A data model and development environment to help end user programmers validate and reuse data
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A Data Model and Development Environment to Help End-User Programmers Validate and Reuse Data. Christopher Scaffidi Thesis Proposal, May 8, 2007 Committee. Target audience. In 2012, we project that there will be 90 million computer end users (“EUs”) in American workplaces.

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A data model and development environment to help end user programmers validate and reuse data

A Data Model and Development Environmentto Help End-User Programmers Validate and Reuse Data

Christopher Scaffidi

Thesis Proposal, May 8, 2007

Committee


Target audience

Target audience

  • In 2012, we project that there will be 90 millioncomputer end users (“EUs”) in American workplaces.

  • Of these, at least half will create spreadsheets, databases, and/or web applications. These are called end-user programmers (“EUPs”). [5]

  • Both EUs and EUPs will benefit from the proposed research, though the proposed research is primarily aimed at EUPs (including EUs who become EUPs because of the research).

introduction ● related work ● studies ●prototype ● proposed work ● evaluation ● summary


Contextual inquiry what are the problems of eus and eups

Contextual inquiry:What are the problems of EUs and EUPs?

  • Observed 3 administrative assistants, 4 managers, and 3 webmasters/graphic designers (1-3 hrs, each)

introduction ● related work ● studies ●prototype ● proposed work ● evaluation ● summary


How do you validate web forms if you do not know javascript

How do you validate web formsif you do not know JavaScript?

Is the input valid?

“EDSH 225”

Is the input nearly valid?

“EDXH 225”

Does it just need reformatting?

“Smith 225”

Or is it obviously badly invalid?

“Robotics Institute”

introduction ● related work ● studies ●prototype ● proposed work ● evaluation ● summary


Other tasks other data other problems

Other tasks, other data, other problems

  • When building a staff roster by merging data sources into a single spreadsheet, one of the EUs:

    • Had to manually transform data to consistent format(e.g.: Put person names in Lastname, Firstname format)

    • Had to scrutinize data to identify questionable values that deserved double-checking(e.g.: A first name with 15 characters might be right)

    • Had to manually check for (near-) duplicates(e.g.: “Scaffidi, Christopher” and “Scaffidi, Chris”)

  • We and research collaborators identified many additional data validation and data reuse tasks that were poorly supported by existing tools. [3][7][9]

introduction ● related work ● studies ●prototype ● proposed work ● evaluation ● summary


Underlying problem abstraction mismatch

Underlying problem: abstraction mismatch

  • Tools support strings, integers, floats, sometimes dates.

  • Problem domain involves higher-level categories of data:

    • University names“Carnegie Mellon”, “CMU”

    • Person names“Scaffidi, Christopher”, “Chris Scaffidi”

    • CMU phone numbers“8-1234”, “x8-1234”

    • CMU room numbers“WeH 4623”, “Wean 4623”

  • These data categories are:

    • Human-readable

    • Short (~ 1 input field)

    • Multi-format

    • Sometimes ambiguous / fuzzy (non-binary scale of validity)

    • Often particular to certain groups of people

introduction ● related work ● studies ●prototype ● proposed work ● evaluation ● summary


A new direction create a new abstraction for each category of data

A New Direction: Create a new abstraction for each category of data

  • Like software “libraries,” implementations of these abstractions could be reused in many programs.

  • Abstractions would need to include functionality for:

    • Recognizing instances of the category

      (for automating data validation)

    • Transforming instances among various formats

      (for automating data reformatting)

    • Testing instances for equality

      (for automating removal of duplicates)

introduction ● related work ● studies ●prototype ● proposed work ● evaluation ● summary


A new direction other requirements for abstractions

A New Direction: Other requirements for abstractions

  • EUPs over a range of programming expertise must be able to create custom new abstractions.

  • Flexibility:

    • Abstractions must capture fuzziness when recognizing instances of the category and when testing equivalence.

    • EUPs must have the option of configuring abstractions to learn exceptional cases.

  • Sharability:

    • EUPs must still be able to share and find useful abstractions even as the number of abstractions grows.

    • Latency and throughput of operations must not become burdensome as EUPs share numerous abstractions.

introduction ● related work ● studies ●prototype ● proposed work ● evaluation ● summary


Thesis

Thesis

The proposed data model and development environment will enable end-user programmers to implement and share custom abstractions for flexibly recognizing, transforming and equivalence-testing values in categories of short, human-readable data.

