Software Engineering Commons^™

Activity Transition Graph Generation: How Far Are We?, Jiakun Liu, Peixin Zhang, Han Hu, Yonghui Liu, Wei Minn, Ferdian Thung, Shahar Maoz, Eran Toch, Debin Gao, David Lo

Research Collection School Of Computing and Information Systems

Android applications (i.e., apps) are indispensable nowadays and are getting bigger and bigger with an increasing number offunctionalities. To understand how to access functionalities in an app, prior studies proposed tools to model the transitionsbetween functionalities with the activity transition graph (ATG). ATG is an important data structure and has been used forvarious Android app analyses, including app design, understanding, and testing. However, there is no benchmarking work onATG generation. It is still unclear whether the transitions identified by tools are correct and how many transitions are missed.To fill this gap, we manually identified all transitions in 98 applications to …

Func: Reducing The Impact Of Android Framework Evolution On Malware Detection, Hailong Yu, Tiantian Wang, Lwin Khin Shar, Hanmeng Li, David Lo

Research Collection School Of Computing and Information Systems

Android malware detection approaches commonly use APIs and permissions as features for classifying malware. However, since the release of the first Android operating system in 2008, the Android framework has undergone numerous version updates. The evolution of the Android framework over time has led to changes in APIs and permissions, including deprecations and replacements. These changes can result in inaccurate characterization of Android malware, thereby affecting performance of malware detectors. There is a lack of methods to mitigate the impact of Android framework evolution on malware detection. To fill this gap, we conduct a systematic study of the impact of …

Reminders App Execution, Alexander Gardner

Harrisburg University Other Works

This poster highlights the creation of an Android mobile application for reminders. This app is titled It's Time, Remind! Developed with the Flutter SDK and SQLite for the local database. Firebase Authentication was utilized for user account registration, login/ logout, and profile management. Users can additionally choose to use the app without an account. Users are able to view, create, and delete reminders and notes. Reminders also notify at specified times.

Globelly: The Travel App, Diana S. Alvarez

Honors Capstones

My honors capstone project, Globelly: The Travel App, began as a feature-rich Android application designed to simplify travel planning, enhance global exploration, and foster community-driven sharing among travelers. The app was envisioned to integrate real-time suggestions using APIs like Yelp and TripAdvisor, incorporate a badge-based gamification system, and support advanced customization and privacy controls. While not all of these features were implemented in the final version, the project achieved a solid and functional foundation focused on core travel-sharing experiences.

Developed using Java, XML, and the MVC architecture in Android Studio, the completed app allows users to pin locations they’ve …

Meta-Learning For Multi-Family Android Malware Classification, Yao Li, Dawei Yuan, Tao Zhang, Haipeng Cai, David Lo, Cuiyun Gao, Xiapu Luo, He Jiang

Research Collection School Of Computing and Information Systems

With the emergence of smartphones, Android has become a widely used mobile operating system. However, it is vulnerable when encountering various types of attacks. Every day, new malware threatens the security of users' devices and private data. Many methods have been proposed to classify malicious applications, utilizing static or dynamic analysis for classification. However, previous methods still suffer from unsatisfactory performance due to two challenges. First, they are unable to address the imbalanced data distribution problem, leading to poor performance for malware families with few members. Second, they are unable to address the zero-day malware (zero-day malware refers to malicious …

Minimon: Minimizing Android Applications With Intelligent Monitoring-Based Debloating, Jiakun Liu, Zicheng Zhang, Xing Hu, Thung Ferdian, Shahar Maoz, Debin Gao, Eran Toch, Zhipeng Zhao, David Lo

Research Collection School Of Computing and Information Systems

The size of Android applications is getting larger to fulfill the requirements of various users. However, not all the features of the applications are needed and desired by a specific user. The unnecessary and non-desired features can increase the attack surface and consume system resources such as storage and memory. To address this issue, we propose a framework, MiniMon, to debloat unnecessary features from an Android app based on the logs of specific users' interactions with the app.However, rarely used features may not be recorded during the data collection, and users' preferences may change slightly over time. To address these …

