Domain Matters: Bringing Further Evidence of the Relationships among Anti-patterns, Application Domains, and Quality-related Metrics in Java Mobile Apps - ICPC 2014 / Online Appendix

This web page is a companion to our ICPC 2014 paper entitled "Domain Matters: Bringing Further Evidence of the Relationships among Anti-patterns, Application Domains, and Quality-related Metrics in Java Mobile Apps".

1. Data


The JME apps used in the study were downloaded from ShareJar. Then, the metrics and anti-patterns/code smells were computed and detected by using the Ptidej tool suite. The Object Oriented metrics we used in the study are listed here. JME apps in ShareJar are categorized using the following list of categories (we used those categories as representative of application domains):
Id Label description
1 A Chat & SMS
2 B Dictionaries & Translators
3 C Education
4 D Free Time
5 E Internet
6 F Localization
7 G Messengers
8 H Music
9 I Science
10 L Utilities
11 M Emulators
12 N Programming
13 O Sports & Health
In the following we list the applications, the occurrences of anti-patterns and code smells on those apps, and the values for the OO metrics on the apps:
* The spreadsheet has code-smells and anti-patterns counts.


2. Results



3. Tools

  • Ptidej tool suite: anti-patterns detection; OO metrics extraction.
  • R: correlations and statistical tests.


Authors

  • Mario Linares-Vásquez - The College of William and Mary. E-mail: mlinarev at cs dot wm dot edu
  • Samuel Klock - Akamai Technologies.  E-mail: sam.klock at gmail dot com
  • Collin McMillan - University of Notre Dame.  E-mail: cmc at nd dot edu
  • Aminata Sabané - École Polytechnique de Montréal. E-mail: aminata dot sabane at polymtl dot ca 
  • Denys Poshyvanyk - The College of William and Mary. E-mail: denys at cs dot wm dot edu
  • Yann-Gaël Guéhéneuc - École Polytechnique de Montréal. E-mail: yann-gael dot gueheneuc at polymtl dot ca