The model and environment will help end-user programmers to more quickly and correctly validate and reuse data than is possible through currently practiced methods.

introduction ● related work ● studies ●prototype ● proposed work ● evaluation ● summary


Topes

Topes

  • Tope = an abstraction implementation for a data category

    • Greek word for “place,” because each corresponds to a data category with a natural place in the problem domain

  • Topes in practice:

    • EUPs create new topes by using the basic tope editor (or by writing topes in another language, such as JavaScript)

    • EUPs publish topes on repositories.

    • Other EUs & EUPs download topes to their local cache.

    • Tool plug-ins let EUs & EUPs browse their local cache and associate topes with variables and input fields.

    • Plug-ins get topes from local cache and use them to recognize, transform, and equivalence-test data.

introduction ● related work ● studies ●prototype ● proposed work ● evaluation ● summary


Outline

Outline

  • Introduction

  • Related work

  • Exploratory studies

  • Prototype

  • Proposed work

  • Evaluation

  • Summary and schedule

Existing approaches lack an easy way for EUPs to create flexible, sharable abstractions for data categories

introduction ● related work ● studies ● prototype ● proposed work ● evaluation ● summary


Existing programming tools for eups eg excel visual studio express robofox

Existing programming tools for EUPs(eg: Excel, Visual Studio Express, Robofox)

  • Limited support for a closed set of data categories:

    • Spreadsheets (like Excel) allow EUs to associate certain formats with cells, but these do not actually validate data

    • Web application design tools (like Visual Studio) allow EUPs to apply certain limited constraints to validate input

    • Web macro tools (like Robofox) allow EUPs to store certain personal data (eg: phone #) and reuse it

  • No straightforward mechanisms for EUPs to create new abstractions for unsupported categories of data

introduction ● related work ● studies ● prototype ● proposed work ● evaluation ● summary


User definable data formats eg swyn grammex lapis data detectors

User-definable data formats(eg: SWYN, Grammex, Lapis, Data Detectors)

  • EUPs struggle to understand and create regexps/CFGs

  • These formats are binary (non-fuzzy) recognizers

  • Formats alone do not transform or equivalence-test data

  • Only Apple Data Detectors offers sharing mechanisms

Lapis example

@DayOfMonth is Number equal to /[12][0-9]|3[01]|0?[1-9]/

ignoring nothing

@ShortMonth is Number equal to /1[012]|0?[1-9]/

ignoring nothing

@ShortYear is Number equal to /\d\d/

ignoring nothing

Date is flatten @ShortMonth

then @DayOfMonth

then @ShortYear

ignoring either Spaces

or Punctuation

introduction ● related work ● studies ● prototype ● proposed work ● evaluation ● summary


Formal and oo types eg ml java c

Formal and OO types(eg: ML, Java, C#)

  • Type systems are inflexible:

    • A value is or is not a valid instance of a type (non-fuzzy)

    • If a value is invalid at compile-time, it cannot become valid at runtime

  • Typed languages are probably difficult for EUPs who are uncomfortable with untyped scripting languages.

introduction ● related work ● studies ● prototype ● proposed work ● evaluation ● summary


Format inference and constraint enforcing eg info extraction lapis cues slate

Format-inference and constraint-enforcing(eg: info. extraction, Lapis, Cues, Slate)

  • Various approaches:

    • Many algorithms infer an abstract model, CFG-like grammar, or other format with very low editability.

    • Other algorithms enforce constraints (either inferred or specified by EUPs) that cannot handle string-like data

  • Formats, grammars, and constraints are not able to transform or equivalence-test data.

introduction ● related work ● studies ● prototype ● proposed work ● evaluation ● summary


Outline1

Outline

  • Introduction

  • Related work

  • Exploratory studies

  • Prototype

  • Proposed work

  • Evaluation

  • Summary and schedule

  • Tasks commonly involve

  • Recognizing

  • Transforming

  • Equivalence-testing

  • values in categories of short, human-readable data.

introduction ● related work ● studies ● prototype ● proposed work ● evaluation ● summary


Survey of eups better data manipulation features needed

Survey of EUPs:Better data-manipulation features needed

  • Asked 831 information workers about use of 23 features in 5 tools (eg: creating spreadsheet macros, database stored procedures, and web forms) [4][9]

