User Involvement
We investigate how end users can be involved in software evolution. More specifically, we develop and evaluate approaches to collect and analyze textual in-app user feedback, app store feedback, and user interactions. So far, we analyzed app store feedback to identify features and sentiments, we automatically classified user feedback into UUX and software evolution dimensions, used tagging to structure textual user feedback, and analyzed monitored user interactions to identify failure reproduction steps, user skills, and deviations of user behavior from use cases.
Research Members
Rana Alkadhi
Master of Science
Doctoral Candidate
Tobias Röhm
Master of Science
Doctoral Candidate
Emitzá Guzmán Ortega
Master of Science
Doctoral Candidate
Jan Ole Johanßen
Master of Science
Doctoral Candidate
Projects Partners and Co-operations
| Name | Partner |
|---|---|
| FastFix http://fastfixrsm.sourceforge.net/fastfix-project/ | See http://fastfixrsm.sourceforge.net/fastfix-project/ |
| URES http://www.dfg-spp1593.de/index.php?id=38 | Uni Heidelberg |
| ReproFit | Software AG, Softwarecampus |
Theses Offered
Theses In Progress
Masterthesis
An Intelligent System for Constructing User Interfaces for Web Applications
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Theses Finished
Master's Thesis
A context-sensitive user feedback mechanism for continuous software evolution
Advisor
Stephan Krusche
Date
October 2015
Regular user feedback is important, as it helps to validate requirements and improves user satisfaction. However, it fails to unfold its full potential in many projects. Common challenges include low user motivation, fragmented feedback channels, and missing information, making it difficult for the development team to extract the underlying requirements of the user. We aim to address these problems by proposing a system for Context-Aware Feedback (CAFE), which integrates user feedback into the software evolution process. The objective is to provide a channel for users to give feedback with as little effort as possible in order to bridge the gap between users and developers. CAFE stores feedback directly in the issue tracker enriching it with recorded usage context and visualizes the evolution of requirements through user feedback. In a formative evaluation with controlled user experiments we found that both developers and users prefer CAFE to other feedback channels and that automatically gathered context data is useful. Both the fact that user feedback is saved in the issue tracker and the added value of Feedback Traceability are regarded as beneficial.
Masterthesis
Analysis of Personalities and Sentiments in User Feedback
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Masterthesis
Mining and Visualizing User Feedback for Software Evolution
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Masterthesis
Automatic Usability and User Experience Analysis in User Feedback
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Masterthesis
Classification of User Feedback for Software Evolution
Advisor
Tobias Röhm
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Masterthesis
Presenting User and Context Information to Developers during Bug Fixing
Advisor
Tobias Röhm
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Masterthesis
Detecting Behavioural Patterns in User Actions
Advisor
Tobias Röhm
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Masterthesis
Recommending and Automating Frequently Occurring Action Patterns of Software End Users
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Masterthesis
Analytics of Software Features Based on Monitored User Actions
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Masterthesis
Mining Social Media Data for Creating Personas in Software Engineering
Advisor
Emitzá Guzmán Ortega, Rana Alkadhi
Bachelorthesis
User Feedback and Rationale Management in Continuous Software Evolution
Advisor
Dora Dzvonyar
Date
04/2016
User feedback is difficult to use as a basis for implementation. For this purpose, we introduce FeedViz, a feedback visualisation component which analyses, structures and prioritises user feedback and illustrates the results to the development team. The aim is to simplify the decision-making process as well as to capture information related to feedback which is important for rationale management.
Masterthesis
A context-sensitive user feedback mechanism for continuous software evolution
Advisor
Stephan Krusche, Rana Alkadhi