Experimental Comparison Of Features, Analyses, And Classifiers For Android Malware Detection, Lwin Khin Shar, Biniam Fisseha Demissie, Mariano Ceccato, Naing Tun Yan, David Lo, Lingxiao Jiang, Christoph Bienert

Research Collection School Of Computing and Information Systems

Android malware detection has been an active area of research. In the past decade, several machine learning-based approaches based on different types of features that may characterize Android malware behaviors have been proposed. The usually-analyzed features include API usages and sequences at various abstraction levels (e.g., class and package), extracted using static or dynamic analysis. Additionally, features that characterize permission uses, native API calls and reflection have also been analyzed. Initial works used conventional classifiers such as Random Forest to learn on those features. In recent years, deep learning-based classifiers such as Recurrent Neural Network have been explored. Considering various …

Codebert For Code Clone Detection: A Replication Study, Saad Arshad, Shamsa Abid, Shafay Shamail

Research Collection School Of Computing and Information Systems

Large pre-trained models have dramatically improved the state-of-the-art on a variety of natural language processing (NLP) tasks. CodeBERT is one such pre-trained model for natural language (NL) and programming language (PL) which captures the semantics in natural language and programming language, and produces general-purpose representations. While it has been shown to support natural language code search and code documentation generation tasks, its effectiveness for code clone detection is not explored in depth. In this paper, we aim to replicate and evaluate the performance of CodeBERT for code clone detection on multiple datasets with varying functionalities to understand (1) whether CodeBERT …

Uipdroid: Unrooted Dynamic Monitor Of Android App Uis For Fine-Grained Permission Control, Mulin Duan, Lingxiao Jiang, Lwin Khin Shar, Debin Gao

Research Collection School Of Computing and Information Systems

Proper permission controls in Android systems are important for protecting users' private data when running applications installed on the devices. Currently Android systems require apps to obtain authorization from users at the first time when they try to access users' sensitive data, but every permission is only managed at the application level, allowing apps to (mis)use permissions granted by users at the beginning for different purposes subsequently without informing users. Based on privacy-by-design principles, this paper develops a new permission manager, named UIPDroid, that (1) enforces the users' basic right-to-know through user interfaces whenever an app uses permissions, and (2) …

Androevolve: Automated Android Api Update With Data Flow Analysis And Variable Denormalization, Stefanus A. Haryono, Ferdian Thung, David Lo, Lingxiao Jiang, Julia Lawall, Hong Jin Kang, Lucas Serrano, Gilles Muller

Research Collection School Of Computing and Information Systems

The Android operating system is frequently updated, with each version bringing a new set of APIs. New versions may involve API deprecation; Android apps using deprecated APIs need to be updated to ensure the apps’ compatibility with old and new Android versions. Updating deprecated APIs is a time-consuming endeavor. Hence, automating the updates of Android APIs can be beneficial for developers. CocciEvolve is the state-of-the-art approach for this automation. However, it has several limitations, including its inability to resolve out-of-method variables and the low code readability of its updates due to the addition of temporary variables. In an attempt to …

Androevolve: Automated Update For Android Deprecated-Api Usages, Stefanus A. Haryono, Ferdian Thung, David Lo, Lingxiao Jiang, Julia Lawall, Hong Jin Kang, Lucas Serrano, Gilles Muller

Research Collection School Of Computing and Information Systems

The Android operating system (OS) is often updated, where each new version may involve API deprecation. Usages of deprecated APIs in Android apps need to be updated to ensure the apps' compatibility with the old and new versions of the Android OS. In this work, we propose AndroEvolve, an automated tool to update usages of deprecated Android APIs, that addresses the limitations of the state-of-the-art tool, CocciEvolve. AndroEvolve utilizes data flow analysis to solve the problem of out-of-method-boundary variables, and variable denormalization to remove the temporary variables introduced by CocciEvolve. We evaluated the accuracy of AndroEvolve using a dataset of …

Looking Back! Using Early Versions Of Android Apps As Attack Vectors, Yue Zhang, Jian Weng, Jia-Si Wneg, Lin Hou, Anjia Yang, Ming Li, Yang Xiang, Deng, Robert H.