  • The most widely used features were related to manipulating linked structures of data (eg: database tables) rather than imperative or macro programming

  • Yet respondents complained about these features:

    • “Not always easy to move sturctured [sic] data or text”

    • “Not always integrated a lot of data manipulation redundant”

    • “Information entered inconsistently into database fields by different people leaves a lot of database cleaning”

introduction ● related work ● studies ● prototype ● proposed work ● evaluation ● summary


Contextual inquiry of eus and eups specific data manipulation features needed

Contextual inquiry of EUs and EUPs:Specific data-manipulation features needed

  • Observed 3 administrative assistants, 4 managers, and 3 webmasters/graphic designers (1-3 hrs, each) [3][9]

  • They needed better support for automatically:

    • Transforming data values among different formats within the same category of data (eg: ST to State)

    • Identifying questionable data values that could be acceptable for a task but deserve double-checking

    • Identifying duplicate values, including values that were probably equivalent

introduction ● related work ● studies ● prototype ● proposed work ● evaluation ● summary


Interviews of web site creators confirmation of specific features needed

Interviews of web site creators:Confirmation of specific features needed

  • Interviewed 6 people involved in creating “person locator” web sites after Hurricane Katrina [7][9]

  • Many omitted data validation on web forms

    • Hard to detect that “12 Years old” is an invalid street address (what would the regexp look like?)

  • “Aggregator” sites were built to scrape and consolidate data from numerous person locator sites.

    • Hard to transform data into a single consistent format

    • Hard to identify probable duplicates in the merged data set

introduction ● related work ● studies ● prototype ● proposed work ● evaluation ● summary


Outline2

Outline

  • Introduction

  • Related work

  • Exploratory studies

  • Prototype

  • Proposed work

  • Evaluation

  • Summary and schedule

How could flexible formats be expressed?

introduction ● related work ● studies ● prototype● proposed work ● evaluation ● summary


Prototype task flow diagram

PrototypeTask flow diagram

User creates a format from scratch

or

User highlights spreadsheet cells

Plug-in flags cells that don’t match format

User loads an existing format from a file

or

Algorithm infers a format from cell values

User reviews and customizes format

[1][6]

introduction ● related work ● studies ● prototype● proposed work ● evaluation ● summary


Sample task validating a spreadsheet with the prototype we have built

Sample task: validating a spreadsheetwith the prototype we have built

  • The second column is “supposed” to contain first names, but some initials have snuck in.

introduction ● related work ● studies ● prototype● proposed work ● evaluation ● summary


Sample task validating a spreadsheet customizing an inferred format

Sample task: validating a spreadsheetCustomizing an inferred format

  • User can specify meaningful names for parts

introduction ● related work ● studies ● prototype● proposed work ● evaluation ● summary


Sample task validating a spreadsheet customizing constraints in our prototype

Sample task: validating a spreadsheetCustomizing constraints in our prototype

  • User can add/edit constraints

introduction ● related work ● studies ● prototype● proposed work ● evaluation ● summary


Sample task validating a spreadsheet flagging potential errors

Sample task: validating a spreadsheetFlagging potential errors

  • A red flag (reviewer comment, actually) appears on cells that do not match the format; mouse over for message

introduction ● related work ● studies ● prototype● proposed work ● evaluation ● summary


Sample task web form validation the painful old way

Sample task: web form validationThe painful old way

  • Drag widgets and validator onto page, select a regexp, customize if desired.

introduction ● related work ● studies ● prototype● proposed work ● evaluation ● summary


Sample task web form validation results of the painful old way

Sample task: web form validationResults of the painful old way

  • Invalid inputs cause a hard-coded message to appear.

    Oops, forgot to enter a message at design-time.

  • For valid inputs, no error message appears.

    Hm, didn’t realize the area code was optional.

    What if I want to allow campus phone numbers?

introduction ● related work ● studies ● prototype● proposed work ● evaluation ● summary


Sample task web form validation the wonderful new way

Sample task: web form validationThe wonderful new way

  • Drag widgets and validator onto page, select a format, customize if desired.

introduction ● related work ● studies ● prototype● proposed work ● evaluation ● summary


Sample task web form validation creating this format took 55 seconds

Sample task: web form validationCreating this format took 55 seconds

introduction ● related work ● studies ● prototype● proposed work ● evaluation ● summary


Sample task web form validation results of the new way

Sample task: web form validationResults of the new way

  • Invalid inputs cause a targeted message to appear.

