oh, no! validation bingo!. algorithm complexity analysis

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oh, no! validation bingo!

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Page 1: Oh, no! validation bingo!. algorithm complexity analysis

oh, no! validation bingo!

Page 2: Oh, no! validation bingo!. algorithm complexity analysis

oh, no! validation bingo!

• algorithm complexity analysis

Page 3: Oh, no! validation bingo!. algorithm complexity analysis

oh, no! validation bingo!

• algorithm complexity analysis• field study with target user population

Page 4: Oh, no! validation bingo!. algorithm complexity analysis

oh, no! validation bingo!

• algorithm complexity analysis• field study with target user population• implementation performance (speed, memory)

Page 5: Oh, no! validation bingo!. algorithm complexity analysis

oh, no! validation bingo!

• algorithm complexity analysis• field study with target user population• implementation performance (speed, memory)• informal usability study

Page 6: Oh, no! validation bingo!. algorithm complexity analysis

oh, no! validation bingo!

• algorithm complexity analysis• field study with target user population• implementation performance (speed, memory)• informal usability study• laboratory user study

Page 7: Oh, no! validation bingo!. algorithm complexity analysis

oh, no! validation bingo!

• algorithm complexity analysis• field study with target user population• implementation performance (speed, memory)• informal usability study• laboratory user study• qualitative discussion of result pictures

Page 8: Oh, no! validation bingo!. algorithm complexity analysis

oh, no! validation bingo!

• algorithm complexity analysis• field study with target user population• implementation performance (speed, memory)• informal usability study• laboratory user study• qualitative discussion of result pictures• quantitative metrics

Page 9: Oh, no! validation bingo!. algorithm complexity analysis

oh, no! validation bingo!

• algorithm complexity analysis• field study with target user population• implementation performance (speed, memory)• informal usability study• laboratory user study• qualitative discussion of result pictures• quantitative metrics• requirements justification from task analysis

Page 10: Oh, no! validation bingo!. algorithm complexity analysis

oh, no! validation bingo!

• algorithm complexity analysis• field study with target user population• implementation performance (speed, memory)• informal usability study• laboratory user study• qualitative discussion of result pictures• quantitative metrics• requirements justification from task analysis• user anecdotes (insights found)

Page 11: Oh, no! validation bingo!. algorithm complexity analysis

oh, no! validation bingo!

• algorithm complexity analysis• field study with target user population• implementation performance (speed, memory)• informal usability study• laboratory user study• qualitative discussion of result pictures• quantitative metrics• requirements justification from task analysis• user anecdotes (insights found)• user community size (adoption)

Page 12: Oh, no! validation bingo!. algorithm complexity analysis

oh, no! validation bingo!

• algorithm complexity analysis• field study with target user population• implementation performance (speed, memory)• informal usability study• laboratory user study• qualitative discussion of result pictures• quantitative metrics• requirements justification from task analysis• user anecdotes (insights found)• user community size (adoption)• visual encoding justification from theoretical principles

Page 13: Oh, no! validation bingo!. algorithm complexity analysis

split threats to validity into four levels

Page 14: Oh, no! validation bingo!. algorithm complexity analysis

split threats to validity into four levels

domain problem characterization

• wrong problem• they don’t do that

Page 15: Oh, no! validation bingo!. algorithm complexity analysis

split threats to validity into four levels

domain problem characterization

data/operation abstraction design

• wrong problem• they don’t do that

• wrong abstraction• you’re showing them the wrong thing

Page 16: Oh, no! validation bingo!. algorithm complexity analysis

split threats to validity into four levels

domain problem characterization

data/operation abstraction design

encoding/interaction technique design

• wrong problem• they don’t do that

• wrong abstraction• you’re showing them the wrong thing

• wrong encoding/interaction technique• the way you show it doesn’t work

Page 17: Oh, no! validation bingo!. algorithm complexity analysis

split threats to validity into four levels

domain problem characterization

data/operation abstraction design

encoding/interaction technique design

algorithm design

• wrong problem• they don’t do that

• wrong abstraction• you’re showing them the wrong thing

• wrong encoding/interaction technique• the way you show it doesn’t work

• wrong algorithm• your code is too slow

Page 18: Oh, no! validation bingo!. algorithm complexity analysis

validate according to threatthreat: wrong problem threat: bad data/operation abstraction threat: ineffective encoding/interaction technique threat: slow algorithm

implement system

Page 19: Oh, no! validation bingo!. algorithm complexity analysis

validate according to threatthreat: wrong problem validate: observe and interview target users threat: bad data/operation abstraction threat: ineffective encoding/interaction technique threat: slow algorithm

implement system validate: observe adoption rates

Page 20: Oh, no! validation bingo!. algorithm complexity analysis

validate according to threatthreat: wrong problem validate: observe and interview target users threat: bad data/operation abstraction threat: ineffective encoding/interaction technique threat: slow algorithm

implement system validate: test on target users, collect anecdotal evidence of utility validate: field study, document human usage of deployed system validate: observe adoption rates

Page 21: Oh, no! validation bingo!. algorithm complexity analysis

validate according to threatthreat: wrong problem validate: observe and interview target users threat: bad data/operation abstraction threat: ineffective encoding/interaction technique validate: justify encoding/interaction design threat: slow algorithm

implement system validate: qualitative/quantitative result image analysis [test on any users, informal usability study] validate: lab study, measure human time/errors for operation validate: test on target users, collect anecdotal evidence of utility validate: field study, document human usage of deployed system validate: observe adoption rates

