When Users Becom Collaborators: Towards Continuous and Context-Aware User Input

When Users Become Collaborators: Towards Continuous and Context-Aware User Input Walid Maalej (TU München) Hans-Jörg Happel , Asarnusch Rashid (FZI Karlsruhe) OOPSLA Onward! Orlando, FL, October 29 th , 2009

Outline Motivation A Benchmarking A New Approach Technical Enablers Next Steps

Reasons for project failure

Incomplete Requirements

No customer requirements

Lack of resources

Unrealistic expectations

Uncontrolled changes of

requirements

User involvement is critical for the success of software development projects 13% 12% 11% 10% 9% Reasons for project success Customer/User involvement Ex. Management support Clear Statement of requirements Proper planning Realistic expectations 16% 14% 13% 10% 8% [Standish Group 2003, recent studies with similar results]

Various concepts to address end users in software development

Various types of user input ? Perpetual Beta Legacy Documents Usage Data Implicit Explicit Pull Push Issue and Bug Report Enhancement Request Feature Request Workshop Interview, Survey Clarification Request Field Observation Lead Users (Not used in SE) Communication Feedback

Various realizations of user input

Mysterious stack traces

Bug reports from within a program

Application usage data

Discussions in user communities

Various realizations of user input …but most applications still do not consider feedback at all…

Problems of the status quo

Gaps through fragmented streams of user interaction – feedback cross-cuts proceses

User input difficult to understand

No frameworks for systematic integration into application

How can we make user Input as a first-order concern in both processes and architectures? For Engineers For Users

User input is usually…

Tedious to provide (e.g. writing detailed context information)

Incomplete or imprecise

Focussed on one particular step (e.g. bug reporting)

Uni-directional and singular

Streams of interaction Requirements Engineers Users Realization Provision Deployment Problem Usage Evolution Fix Question Support

A Continuous Feedback Model Prospective Observation Assisted Feedback Improvement D ecision Back- Feedback Systematic Analysis Application User Engineering Team Development Infrastructure Community Sharing

Technical building blocks Visual Annotation Recommend end user to share their experience with engineering teams end other end users Observation & Context Elicitation Allow user to annotate and „paint“ on the GUI in the work context Proactive Assistance Detect user intention and problem situations through observation of user and application Making user input a 1 st order concern

TeamWeaver Context Framework problem problem Execution Ontology Interaction Ontoloy Feedback Reporting Interface OS sensors User Profile Elicitation Problem events update trigger A pplication sensors Execution Env. sensors A dditional feedback interact Session- ization Context Observer http://www.teamweaver.org

Visual Annotation with OpenProposal End user application http://www.openproposal.de OpenProposal plus Username, Application, Version, Date, etc. Issue Tracker

Inverse Search to recommend users to share their experience

Conventional recommendation systems:

Match interests of users against a given set of information

Push information to the user

Users providing information are not part of this model although they are potential sources for additional information

Recommendation using inverse search:

Matches the private/local information of users (information providers) against a given set of needs

Identify information (e.g. experiences and interactions) worth sharing

Experiences Needs 3. iSearch 4. Share 1. Query 2. Results Engineer / User Information Seeker User Information Provider

Conclusion

Feasability

Technical building blocks are there

Further technologies to enable tighter collaboration between users and developers emerge (e.g. Microblogging)

Communication and transparency in Open Source projects

Several services on the web decide on realization options based on implicit feedback

Users are motivated by feedback

Challenges

Privacy

Development culture

Non-intrusiveness

Context-similarity

Summary

Results

Comparing different types of user input

Identification of technology and process enablers for feedback-driven development

User input deserves to become a first order concern in development processes and architectures

How can users become prosumers instead of mere consumers of applications?

How to give engineering teams more continuous, direct and rich input for development?

Tools

www.teamweaver.org

www.openproposal.de

References

Walid Maalej and Hans-Joerg Happel: A Lightweight Approach for Knowledge Sharing in Distributed Software Teams. In Proceeedings of the 7th International Conference on Practical Aspects of Knowledge Management (PAKM2008).

Happel, H.-J. and Maalej, W.: Potentials and Challenges of Recommendation Systems for Software Development. In Proceedings of the International Workshop on Recommendation Systems for Software Engineering (RSSE 2008).

Rashid, A., Wiesenberger, J., Meder, D. Baumann , J.: Bringing Developers and Users closer together: The OpenProposal story. In: Multikonferenz Wirtschaftsinformatik 2008 (MKWI 2008), 26.2. - 28.2.2008, München.

Standish Group: The 2003 CHAOS Chronicles report.

Walid Maalej: Task-First or Context-First? Tool Integration Revisited. In: 24th IEEE/ACM International conference on Automated Software Engineering (ASE 2009) Auckland, New Zealand. 16th-20th November 2009.