  • Inputs that violate an always or never constraint cannot be submitted to the server.

  • Inputs that violate an oftenconstraint cause a warning, which the application user can override.

introduction ● related work ● studies ● prototype● proposed work ● evaluation ● summary


Prototype implementation system block diagram

Prototype implementationSystem block diagram

Microsoft Excel

Plug-in

Microsoft Visual Studio.NET

Web application

Plug-in

Validator

Spreadsheet

Format editor

Parser

introduction ● related work ● studies ● prototype● proposed work ● evaluation ● summary


Benefits of the format editor

Benefits of the format editor

  • Exotic regexp notation is replaced with sentence-like screen prompts.

  • Soft constraints (“often”) are supported.

  • Negation constraints (“never”) are supported.

  • In terms of expressiveness,

    Augmented context-free grammars

    > context-free grammars > regexps

    But is the expressiveness adequate for common data?

introduction ● related work ● studies ● prototype● proposed work ● evaluation ● summary


Expressiveness evaluation

Expressiveness evaluation

  • Four administrative assistants’ use of a web browser was logged for three weeks, resulting in nearly 6000 sample data values that they typed into web forms.

  • Not logged verbatim: characters were generalized

    • Eg: [email protected][email protected]{5}.a{3}

  • We manually grouped values into 19 semantic families (eg: email address) based on widget’s HTML name and words visually nearby to the widgets

  • Created and tested formats for 14 families (4250 values)

    • Omitted: username/passwords and long blocks of “text”

    • Inference & testing features were not used during format creation

introduction ● related work ● studies ● prototype● proposed work ● evaluation ● summary


Expressiveness evaluation results

Expressiveness evaluation results

  • 9 families needed 1 format each; 5 needed 2 formats each

  • Easy to quickly express a reasonably correct format?

    • 11 families took < 1 minute each; others 3, 5, 7 minutes

    • No errors found in formats for 9 families; 5 had errors

      • Most errors: forgetting to mark a part as optional

      • Testing feature was added after this evaluation

  • The only error attributable to editor expressiveness:

    • 1 of the 4250test values had a trailing period on a street type (in an address line)

    • This particular version of the editor had no way to say that a part could contain a period but only at the end

[6]

introduction ● related work ● studies ● prototype● proposed work ● evaluation ● summary


Extension and further evaluation needed

Extension and further evaluation needed

  • The editor evaluation again highlighted the need for supporting multiple formats within each data category.

  • The proposed work will add this support.

  • Then, usability of the editor as a whole will be evaluated.

introduction ● related work ● studies ● prototype● proposed work ● evaluation ● summary


Outline3

Outline

  • Introduction

  • Related work

  • Exploratory studies

  • Prototype

  • Proposed work

  • Evaluation

  • Summary and schedule

Generalizing the prototype:

A lightweight data model

+

A development environment to help EUPs create, share and use topes

introduction ● related work ● studies ● prototype ● proposed work ● evaluation ● summary


Proposed data model

Proposed data model

  • 1 tope implementation contains executable functions:

    • 1 isa:string[0,1] function per format, for recognizing instances of the format

    • 0 or 1 eqc:string x string[0,1] function per format, for testing equivalence of two values in a format(default is a binary test for being exactly identical)

    • 0 or more trf:stringstring function linking formats, for transforming values form one format to another

  • A lightweight data model…

    • Only contains 3 kinds of functions (isa/eqc/trf)

    • These correspond to the operations that people had to keep performing manually in our studies.

introduction ● related work ● studies ● prototype ● proposed work ● evaluation ● summary


Example tope notional representation

Example topeNotional representation

  • An example tope for CMU room numbers

    • 3 isa functions, up to 3 eqc functions, 4 trf functions

    • A tope’s eqc and trf functions can be omitted if desired

Formal building name& room number

Elliot Dunlap Smith Hall 225

Building abbreviation& room number

EDSH 225

Colloquial building name& room number

Smith 225

introduction ● related work ● studies ● prototype ● proposed work ● evaluation ● summary


Proposed development environment functional decomposition diagram

Proposed development environmentFunctional decomposition diagram

Development Environment

Repository Software

Plug-Ins

Basic Topes Editor

Publishing Tools

Search Tools

Normalization

EUPs implement topes in basic topes editor (or JavaScript), then publish in repositories.

