• Quick Links
• 1. Data
• 2. CRISTAL
• 3. Results
• *Authors

Crowdsourcing User Reviews to Support the Evolution of Mobile Apps - JSS Online Appendix

This web page is a companion to our JSS submission entitled "Crowdsourcing User Reviews to Support the Evolution of Mobile Apps".

1. Data

Android apps

The list of apps used in our study is available as a CSV file. It includes the links to Google Play, issue trackers, and source code repositories

Data

• Stop words list
• Summary of traceability oracles manually defined for the ten apps in RQa
• Data table used to generate the reported tables and figures
• R script used to generate the reported tables and figures
• Raw data of the questionnaire with Android developers

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2. CRISTAL

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3. Results

Developers Background

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RQ1: To what extent do developers fulfill reviews when working on a new app release?

Review coverage of the 70 apps

RQ2: What is the effect of a crowd review mechanism (for planning and realizing future changes) on the app success?

Boxplots of avgerate ratio change for apps having different coverage levels. The red dot indicates the mean

F-Average Score vs Similarity Treshold

Raw data for the analysis

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*Authors

• Fabio Palomba - University of Salerno, Fisciano (SA), Italy
  E-mail: fpalomba at uinisa dot it
• Mario Linares-Vásquez - Universidad de los Andes, Bogotá, Colombia
  E-mail: m.linaresv at uniandes dot edu dot co
• Gabriele Bavota - University of Sannio, Benevento, Italy.
  Email: gbavota at unisannio dot it
• Rocco Oliveto - University of Molise, Pesche (IS), Italy.
  E-mail: rocco.oliveto at unimol dot it
• Massimiliano Di Penta - University of Sannio, Benevento, Italy.
  Email: dipenta at unisannio dot it
• Denys Poshyvanyk - The College of William and Mary, VA, USA
  E-mail: denys at cs dot wm dot edu
• Andrea De Lucia - University of Salerno, Fisciano (SA), Italy
  E-mail: adelucia at uinisa dot it