The “55M End-User Programmers” Estimate Revisited

The “55M End-User Programmers” Estimate Revisited

Christopher Scaffidi

1. Introduction to a Popular Estimate

2. The Estimation Method– 55M End-User Programmers in 2005

3. Extending the Method– 90M End-Users in 2012– A Survey of End-User Abstraction Practices

4. Conclusion

55M End-User Programmers > Table of Contents

Table of Contents

55 Million End-User Programmers by 2005

“End-User” =– “The ultimate consumer of a product, especially the one

for whom the product has been designed.” (Dictionary)– “People who are not employed as programmers”

(citation on next slide)

“Programmers” =– People who act “to create an application that serves

some function” (Nardi, A Small Matter of Programming)– Researchers often use the term to include creators of

spreadsheets.

55M End-User Programmers > Introduction to a Popular Estimate

Introduction to a Popular Estimate

Context: – The authors of this conference paper added more

abstraction capabilities to Excel, to boost Excel’s utility

Usage: – “The number of end-user programmers in the U.S. alone

is expected to reach 55 million by 2005, as compared to only 2.75 million professional programmers”

Appeared in:– S. Jones, A. Blackwell, and M. Burnett. A User-Centered Approach To Functions in

Excel. Proceedings of the 8th ACM SIGPLAN International Conference on Functional Programming, ACM Press, 2003, pp. 165-176.


Example #1 of Estimate’s Usage

Context: – The magazine author discusses a grant awarded by NSF

for research on improving the reliability of spreadsheets

Usage: – “Experts estimate the number of so-called 'end-user

programmers’ to reach 55 million by 2005,” said NSF spokesperson David Hart… “Nearly half of the programs created by these end-users have nontrivial bugs.”

Appeared in:– Mike Martin, New Program Exterminates End-User Bugs. CIO Today, NewsFactor

Network, June 9, 2004.



Used in many places– Journal articles– Conference papers– Workshop papers– Grant applications? – Trade magazines– Web sites

Used to make an important point– There are a lot of end-user programmers

(in fact, many more than professional programmers).– Therefore they are a significant group of programmers.– Therefore we should not neglect their needs.


Introduction to a Popular Estimate

cscaffid

Journal: CACM Sep 2004, p31

First appeared in COCOMO 2.0– COCOMO is a cost estimation model from Boehm et al.– Extended into COCOMO 2.0 (late 1990’s) modern practices

COCOMO 2.0 is for professionals (not end-users)– How many people would/wouldn’t benefit from COCOMO 2.0?– To answer this, Boehm estimated projections of…

• # of professional programmers (2.75M by 2005)• # of end-user programmers (55M by 2005)

– B. Boehm et al. Cost Models for Future Software Life Cycle Processes: COCOMO 2.0. Annals of Software Engineering Special Volume on Software Process and Product Measurement (J. Arthur and S Henry, eds), J.C. Baltzer AG, Science Publishers, Amsterdam, The Netherlands, 1995.

– Also widely disseminated through a book by Boehm in 2000, as well as IEEE Software.

55M End-User Programmers > The Estimation Method

The Estimation Method


Steps to generate the estimate– Get the Bureau of Labor Statistics (BLS) occupation projections

for 2005


Occupational Category Projected # workers (2005)Managerial and Professional 36.773 million

Technical, Sales, Administration 48.078

Service 24.806

And so forth …



for 2005– Get the BLS computer usage rates by occupation for 1989

(which were actual data from a survey, not a projection)


Occupational Category How many used computers at work (1989)

Managerial and Professional 56.2%

Technical, Sales, Administration 55.1%

Service 10.2%

And so forth …




(which were actual data from a survey, not a projection)– Multiply occupation projections by computer usage rates and

total up

Sum of all end-user programmers turns out to be -----> 55 M


Occupational Category 2005 Proj 1989 Rate # UsersManagerial and Professional 36.773 M 56.2% 20.666 M

