetic  Smart&can challengecandidate  Train them thoroughly  Empowerthem  Assign outside of team  Watch out for scale/exhaustion!
  • 17. Gayle Laakmann McDowell 17gayle in/gaylemcdgayle OfflineAssessments Homework Projects Code Assessment Tools
  • 18. gayle in/gaylemcdgayleGayle Laakmann McDowell 18 Homework Projects Big Very Practical Some love this Lesscheating  Except:algos Too immediate Needs eng time Disproportionate workload Scales poorly for candidate
  • 19. gayle in/gaylemcdgayleGayle Laakmann McDowell 19 Homework: Best Practices Show candidate interestfirst < 4 hours  If >4, onsite project review Architecture, not algorithms Define review criteria Avoid confusion with company work
  • 20. gayle in/gaylemcdgayleGayle Laakmann McDowell 20 Homework: Who It’s Good For Language focused  Low priority on algorithms / thought process Experienced candidates (maybe)
  • 21. gayle in/gaylemcdgayleGayle Laakmann McDowell 21 Code Assessment Tools Fast, cheap eval  Morecandidates  Non-traditional Sets expectations for onsite Consistent data point Cheating May turn off senior candidates
  • 22. gayle in/gaylemcdgayleGayle Laakmann McDowell 22 ImplementationOptions Everyone Just your “maybe” candidates Fast-Track
  • 23. gayle in/gaylemcdgayleGayle Laakmann McDowell 23 Who It’s GoodFor Small, mid-sized, and big companies Value algorithms / problem solving Lots of candidates Want to look at non-traditional candidates
  • 24. gayle in/gaylemcdgayleGayle Laakmann McDowell 24 Code Assessment: Best Practices Show candidate interest first Beware of cheating  (But nobiggie!) Clearexpectations Pick GREAT questions  Similar to real interviews  Unique questions 1 – 2 hour test
  • 25. Question Style Pair programming, algorithms, knowledge 03
  • 26. Gayle Laakmann McDowell 26gayle in/gaylemcdgayle What ToAsk Knowledge Algorithms Design/Architecture Pairprogramming
  • 27. Gayle Laakmann McDowell 27gayle in/gaylemcdgayle Knowledge Questions Good whenyou can’t train skilleasily Best practice:  In-depth,ifat all  Keepita discussion
  • 28. Gayle Laakmann McDowell 28gayle in/gaylemcdgayle Algorithm Questions Smartmatters. Good for everyone Best practices:  Clear expectations with interviewers & candidates  Ask medium-to-hard & unusual questions
  • 29. Gayle Laakmann McDowell 29gayle in/gaylemcdgayle Design/Architecture Great for experienced candidates Shows communicationskills Best practice:  Prepcandidates.Big unknown!
  • 30. gayle in/gaylemcdgayleGayle Laakmann McDowell 30 PairProgramming  Many candidates enjoy it  Feels fair & real world  Assesses codestyle / structure  Shows interpersonal interaction  Less understood  Not greatfor algos  Interviewer really matters  Biased by tools
  • 31. Gayle Laakmann McDowell 31gayle in/gaylemcdgayle PairProgramming: Best Practices  Prep/warn candidates  Need GREAT interviewer  Give choice of problems  Okay/good to pick unreasonably big problems  Guide candidates  (Okaytoaskquestions,notknowtools,etc.)
  • 33. Gayle Laakmann McDowell 33gayle in/gaylemcdgayle Why We Make Them Code Can theyput“thoughts”into “actions”? Do they show good structure and style? Do they thinkabout theimpact of decisions?
  • 35. A Game with Secret Rules … and this is for a simple problem
  • 36. Gayle Laakmann McDowell 36gayle in/gaylemcdgayle Don’t Allow Pseudocode Unpredictable playing field Detailsmatter If “real code” is too hard for them…
  • 37. gayle in/gaylemcdgayleGayle Laakmann McDowell 37 How toCode Big Practical Stuff Use computer Pair Programming Small Stuff Algorithm-focused Computer or whiteboard
  • 38. gayle in/gaylemcdgayleGayle Laakmann McDowell 38 Buthow to code? whiteboard computer
  • 39. gayle in/gaylemcdgayleGayle Laakmann McDowell 39 A Case for Computers  Realistic. Allows tools.  Candidates feel more comfortable  (Especially experienced &diversity candidates)  Faster to write (often)  Morecode
  • 40. gayle in/gaylemcdgayleGayle Laakmann McDowell 40 The Downsideof Computers Oftenwrite stupid stuff Desperate attemptfor compilation Communicationshutsdown Biased by tools/laptop “Transition” betweenalgorithm & code
  • 41. gayle in/gaylemcdgayle 41 z Gayle Laakmann McDowell Computer Best Practices Let candidate bring laptop Instruct: not every detail Encourage communication and thinking Recognize the bias!
  • 42. gayle in/gaylemcdgayleGayle Laakmann McDowell 42 A Case for Whiteboards Encourages thinking & communication More language agnostic Consistent across candidates  Better laptop/tools doesn’t matter It’s “standard”
  • 43. gayle in/gaylemcdgayleGayle Laakmann McDowell 43 The Downsideof Whiteboards Slow to write Artificial environment Can be intimidating
  • 44. gayle in/gaylemcdgayle 44 z Gayle Laakmann McDowell Whiteboard Best Practices Encourage shorthand Be upbeat & encouraging Reasonable expectations
  • 45. gayle in/gaylemcdgayleGayle Laakmann McDowell 45 Recommendations If skill-focused: then Computer If algos-focused: then Whiteboard If a little of each: then Either/or  Both can work!  … with proper training  Whynot let candidate choose?
  • 47. gayle in/gaylemcdgayleGayle Laakmann McDowell 47 Thingsto Consider  BarRaisersor Hiring Committees  Code assessmenttools  Pairprogramming(forpracticalstuff)  Whiteboard(orpick-your-poison)foralgorithmsstuff