Page 22: Oh, no! validation bingo!. algorithm complexity analysis

validate according to threatthreat: wrong problem validate: observe and interview target users threat: bad data/operation abstraction threat: ineffective encoding/interaction technique validate: justify encoding/interaction design threat: slow algorithm

validate: analyze computational complexity implement system validate: measure system time/memory validate: qualitative/quantitative result image analysis [test on any users, informal usability study] validate: lab study, measure human time/errors for operation validate: test on target users, collect anecdotal evidence of utility validate: field study, document human usage of deployed system validate: observe adoption rates

Page 23: Oh, no! validation bingo!. algorithm complexity analysis

threat: wrong problem validate: observe and interview target users threat: bad data/operation abstraction threat: ineffective encoding/interaction technique validate: justify encoding/interaction design threat: slow algorithm

validate: analyze computational complexity implement system validate: measure system time/memory validate: qualitative/quantitative result image analysis [test on any users, informal usability study] validate: lab study, measure human time/errors for operation validate: test on target users, collect anecdotal evidence of utility validate: field study, document human usage of deployed system validate: observe adoption rates

don’t do them all in any single paper

Page 24: Oh, no! validation bingo!. algorithm complexity analysis

threat: wrong problem validate: observe and interview target users threat: bad data/operation abstraction threat: ineffective encoding/interaction technique validate: justify encoding/interaction design threat: slow algorithm

validate: analyze computational complexity implement system validate: measure system time/memory validate: qualitative/quantitative result image analysis [test on any users, informal usability study] validate: lab study, measure human time/errors for operation validate: test on target users, collect anecdotal evidence of utility validate: field study, document human usage of deployed system validate: observe adoption rates

match up with level of contributions!

Page 25: Oh, no! validation bingo!. algorithm complexity analysis

threat: wrong problem validate: observe and interview target users threat: bad data/operation abstraction threat: ineffective encoding/interaction technique validate: justify encoding/interaction design threat: slow algorithm

validate: analyze computational complexity implement system validate: measure system time/memory validate: qualitative/quantitative result image analysis [test on any users, informal usability study] validate: lab study, measure human time/errors for operation validate: test on target users, collect anecdotal evidence of utility validate: field study, document human usage of deployed system validate: observe adoption rates

match up with level of contributions!

Page 26: Oh, no! validation bingo!. algorithm complexity analysis

threat: wrong problem validate: observe and interview target users threat: bad data/operation abstraction threat: ineffective encoding/interaction technique validate: justify encoding/interaction design threat: slow algorithm

validate: analyze computational complexity implement system validate: measure system time/memory validate: qualitative/quantitative result image analysis [test on any users, informal usability study] validate: lab study, measure human time/errors for operation validate: test on target users, collect anecdotal evidence of utility validate: field study, document human usage of deployed system validate: observe adoption rates

match up with level of contributions!

Page 27: Oh, no! validation bingo!. algorithm complexity analysis

threat: wrong problem validate: observe and interview target users threat: bad data/operation abstraction threat: ineffective encoding/interaction technique validate: justify encoding/interaction design threat: slow algorithm

validate: analyze computational complexity implement system validate: measure system time/memory validate: qualitative/quantitative result image analysis [test on any users, informal usability study] validate: lab study, measure human time/errors for operation validate: test on target users, collect anecdotal evidence of utility validate: field study, document human usage of deployed system validate: observe adoption rates

match up with level of contributions!

Page 28: Oh, no! validation bingo!. algorithm complexity analysis

threat: wrong problem validate: observe and interview target users threat: bad data/operation abstraction threat: ineffective encoding/interaction technique validate: justify encoding/interaction design threat: slow algorithm

validate: analyze computational complexity implement system validate: measure system time/memory validate: qualitative/quantitative result image analysis [test on any users, informal usability study] validate: lab study, measure human time/errors for operation validate: test on target users, collect anecdotal evidence of utility validate: field study, document human usage of deployed system validate: observe adoption rates

avoid deadly mismatches

Page 29: Oh, no! validation bingo!. algorithm complexity analysis

threat: wrong problem validate: observe and interview target users threat: bad data/operation abstraction threat: ineffective encoding/interaction technique validate: justify encoding/interaction design threat: slow algorithm

validate: analyze computational complexity implement system validate: measure system time/memory validate: qualitative/quantitative result image analysis [test on any users, informal usability study] validate: lab study, measure human time/errors for operation validate: test on target users, collect anecdotal evidence of utility validate: field study, document human usage of deployed system validate: observe adoption rates

avoid deadly mismatches

Page 30: Oh, no! validation bingo!. algorithm complexity analysis

examples! nuances! 4:15 tomorrow

genealogical graphs

justify encoding/interaction design

qualitative result image analysistest on target users, collect anecdotal evidence of utility

MatrixExplorerjustify encoding/interaction design measure system time/memory

qualitative result image analysis

observe and interview target users

LiveRACjustify encoding/interaction design

field study, document usage of deployed system

qualitative result image analysis

observe and interview target users

LinLog qualitative/quantitative result image analysis