Technical, Sales, Administration 48.078 55.1 26.491

Service 24.806 10.2 2.530

And so forth …




(which were actual data from a survey, not a projection)– Multiply occupation projections by computer usage rates and

total up– Bottom line = 55M end-user programmers in 2005


Extending the Method

Main inherent approximations– Computer usage rates by occupation will remain constant from

1989 through 2005– All end-users are programmers

55M End-User Programmers > Extending the Method

Extending the Method

Main inherent approximations– Computer usage rates by occupation will remain constant from

1989 through 2005– All end-users are programmers

Address these by– Using additional data to estimate how usage rates have grown– Developing a classification of end-users to capture their

continuum of programming-like activities


Approximation #1: Constant Usage Rates

New computer usage rate data became available– Boehm based his estimate on usage rates measured in 1989– BLS also measured those rates in 1984, 1993, and 1997

A valid approximation?– Not very– Usage rates have grown substantially for each of the

occupational categories studied by BLS– In fact, in 1997, there were already around 64M end-users



Interesting curve shape– Most of these curves (especially the lower ones) seem to have

an S-shape trending to a horizontal asymptote



Innovation diffusion theory to the rescue– Researchers have realized that innovations diffuse through

populations like diseases.– They have studied various functional forms for describing this.– The simplest form (and most generally applicable) is S-shaped

– J. Teng, V. Grover, and W. Güttler. Information Technology Innovations: General Diffusion Patterns and Its Relationships To Innovation Characteristics. Transactions on Engineering Management, Vol. 49, No. 1, February 2002, pp. 13-27.



Projecting the computer usage rates– The S-shaped functional form had 3 free parameters (K, m, b)– We have 4 measurements from BLS (1984, 1989, 1993, 1997)– So we can fit to functional form for each occupation category– (Note that with so few points, “goodness of fit” means little.)

A somewhat better estimate– Get the BLS’s latest occupation projection (which happens to

be for the year 2012)– Plug in t=2012 to forecast future computer usage rates– Multiply and sum as Boehm did– Result: 90M end-users in 2012


90M End-Users in 2012

This uses a different approximation than Boehm’s– He assumed 1995 usage rates would equal 1989 usage rates.– We assume 2012 usage rates are predictable using a simple fit

to the innovation diffusion function.


90M End-Users in 2012

This uses a different approximation than Boehm’s– He assumed 1995 usage rates would equal 1989 usage rates.– We assume 2012 usage rates are predictable using a simple fit

to the innovation diffusion function.

Implication of using our assumption– Fairly questionable assumption! On-going improvements in

computers will probably drive adoption still higher.– Therefore, 90M is probably something of a lower bound.


You keep using that word. I do not think it means what you think it means. --Inigo Montoyo, Princess Bride

What Does “Programmer” Mean?


Approximation #2: All End-Users Program

Usefulness of a big scalar number– 55M or 90M is a number with no structure– Thus, it can only be used to argue, “This sure is big.”

Usefulness of a collection of numbers– Can we break down the estimate into smaller groups?– Doing this right could help guide research and development.



Usefulness of a big scalar number– 55M or 90M is a number with no structure– Thus, it can only be used to argue, “This sure is big.”

Usefulness of a collection of numbers– Can we break down the estimate into smaller groups?– Doing this right could help guide research and development.

Possible categorizations– By industry (e.g.: shipping, manufacturing, transportation, …)– By occupation (e.g.: secretary, accountant, manager, …)– By education (e.g.: K-12, college, professional, …)– By technology skills (e.g.: Java, Oracle, HTML forms, …)– By enduring programming skills (e.g.: abstraction mastery, …)



In building tools, researchers focus on abstractions– Helping end-users represent abstractions as functions:

S. Jones, A. Blackwell, and M. Burnett. A User-Centered Approach to Functions in Excel. Proceedings of the 8th ACM SIGPLAN International Conference on Functional Programming, ACM Press, 2003, pp. 165-176.