Other EUs and EUPs search for topes, download them, then use them through plug-ins.

introduction ● related work ● studies ● prototype ● proposed work ● evaluation ● summary


Proposed development environment enhanced basic topes editor

Proposed development environmentEnhanced basic topes editor

Development Environment

Repository Software

Plug-Ins

Basic Topes Editor

Publishing Tools

Search Tools

Normalization

introduction ● related work ● studies ● prototype ● proposed work ● evaluation ● summary


Proposed work enhancing the basic topes editor

Proposed workEnhancing the basic topes editor

  • Extend isa support

    • Improve error message generation

  • Add trf support

    • EUPs will specify a series of steps:

      • Select a part, select an operator

      • Operators: permutation, lookup, arithmetic, capitalization

    • Add (regression) testing features to facilitate consistency

  • Add eqc support

    • For each part, EUPs will specify a comparison operator, returning value in [0,1], and these will be multiplied.

      • Operators: exactly identical, case-insensitive comparison, ~arithmetic distance, ~edit distance

introduction ● related work ● studies ● prototype ● proposed work ● evaluation ● summary


Proposed development environment repository software

Proposed development environmentRepository software

Development Environment

Repository Software

Plug-Ins

Basic Topes Editor

Publishing Tools

Search Tools

Normalization

introduction ● related work ● studies ● prototype ● proposed work ● evaluation ● summary


Proposed work repository software

Proposed workRepository software

  • Clients will have a list of “known” repository servers

    • Generally pre-configured to include a global server at CMU

    • Organizations will configure clients to include the organizational server

    • EUs and EUPs will be able to add new servers to their list

  • To support publishing/searching, the repository will house meta-information about topes.

  • (EUPs can also simply email topes to EUs and other EUPs, bypassing the repository system.)

introduction ● related work ● studies ● prototype ● proposed work ● evaluation ● summary


Proposed development environment publishing tools

Proposed development environmentPublishing tools

Development Environment

Repository Software

Plug-Ins

Basic Topes Editor

Publishing Tools

Search Tools

Normalization

introduction ● related work ● studies ● prototype ● proposed work ● evaluation ● summary


Proposed work publishing topes

Proposed workPublishing topes

  • Publishing a tope on a repository

    • Anonymously, or authenticated

    • EUPs can gather into groups, publish group-private topes

    • Each tope can have a non-unique name & description

    • Internally, each tope will have a globally unique id (guid)

      • For published tope, guid = URL of the master copy

      • (For emailed tope, guid based on sender’s email address)

  • Tope aliases

    • EUPs can publish tope aliases

    • Alias has no implementation; just points to another tope

    • Alias can have its own name, description

introduction ● related work ● studies ● prototype ● proposed work ● evaluation ● summary


Proposed development environment search tools

Proposed development environmentSearch tools

Development Environment

Repository Software

Plug-Ins

Basic Topes Editor

Publishing Tools

Search Tools

Normalization

introduction ● related work ● studies ● prototype ● proposed work ● evaluation ● summary


Proposed work searching for relevant topes

Proposed workSearching for relevant topes

  • Search by keyword:

    • Search tope name and description

    • And match based on words that are visually near to topes

  • Search by groups of people:

    • Within an organization, or by author’s email domain

    • Within spaces that are “group-private”

  • Search by groups of topes:

    • “If you liked this tope, you may also like XYZ”

    • Similar to Amazon.com’s product recommendations

  • Search by example:

    • “Find me a tope that recognizes 412-555-1212”

    • For efficiency, filter based on “signature” (\d{3}-\d{3}-\d{4})

introduction ● related work ● studies ● prototype ● proposed work ● evaluation ● summary


Proposed work searching for trustworthy topes

Proposed workSearching for trustworthy topes

introduction ● related work ● studies ● prototype ● proposed work ● evaluation ● summary


Proposed development environment enhanced plug ins

Proposed development environmentEnhanced plug-ins

Development Environment

Repository Software

Plug-Ins

Basic Topes Editor

Publishing Tools

Search Tools

Normalization

introduction ● related work ● studies ● prototype ● proposed work ● evaluation ● summary


