Skip to main content
main-content

Tipp

Weitere Artikel dieser Ausgabe durch Wischen aufrufen

17.04.2019

iPerfDetector: Characterizing and detecting performance anti-patterns in iOS applications

Zeitschrift:
Empirical Software Engineering
Autoren:
Sara Seif Afjehei, Tse-Hsun (Peter) Chen, Nikolaos Tsantalis
Wichtige Hinweise
Communicated by: David Lo, Meiyappan Nagappan, Fabio Palomba and Sebastian Panichella

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Abstract

Performance issues in mobile applications (i.e., apps) often have a direct impact on the user experience. However, due to limited testing resources and fast-paced software development cycles, many performance issues remain undiscovered when the apps are released. As found by a prior study, these performance issues are one of the most common complaints that app users have. Unfortunately, there is a limited support to help developers avoid or detect performance issues in mobile apps. In this paper, we conduct an empirical study on performance issues in iOS apps written in Swift language. To the best of our knowledge, this is the first study on performance issues of apps on the iOS platform. We manually studied 225 performance issues that are collected from four open source iOS apps. We found that most performance issues in iOS apps are related to inefficient UI design, memory issues, and inefficient thread handling. We also manually uncovered four performance anti-patterns that recurred in the studied issue reports. To help developers avoid these performance anti-patterns in the code, we implemented a static analysis tool called iPerfDetector. We evaluated iPerfDetector on eight open source and three commercial apps. iPerfDetector successfully detected 34 performance anti-pattern instances in the studied apps, where 31 of them are already confirmed and accepted by developers as potential performance issues. Our case study on the performance impact of the anti-patterns shows that fixing the anti-pattern may improve the performance (i.e., response time, GPU, or CPU) of the workload by up to 80%.

Bitte loggen Sie sich ein, um Zugang zu diesem Inhalt zu erhalten

Sie möchten Zugang zu diesem Inhalt erhalten? Dann informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 58.000 Bücher
  • über 300 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb




Testen Sie jetzt 30 Tage kostenlos.

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 50.000 Bücher
  • über 380 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Umwelt
  • Maschinenbau + Werkstoffe​​​​​​​




Testen Sie jetzt 30 Tage kostenlos.

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 69.000 Bücher
  • über 500 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Umwelt
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe

Testen Sie jetzt 30 Tage kostenlos.

Literatur
Über diesen Artikel

Premium Partner

    Bildnachweise