Automatically Discovering, Reporting and Reproducing Android Application Crashes

Mobile developers face unique challenges when detecting and reporting crashes in apps due to their prevailing GUI event-driven nature and additional sources of inputs (e.g., sensor readings). To support developers in these tasks, we introduce a novel, automated approach called CRASHSCOPE. This tool explores a given Android app using systematic input generation, according to several strategies informed by static and dynamic analyses, with the intrinsic goal of triggering crashes. When a crash is detected, CRASHSCOPE generates an augmented crash report containing screenshots, detailed crash reproduction steps, the captured exception stack trace, and a fully replayable script that automatically reproduces the crash on a target device(s). We evaluated CRASHSCOPE's effectiveness in discovering crashes as compared to five state-of-the-art Android input generation tools on 61 applications. The results demonstrate that CRASHSCOPE performs about as well as current tools for detecting crashes and provides more detailed fault information. Additionally, in a study analyzing eight real-world Android app crashes, we found that CRASHSCOPE's reports are easily readable and allow for reliable reproduction of crashes by presenting more explicit information than human written reports.Comment: 12 pages, in Proceedings of 9th IEEE International Conference on Software Testing, Verification and Validation (ICST'16), Chicago, IL, April 10-15, 2016, pp. 33-4

DroidNet: An Android Application Security Framework through Crowdsourcing

In the current Android architecture, users have to decide whether an app is safe to use or not by themselves. Savvy users can make correct decisions to avoid unnecessary privacy breaches, however most users are not capable or do not care to make impactful decisions. To assist those users, we propose DroidNet, an Android permission control framework based on crowdsourcing. In this framework, DroidNet runs new apps and their permissions initially, and then collects data based on each individual user’s settings in regards to each permission unique to every installed app. After collecting each user’s data, DroidNet provides recommendations on whether to accept or reject the permission requests based on decisions from peer expert users. To seek expert users, we utilize an expertise ranking algorithm using a transitional Bayesian inference model. The recommendation, respective to each application permission, is based on the aggregated expert responses and our generated confidence level, which are collectively stored and sorted in our DroidNet database. The overall culmination of the model resulted in the creation of a real-time Android application which utilizes our Bayesian inference model and aggregate data from each individual user, all of which is connected to our DroidNet database.https://scholarscompass.vcu.edu/capstone/1173/thumbnail.jp

Image processing of periapical radiograph on granuloma detection by analysis method based on Android

Objectives: The study assesses periapical radiograph image with various android based analysis method to detect granuloma. Materials and Methods: The study uses survey descriptive cross sectional by using questionnaire. The questionnaire is distributed to 70 random respondents. The methods of the android application used are BLOB (Binary Large Object), DCT and LDA (Discrete Cosine Transform and Linier Discriminant Analysis), DWT and PCA (Discrete Wavelet Transform & Principal Component Analysis), and multiwavelet transformation. The questionnaire assessment included accuracy, effectiveness, attractiveness, innovativeness of the android application. Results: Android application with BLOB has effectivity and accuracy of 62,5%, attractiveness and innovativeness of 75%. Android application with DCT and LDA has effectivity and accuracy of 50 %, attractiveness of 70% and innovativeness of 80%. Android application with DWT and PCA has effectivity of 50%, accuracy of 60%, attractiveness of 66,66% and innovativeness of 80%. Android application with multiwavelet transformation has effectivity and accuracy of 50%, attractiveness of 55% and innovativeness of 73%. Conclusion: Based on assessment, the four methods used to detect granuloma are effective and applicative with android-based application. Android-based Application can detect granuloma with approximately more than 70% successful rate. These methods ease the practitioner to interpret the granuloma image

Android application development

The purpose of this thesis was to investigate the design and implementation process of an Android application which uses a web service. The idea of the application was to join an Android user and an Android developer for creating better applications. In addition, the objective of this thesis was to develop a prototype which operates with the Parse web service. The theoretical part of the thesis discussed the Android platform, its history, the compatible web services and the methods used in this thesis process. The empirical part of the thesis describes the whole process of developing an Android application which uses a web service. The emphasis was set on finding out how a program would work with the Parse web service. The tools that were used during the development phase were Eclipse with the ADT plug-in, the Android SDK and the Parse SDK. The result of this thesis project was a working Android application which can connect to the Parse web service. The application can input and retrieve data from it and display information to the user. The thesis concludes that the study at hand can be extended with further development of the application by improving the design and adding more functionality. Moreover, it is possible to improve the user experience by creating a website for the application which would use the same web service

FINSERV ANDROID APPLICATION

The FINSERV Android application is a mobile tool designed for individuals to manage and track their finances. In financially complex world, many people struggle to maintain a clear overview of their income, expenses, and financial goals. This application aims to bridge that gap by providing users with a powerful and user-friendly platform to efficiently monitor and optimize their personal finances. With the Personal Finance Tracking Android Application, users can effortlessly track their income and expenses, categorize transactions, and gain valuable insights into their spending patterns. The application offers features such as expense categorization and real-time expense tracking. To enhance usability and understanding, the application employs data visualization techniques. Financial information is presented in clear and concise graphs, charts, and reports, making it easy for users to comprehend their financial status at a glance. This visual representation enhances financial literacy and enables users to make informed decisions

Android application collusion demystified

Application collusion is an emerging threat to Android based devices. In app collusion, two or more apps collude in some manner to perform a malicious action that they are unable to do independently. Detection of colluding apps is a challenging task. Existing commercial malware detection systems analyse each app separately, hence fail to detect any joint malicious action performed by multiple apps through collusion. In this paper, we discuss the current state of research on app collusion and open challenges to the detection of colluding apps. We compare existing approaches and present an integrated approach to effectively detect app collusion

Perancangan Smart Locker dengan Implementasi Sistem IoT dan Aplikasi Mobile Android

A locker is a storage facility that can be seen at several public facilities such as public swimming pools, a library, and sports facilities like a gymnasium. Most lockers at public facilities still use conventional locking techniques. This has a negative impact in terms of effectiveness, efficiency, and security. Therefore, a QR-Code-based system that is integrated with the android application has been created to function for monitoring availability, borrowing lockers, and opening and locking lockers through the android application. Smart locker system using ESP32 as microcontroller and network that used to receive data sent from android application. When data is received, ESP32 will respond by activating the relay which controls the magnetic lock that replaced the conventional lock, while the android application is created for monitoring locker availability, borrowing lockers, and opening and locking lockers through the android application. This test is carried out for this application, which refers to the ISO 25010 standard with aspects of functional suitability, usability, and compatibility. The results of testing aspects of functional suitability and compatibility get 100% feasibility percentage results. Then for usability, it shows that from the 10-point questionnaire distributed to respondents, the percentage of feasibility results is 78.98% which is included in the acceptable category, this shows that the mobile application has good quality. The system test was done by pressing the button in the android application at the same time with two different devices and having a time difference while opening the lockers with a time average of 0.874 seconds