2016 IEEE/ACM International Conference on Mobile Software Engineering and Systems (MOBILESoft)最新文献_第2页

An Empirical Study of the Performance Impacts of Android Code Smells Android代码气味对性能影响的实证研究

2016 IEEE/ACM International Conference on Mobile Software Engineering and Systems (MOBILESoft) Pub Date : 2016-05-14 DOI: 10.1145/2897073.2897100

Geoffrey Hecht, Naouel Moha, Romain Rouvoy

{"title":"An Empirical Study of the Performance Impacts of Android Code Smells","authors":"Geoffrey Hecht, Naouel Moha, Romain Rouvoy","doi":"10.1145/2897073.2897100","DOIUrl":"https://doi.org/10.1145/2897073.2897100","url":null,"abstract":"Android code smells are bad implementation practices within Android applications (or apps) that may lead to poor software quality, in particular in terms of performance. Yet, performance is a main software quality concern in the development of mobile apps. Correcting Android code smells is thus an important activity to increase the performance of mobile apps and to provide the best experience to mobile end-users while considering the limited constraints of mobile devices (e.g., CPU, memory, battery). However, no empirical study has assessed the positive performance impacts of correcting mobile code smells. In this paper, we therefore conduct an empirical study focusing on the individual and combined performance impacts of three Android performance code smells (namely, Internal Getter/Setter, Member Ignoring Method, and HashMap Usage) on two open source Android apps. To perform this study, we use the Paprika toolkit to detect these three code smells in the analyzed apps, and we derive four versions of the apps by correcting each detected smell independently, and all of them. Then, we evaluate the performance of each version on a common user scenario test. In particular, we evaluate the UI and memory performance using the following metrics: frame time, number of delayed frames, memory usage, and number of garbage collection calls. Our results show that correcting these Android code smells effectively improve the UI and memory performance. In particular, we observe an improvement up to 12.4% on UI metrics when correcting Member Ignoring Method and up to 3.6% on memory-related metrics when correcting the three Android code smells. We believe that developers can benefit from these results to guide their refactoring, and thus improve the quality of their mobile apps.","PeriodicalId":296509,"journal":{"name":"2016 IEEE/ACM International Conference on Mobile Software Engineering and Systems (MOBILESoft)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132455630","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 85

Profiling the Responsiveness of Android Applications via Automated Resource Amplification 通过自动资源放大分析Android应用程序的响应性

2016 IEEE/ACM International Conference on Mobile Software Engineering and Systems (MOBILESoft) Pub Date : 2016-05-14 DOI: 10.1145/2897073.2897097

Yan Wang, A. Rountev

{"title":"Profiling the Responsiveness of Android Applications via Automated Resource Amplification","authors":"Yan Wang, A. Rountev","doi":"10.1145/2897073.2897097","DOIUrl":"https://doi.org/10.1145/2897073.2897097","url":null,"abstract":"The responsiveness of the GUI in an Android application is an important component of the user experience. Android guidelines recommend that potentially-expensive operations should not be performed in the GUI thread, but rather in separate threads. The responsiveness of existing code can be improved by introducing such asynchronous processing, either manually or automatically. One simple view is that all potentially-expensive operations should be removed from the GUI thread. We demonstrate that this view is too simplistic, because run-time cost under reasonable conditions may often be below the threshold for poor responsiveness. We propose a profiling approach to characterize response times as a function of the size of a potentially-expensive resource (e.g., shared preferences store, bitmap, or Silt database). By manipulating and \"amplifying\" such resources automatically, we can obtain a responsiveness profile for each GUI-related callback. The profiling is based on a static analysis to generate tests that trigger expensive operations, followed by a dynamic analysis of amplified test execution. Based on our evaluation, we conclude that many operations can be safely left in the GUI thread. These results highlight the importance of choosing carefully - based on profiling information - the operations that should be removed from the GUI thread, in order to avoid unnecessary code complexity.","PeriodicalId":296509,"journal":{"name":"2016 IEEE/ACM International Conference on Mobile Software Engineering and Systems (MOBILESoft)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131664602","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 29

Mobile User Identification through Authentication Using Keystroke Dynamics and Accelerometer Biometrics 使用击键动力学和加速度计生物识别技术的移动用户身份验证

2016 IEEE/ACM International Conference on Mobile Software Engineering and Systems (MOBILESoft) Pub Date : 2016-05-14 DOI: 10.1145/2897073.2897111