– Helping end-users map domain models to web app models:K. Kim, J. Carroll, M. Rosson. An Empirical Study of Web Personalization Assistants Supporting End-Users in Web Information Systems. IEEE 2002 Symposia on Human Centric Computing Languages and Environments, September 2002, pp. 60-62.

– Helping end-users identify abstractions from examples:M. Balaban, E. Barzilay, M. Elhadad. Abstraction as a Means for End-User Computing in Creative Applications. IEEE Transactions on Systems, Man and

Cybernetics, Part A, Vol. 32, No. 6, November 2002, pp. 640-653.

– Helping end-users model abstractions in general:F. Paternò. From Model-based to Natural Development. Proceedings HCI International 2003, Universal Access in HCI, pp.592-596.



What abstraction issues are important?– We now have an improved estimate of how many end-users.– Actually, we also have surveys of what software they use.– We don’t have any survey of what abstractions they are using.– So what abstractions are important for new tools to address?



What abstraction issues are important?– We now have an improved estimate of how many end-users.– Actually, we also have surveys of what software they use.– We don’t have any survey of what abstractions they are using.– So what abstractions are important for new tools to address?

Study users’ needs and practices before building– That’s part of what I argued (in a business context) during my

practicum talk last fall.– Why not apply it to research, too?


Anticipated Work for 2005

Phase 1: Informal survey of abstraction practices– About to go live (~ Feb 7)– On-line aspects handled by partner, Information Week– Ask about usage of abstraction-oriented programming features

• Referencing data vs making copies (e.g.: using variables)• Encapsulating reusable algorithms (e.g.: using functions)• Representing common structures (e.g.: using data structures)

– Ask about usage of other good programming practices• Documentation• Back-ups• Testing

– Ask about usage of the web• Source/destination of documentation• Source/destination of data• Source/destination of other artifacts

– Ask about background (for use as explanatory variables)


Anticipated Work for 2005

Phase 2: Direct the survey at a controlled sample– We have IRB approval through June 1– Tentative sample is marketing professionals

• They program with numbers, text, and rich text… very diverse.• They likely program more than most end-users ( upper bound).• Other options suggested by researchers: accounting & operations.

– We’ll tweak the survey based on Information Week feedback.

Phase 3: Target subgroups with interviews– Tentative dates: Fall 2005.– Just because people use a programming feature doesn’t mean

that they actually understand the abstraction behind it.– Just because people don’t use a feature doesn’t mean they

wouldn’t value it if it were implemented better.– Interviews let us “get under the hatch” into these issues.


Conclusion

“55M End-User Programmers” is a popular estimate– It makes the point that end-user programming is an

important area of research!

The estimate embodies two main approximations– Constant computer usage rates– All end-users are programmers

We can begin to remove these approximations– Model adoption rates using innovation diffusion theory

• New estimate: 90M end-users in 2012

– Study end-users according to a classification scheme• Use surveys and interviews to get guidance on research

55M End-User Programmers > Conclusion

The most powerful productivity strategy is to equip line workers with generalized programs and then to turn them loose.

The same strategy, with generalized mathematical, statistical and programming capabilities will work for scientists.

--Paraphrased from “No Silver Bullet: Essence and Accidents of Software Engineering”, Frederick Brooks, Computer Magazine,

April 1987

Any Questions?

55M End-User Programmers > Summary

Context: – The author of this workshop paper describes why

existing model-driven development approaches do not work well for end-user programmers

Usage: – “Studies report that by 2005 there will be 55 million end-

users, compared to 2.75 million professional users”

Appeared in:– F. Paternò. From Model-based to Natural Development. Proceedings HCI

International 2003, Universal Access in HCI, pp.592-596.



– Screenshot taken fromB. Boehm et al. Cost Models for Future Software Life Cycle Processes: COCOMO 2.0. Annals of Software Engineering Special Volume on Software Process and Product Measurement (J. Arthur and S Henry, eds), J.C. Baltzer AG, Science Publishers, Amsterdam, The Netherlands, 1995.

– Also widely disseminated through a book by Boehm in 2000, as well as IEEE Software.



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