Proposed work enhancing plug ins

Proposed workEnhancing plug-ins

  • Microsoft Excel

    • Outlier findinginfer format on selected cells, run isa

    • Assertions run isa on selected cells

    • Transformation run trf on selected cells

    • De-duplication run eqc on selected cells, cluster the cells

  • Microsoft Visual Studio.NET

    • Input validation run isa on form widget, show error message

    • Input consistency run trf on value if in wrong format

  • Robofox

    • Assertions run isa on selected variable

    • Transformation run trf on selected variable

  • In each, support basic editor topes & JavaScript topes

introduction ● related work ● studies ● prototype ● proposed work ● evaluation ● summary


Proposed development environment normalization the tope who cried wolf

Proposed development environmentNormalization (“the tope who cried wolf”)

Development Environment

Repository Software

Plug-Ins

Basic Topes Editor

Publishing Tools

Search Tools

Normalization

introduction ● related work ● studies ● prototype ● proposed work ● evaluation ● summary


Proposed work normalization recognizing exceptions

Proposed workNormalization: Recognizing exceptions

  • Tope creators might overlook values.

  • From the standpoint of a tope format, these “normal” values are exceptional cases that need to be tolerated.

  • Simple approach: Record a whitelist of exceptions

  • More sophisticated: For each format, record exceptions, infer a format (new isa function), and average this function’s score with the raw function’s score

  • Exceptional values can be incorporated into the tope in the local cache and/or, at EUP’s discretion, propagated to the repository of the tope’s master copy

introduction ● related work ● studies ● prototype ● proposed work ● evaluation ● summary


Outline4

Outline

  • Introduction

  • Related work

  • Exploratory studies

  • Prototype

  • Proposed work

  • Evaluation

  • Summary and schedule

Expressiveness: evaluation on examples

Use by EUPs: evaluation in controlled experiments

Flexibility: evaluation through analyses

Sharability: field testing + analyses

introduction ● related work ● studies ● prototype ● proposed work ● evaluation ● summary


Thesis1

Thesis

The proposed data model and development environment will enable end-user programmers to implement and share custom abstractions for flexibly recognizing, transforming and equivalence-testing values in categories of short, human-readable data.

The model and environment will help end-user programmers to more quickly and correctly validate and reuse data than is possible through currently practiced methods.

introduction● related work ● studies ●prototype ● proposed work ● evaluation ● summary


Expressiveness is needed

Expressiveness is needed

  • Claim: End users’ tasks commonly involve categories of short, human-readable data that appear in multiple formats, and that users recognize and test for equivalence in a fuzzy manner.

  • Using contextual inquiry and interview data, identify and characterize examples of these data categories.

introduction ● related work ● studies ● prototype ● proposed work ● evaluation ● summary


Expressiveness is provided

Expressiveness is provided

  • Claim: The operators and constructs supported by the basic editor are expressive enough for creating topes for data categories in common tasks.

    • We’ll create topes for data categories infour tasks similar to those that we saw in our prior studies:

    • 1 “graduated response” validation task in web application

    • 1 web macro task

    • 1 outlier finding task in spreadsheet

    • 1 data de-duplicationtask in spreadsheet

introduction ● related work ● studies ● prototype ● proposed work ● evaluation ● summary


Eups can create topes

EUPs can create topes

  • Claim: Given a suitable development environment, EUPs can create custom software abstractions for recognizing, transforming and equivalence-testing values in commonly occurring data categories.

  • Evaluate with controlled experiment (with CMU staff):

    • Create topes for data categories in sample tasks

    • Within-subjects, we may have subjects use a comparison method

      • Eg: Lapis for isa, manual for trf, Excel formulas for eqc

  • Measure time-on-task and error rates

introduction ● related work ● studies ● prototype ● proposed work ● evaluation ● summary


Eups can benefit from using topes

EUPs can benefit from using topes

  • Claim: Extending existing programming tools with these abstractions enables EUs and EUPs to more quickly and correctly validate and reuse data than is possible through currently practiced methods.