Kyle R. Corpus, Ralph Joseph DL. Gonzales, Alvin Scott Morada, L. Vea

{"title":"Mobile User Identification through Authentication Using Keystroke Dynamics and Accelerometer Biometrics","authors":"Kyle R. Corpus, Ralph Joseph DL. Gonzales, Alvin Scott Morada, L. Vea","doi":"10.1145/2897073.2897111","DOIUrl":"https://doi.org/10.1145/2897073.2897111","url":null,"abstract":"Biometrics is everything that can be measured in a human being. It has two types; behavioral and physiological. This paper discusses the use of keystroke dynamics, a form of behavioral biometrics that deals with the measure of how a person types, and the utilization of accelerometer biometrics as a form of behavioral biometric that measures how a person holds his mobile device. We collected biometric data from 30 volunteer participants by asking them to enter their 8-16-character password specimens 8 times using a customized tool in a mobile phone. The first 6 collection from each participant was set aside for the training set while the other 2 is for the test set. The data were then processed and extracted keystroke dynamic and accelerometer biometrics using a customized tool written in Java. Several well-known classifiers were trained using keystroke dynamic features alone, accelerometer biometrics alone, and the combination of both. Results show that Neural Network classifier using the combined features gave the most acceptable model. The model performance was further improved by removing some low ranking features defined by the Chi Square attribute evaluator and by removing some features that are highly correlated to other features.","PeriodicalId":296509,"journal":{"name":"2016 IEEE/ACM International Conference on Mobile Software Engineering and Systems (MOBILESoft)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122983161","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 27

Blending Mobile Programming and Liberal Education in a Social-Economic High School 一所社会经济高中融合移动编程与通识教育

2016 IEEE/ACM International Conference on Mobile Software Engineering and Systems (MOBILESoft) Pub Date : 2016-05-14 DOI: 10.1145/2897073.2897096

Ilenia Fronza, Nabil El Ioini, Luis Corral

引用次数: 12

Comparing Performance Parameters of Mobile App Development Strategies 比较手机应用开发策略的性能参数

2016 IEEE/ACM International Conference on Mobile Software Engineering and Systems (MOBILESoft) Pub Date : 2016-05-14 DOI: 10.1145/2897073.2897092

M. Willocx, Jan Vossaert, Vincent Naessens

引用次数: 46

Inter-App Communication between Android Apps Developed in App-Inventor and Android Studio 在App-Inventor和Android Studio中开发的Android应用程序之间的应用间通信

2016 IEEE/ACM International Conference on Mobile Software Engineering and Systems (MOBILESoft) Pub Date : 2016-05-14 DOI: 10.1145/2897073.2897117

L. A. Allison, M. M. Fuad

引用次数: 6

App Security with JSFlow 应用安全与JSFlow

2016 IEEE/ACM International Conference on Mobile Software Engineering and Systems (MOBILESoft) Pub Date : 2016-05-14 DOI: 10.1145/2897073.2897714

Daniel Hedin

引用次数: 0

Migrating User Interfaces in Native Mobile Applications: Android to iOS 原生移动应用程序的用户界面迁移:Android到iOS

2016 IEEE/ACM International Conference on Mobile Software Engineering and Systems (MOBILESoft) Pub Date : 2016-05-14 DOI: 10.1145/2897073.2897101

Xiaochao Fan, Kenny Wong

引用次数: 10

PVDetector: A Detector of Privacy-Policy Violations for Android Apps PVDetector: Android应用程序违反隐私政策的检测器

2016 IEEE/ACM International Conference on Mobile Software Engineering and Systems (MOBILESoft) Pub Date : 2016-05-14 DOI: 10.1145/2897073.2897720

Rocky Slavin, Xiaoyin Wang, M. Hosseini, James Hester, R. Krishnan, Jaspreet Bhatia, T. Breaux, Jianwei Niu

引用次数: 9

Identifying Android Inter-app Communication Vulnerabilities Using Static and Dynamic Analysis 使用静态和动态分析识别Android应用间通信漏洞

2016 IEEE/ACM International Conference on Mobile Software Engineering and Systems (MOBILESoft) Pub Date : 2016-05-14 DOI: 10.1145/2897073.2897082

Biniam Fisseha Demissie, Davide Ghio, M. Ceccato, Andrea Avancini

引用次数: 16