1 Keeping Track: Coordinating Multiple Representations in Programming Pablo Romero, Benedict du Boulay & Rudi Lutz IDEAs Lab, Human Centred Technology.

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Keeping Track: Coordinating Multiple Representations in

Programming

Pablo Romero, Benedict du Boulay & Rudi LutzIDEAs Lab,

Human Centred Technology Research Group,

School of Science and Technology,

University of Sussex.

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Background

• Computer programs can be looked at from different perspectives

• Experienced programmers’ mental representations include multiple perspectives and mappings between them

• SDEs often provide multiple, multimodal, linked and concurrent displays (code, visualisation(s), output)

• Programming requires co-ordination of these

BlueJ Java tutoring

Environment

Kolling (2000)

Monash University

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Some Research Questions

• Are there patterns of interaction which characterise better debugging performance?– Representation use (attention and switches)– Tool use

• Are graphical representations more helpful than textual ones?

• Is debugging performance associated with any “individual difference” variable values?

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Contents

• Programming is a multi-representation and multi-faceted activity

• Debugging• Experiments

– Static System– “Dynamic” system

• Conclusions

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Representations - The Problem

• The original problem in real world terms;• The abstraction of the problem, in real world

terms, but omitting irrelevant detail;• The realisation of the real world abstraction in

terms of programming forms e.g. general computational methods of approach;

• The detailed realisation of the program in terms of the kinds data-structures and algorithms available to be used in the given language;

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Representations - The Code

• The code itself as data-structures and algorithms;

• The input/output behaviour of the code when run;

• Dynamic representations of different aspects of the code, e.g. control-flow and data-structure representations;

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Representations - The Context

• The workings of the underlying virtual machine• The workings of the programming environment

itself;• Descriptions of the code produced by

static/dynamic analysis tools;

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Programming Skills : Debugging

• Subdivision of the task– Strategies for divide and conquer and for keeping track

within and between representations– Reasoning about overall strategy

• Reasoning in the problem and programming domains– Forwards from code to behaviour, and backwards from

behaviour to code– Between representations

• Instrumenting the situation– Tools for observing hidden events e.g. print statements

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Dynamic SDE experiment• 42 participants (1st & 2nd year ug)• Verbal and graphical abilities pre-tests• 5 programs

– 1 control,– Graphical-textual visualisations,

– Control-flow, data structure errors

• 1 error each• Static SDE with 4 windows

– Code– Objects– Call sequence– Output

• Breakpoints

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The experimental tool• Modified version of

Restricted Focus Viewer

• Presents blurred image stimuli

• User moves unblurred ‘foveal’ area around screen

• Logs user actions and records audio

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Experimental data• Debugging performance

– Accuracy– Spotting time

• Representation use– Fixation periods– Switching

• Individual differences• (Verbal protocols)

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Debugging accuracy results

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Window fixation results

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Window switching results

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Window switching results

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Breakpoint fixation results

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Critical window fixation results

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Results summary

• Visualisations helpful

• More interaction for intermediates

• Graphical condition associated with more efficient use for best performers

• Positive correlation between graphical literacy and debugging accuracy

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Questions and Conclusions

• How far does window blurring alter programming strategy? e.g. Peripheral vision

• How far can we assume that the unblurred window is the focus of attention?

• How do we interpret time spent focusing on a representation? Utility vs. difficulty

• How do we interpret different patterns of switches? E.g. rapidly between a pair or reps., leisurely between a pair of reps.

• Should we expect stronger interactions between graphical/spatial/textual abilities and representation preferences

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AcknowledgementsRichard Cox

EPSRC

www.cogs.susx.ac.uk/projects/crusade/

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The End

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BlueJ Java tutoringEnvironment

Kolling (2000)Monash University

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Background• Computer programs can be looked at from different

perspectives

• Experienced programmers’ mental representations include multiple perspectives and mappings between them

• SDEs often provide multiple, multimodal, linked and concurrent displays (code, visualisation(s), output)

• Programming requires co-ordination of these

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Some of the Tasks….

• Understanding the problem

• Constructing general approach

• Specifying sequences, entities and relationships

• Coding

• Debugging (at any of the above stages)

• Maintenance

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Static SDE experiment

• 48 participants (1st & 2nd year UG)• Verbal and spatial abilities pre-tests• 4 programs to debug• 4 errors each• Static SDE with 3 windows

– Code

– Visualisation

– Output

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Debugging strategy results

• Qualitative analysis for 2 contrasting participants– Experience

– Verbal ability

• Initial code browsing episode• Two ways of detecting bugs

– by spotting something odd in code browsing episode

– by coordinating representations

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Window fixation results

• Poor performers focus on the code a lot

• Good performers also focus on objects window

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Visualisations

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Representation Issues….

• Cognitive– Relationships between internal and external representations– Structure of knowledge and nature of expertise

• Educational– Evolution of knowledge and its organization from novice to expert– Activities to support learning– Scaffolding needed at various stages

• Aesthetic and Motivational– Nature of the experience– Quality of the artifacts

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Crusade overall aims• Investigate the co-ordination of multiple external

representations in OO program comprehension

• Investigate role of perspective, modality and individual differences in representation co-ordination in programming.

• Develop set of design principles for program comprehension tools

• Develop computerised experimental tool to study representation co-ordination in programming