  • Evaluate with controlled experiment (with CMU staff):

    • Provide subjects with appropriate topes

    • Have them perform the sample tasks, using plug-ins

    • Within-subjects, we may have subjects use a comparison method

      • Eg: JavaScript, manual performance, Lapis, Excel formulas

  • Measure time-on-task and error rates

introduction ● related work ● studies ● prototype ● proposed work ● evaluation ● summary


Recognition equivalence testing and exception handling are flexible

Recognition, equivalence-testing,and exception-handling are flexible

  • Claim: The abstractions created by EUPs flexibly capture the fuzziness of data recognition and equivalence-testing, and flexibly adapt at runtime when validating exceptional inputs.

  • Evaluate with analyses:

    • Take topes created by EUPs in experiments

    • Run them on test data from EUSES spreadsheet corpus

    • Based on manual annotation of test data, score the topes

    • Evaluate the normalization algorithms: which works best?

  • Measure topes’ precision/recall, compare to Lapis scores

introduction ● related work ● studies ● prototype ● proposed work ● evaluation ● summary


Eups can share topes

EUPs can share topes

  • Claim: Given a suitable development environment operating on meta-information about these abstractions, EUPs can share abstractions with one another.

  • Evaluate through field testing

    • Create an installer for plug-ins and basic topes editor

    • Recruit CMU grad students and staff to use it for 3 months

    • Log user actions (eg: published topes, queries, downloads)

    • Record (and answer) frequently asked questions

    • Periodic surveys

  • Which features do EUPs consider helpful (or need work)?

  • Which sources of “trust” evidence are actually helpful?

introduction ● related work ● studies ● prototype ● proposed work ● evaluation ● summary


Performance is scalable

Performance is scalable

  • Claim: The latency and throughput of operations does not become burdensome as EUPs share numerous abstractions with one another.

  • Evaluate with analyses:

    • Logs provide sample queries

    • Measure execution time of queries on sample tope sets

    • Perform algorithmic analysis of the search algorithms

  • Combining execution time with algorithmic analysis yields a rough estimate of scalability

introduction ● related work ● studies ● prototype ● proposed work ● evaluation ● summary


Outline5

Outline

  • Introduction

  • Related work

  • Exploratory studies

  • Prototype

  • Proposed work

  • Evaluation

  • Summary and schedule

3 knowledge contributions

5 technical contributions

20 months

introduction ● related work ● studies ● prototype ● proposed work ● evaluation ● summary


Knowledge contributions

Knowledge contributions

  • Characterization of the fuzzy, multi-format categories of data commonly involved in end-user programming

  • Lightweight data model (isa/trf/eqc) for representing these data categories

  • A list of sources of evidence that help EUPs share abstractions

introduction ● related work ● studies ● prototype ● proposed work ● evaluation ● summary


Primary technical contributions

Primary technical contributions

  • Algorithms

    • For validating, transforming, and equivalence-testing data based on formats implemented by EUPs

    • For generating targeted error messages

    • For search-by-example

    • For collecting and searching on context words

    • For normalization and format inference

introduction ● related work ● studies ● prototype ● proposed work ● evaluation ● summary


Intended schedule 20 months

Intended schedule: 20 months

Green = implementation Blue = evaluation Purple = dissertation

Editor and plug-in support for trf and eqc (3 mo)

Evaluate with examples, experiments, analyses (3 mo)

Addl. editor and plug-in enhancements (3 mo)

Implement repository (5 mo)

Evaluate sharability & scalability (3 mo)

Dissertation (3 mo)

introduction ● related work ● studies ● prototype ● proposed work ● evaluation ● summary


Referenced papers

Referenced papers

Conference papers

[1]C. Scaffidi. Unsupervised Inference of Data Formats in Human-Readable Notation. Proceedings of 9th International Conference on Enterprise Integration Systems (ICEIS'07), 2007, to appear.

[2]C. Scaffidi, K. Bierhoff, E. Chang, M. Felker, H. Ng, C. Jin. Red Opal: Product-Feature Scoring from Reviews. Proceedings of 8th ACM Conference on Electronic Commerce (ACMEC'07), 2007, to appear

[3]C. Scaffidi, A. Cypher, S. Elbaum, A. Koesnandar, and B. Myers. Scenario-Based Requirements for Web Macro Tools. Submitted for publication, 2007.

[4]C. Scaffidi, A. Ko, B. Myers, M. Shaw. Dimensions Characterizing Programming Feature Usage by Information Workers. VL/HCC'06: Proceedings of the 2006 IEEE Symposium on Visual Languages and Human-Centric Computing, pp. 59-62, 2006.

[5]C. Scaffidi, M. Shaw, and B. Myers. Estimating the Numbers of End Users and End User Programmers. VL/HCC'05: Proceedings of the 2005 IEEE Symposium on Visual Languages and Human-Centric Computing, pp. 207-214, 2005.

Other papers

[6]C. Scaffidi, B. Myers, M. Shaw. The Topes Format Editor and Parser, Technical Report CMU-ISRI-07-104, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, May 2007.

[7]C. Scaffidi, B. Myers, and M. Shaw. Trial By Water: Creating Hurricane Katrina "Person Locator" Web Sites. In Leadership at a Distance: Research in Technologically-Supported Work (S. Weisband, ed), Lawrence Erlbaum, pp. 209-222, 2007.

[8]C. Scaffidi, M. Shaw. Toward a Calculus of Confidence. First International Workshop on the Economics of Software and Computation, co-located with ICSE'07, 2007, to appear.

[9]C. Scaffidi, M. Shaw, B. Myers. Games Programs Play: Obstacles to Data Reuse, 2nd Workshop on End User Software Engineering (WEUSE), 2006.

introduction ● related work ● studies ● prototype ● proposed work ● evaluation ● summary


Thank you

Thank You…

  • …to many people for helpful suggestions

  • …to NSF and EUSES for funding (ITR-0325273 and CCF-0438929)

  • …to my wife, and to the Lord, for emotional support

introduction ● related work ● studies ● prototype ● proposed work ● evaluation ● summary


A data model and development environment to help end user programmers validate and reuse data

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Contextual inquiry what are the problems of eus and eups1

Contextual inquiry:What are the problems of EUs and EUPs?

  • Admin assistants and managers performed tasks in browsers and/or spreadsheets for the entire observation.

  • Tasks required copying data among web forms and/or spreadsheets.

    • E.g.: using a government web site to look up an appropriate per diem rate based on a locality (City, ST) and a date (MM/DD/YYYY) in an expense report

introduction ● related work ● studies ●prototype ● proposed work ● evaluation ● summary


We considered helping them automate their tasks by creating web macro programs

We considered helping them automate their tasks by creating web macro programs.

But existing tools cannot perform needed data transformations

E.g.: Selecting the year based on the date (MM/DD/YYYY) and selecting the state based on the locality (City, ST)

introduction ● related work ● studies ●prototype ● proposed work ● evaluation ● summary


Proposed work searching for topes by example

Proposed workSearching for topes – by example

  • Overview

    • Required meta-information:

      • Published topes can include positive/negative examples (e.g.: “EDSH 225” matches this format)

      • Tope users can also post examples, with ratings & comments

    • Generalize these examples to a format signature

      • Required algorithm is similar to existing format inference but slightly more coarse (e.g.: “[a-z]{2-5} [0-9]{2-4}”)

  • To search by example:

    • Specify some examples of the desired tope

    • Repository generalizes these examples to a signature

    • Repository returns topes with a similar signature

introduction ● related work ● studies ● prototype ● proposed work ● evaluation ● summary


Proposed work searching for topes in groups of topes

Proposed workSearching for topes – in groups of topes

  • Overview

    • People with one tope in common probably have other topes in common (eg: medical staff, CMU students, etc)

    • Approach: cluster topes based on who creates/uses them

    • Many algorithms exist for this kind of problem (eg: HAC)

  • Searching by tope group:

    • The person searching has already used a few topes

    • Return topes that are in the same clusters

introduction ● related work ● studies ● prototype ● proposed work ● evaluation ● summary


Proposed work searching for topes by keyword

Proposed workSearching for topes – by keyword

  • Keywords can occur in tope name or description

  • Keywords can occur contextually:

    • EUP identifies the field where the tope will be used

      • Eg: a spreadsheet cell, or a web form widget

    • The programming tool plug-in looks for nearby words

      • Eg: top of spreadsheet column, left end of spreadsheet row, labels above form widget, or form widget’s HTML name

    • With user’s permission, these are sent to repository

      • As meta-information, when publishing

      • As a query, when searching

  • Adapt algorithm for finding products based on features? [2]

introduction ● related work ● studies ● prototype ● proposed work ● evaluation ● summary


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