Research Collection School Of Computing and Information Systems

Android platform is gaining explosive popularity. This leads developers to invest resources to maintain the upward trajectory of the demand. Unfortunately, as the profit potential grows higher, the chances of these Apps getting attacked also get higher. Therefore, developers improved the security of their Apps, which limits attackers ability to compromise upgraded versions of the Apps. However, developers cannot enhance the security of earlier versions that have been released on the Play Store. The earlier versions of the App can be subject to reverse engineering and other attacks. In this paper, we find that attackers can use these earlier versions …

Experimental Comparison Of Features And Classifiers For Android Malware Detection, Lwin Khin Shar, Biniam Fisseha Demissie, Mariano Ceccato, Wei Minn

Research Collection School Of Computing and Information Systems

Android platform has dominated the smart phone market for years now and, consequently, gained a lot of attention from attackers. Malicious apps (malware) pose a serious threat to the security and privacy of Android smart phone users. Available approaches to detect mobile malware based on machine learning rely on features extracted with static analysis or dynamic analysis techniques. Dif- ferent types of machine learning classi ers (such as support vector machine and random forest) deep learning classi ers (based on deep neural networks) are then trained on extracted features, to produce models that can be used to detect mobile malware. …

Automatic Android Deprecated-Api Usage Update By Learning From Single Updated Example, Stefanus A. Haryono, Ferdian Thung, Hong Jin Kang, Lucas Serrano, Gilles Muller, Julia Lawall, David Lo, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

Due to the deprecation of APIs in the Android operating system, developers have to update usages of the APIs to ensure that their applications work for both the past and current versions of Android. Such updates may be widespread, non-trivial, and time-consuming. Therefore, automation of such updates will be of great benefit to developers. AppEvolve, which is the state-of-the-art tool for automating such updates, relies on having before- and after-update examples to learn from. In this work, we propose an approach named CocciEvolve that performs such updates using only a single after-update example. CocciEvolve learns edits by extracting the relevant …

Understanding The Relation Between Repeat Developer Interactions And Bug Resolution Times In Large Open Source Ecosystems: A Multisystem Study, Subhajit Datta, Reshma Roychoudhuri, Subhashis Majumder

Research Collection School Of Computing and Information Systems

Large‐scale software systems are being increasingly built by distributed teams of developers who interact across geographies and time zones. Ensuring smooth knowledge transfer and the percolation of skills within and across such teams remain key challenges for organizations. Towards addressing this challenge, organizations often grapple with questions around whether and how repeat collaborations between members of a team relate to outcomes of important activities. In the context of this paper, the word ‘repeat interaction’ does not imply a greater number of interactions; it refers to repeat interaction between a pair of developers who have collaborated before. In this paper, we …

Black Box Analysis Of Android Malware Detectors, Guruswamy Nellaivadivelu, Fabio Di Troia, Mark Stamp

Faculty Publications, Computer Science

If a malware detector relies heavily on a feature that is obfuscated in a given malware sample, then the detector will likely fail to correctly classify the malware. In this research, we obfuscate selected features of known Android malware samples and determine whether these obfuscated samples can still be reliably detected. Using this approach, we discover which features are most significant for various sets of Android malware detectors, in effect, performing a black box analysis of these detectors. We find that there is a surprisingly high degree of variability among the key features used by popular malware detectors.

Automated Deprecated-Api Usage Update For Android Apps: How Far Are We?, Ferdian Thung, Stefanus Agus Haryono, Lucas Serrano, Gilles Muller, Julia Lawall, David Lo, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

As the Android API evolves, some API methods may be deprecated, to be eventually removed. App developers face the challenge of keeping their apps up-to-date, to ensure that the apps work in both older and newer Android versions. Currently, AppEvolve is the state-of-the-art approach to automate such updates, and it has been shown to be quite effective. Still, the number of experiments reported is moderate, involving only API usage updates in 41 usage locations. In this work, we replicate the evaluation of AppEvolve and assess whether its effectiveness is generalizable. Given the set of APIs on which AppEvolve has been …

Android Game, Ryan Weston

Williams Honors College, Honors Research Projects

The purpose of this project was to create an endless runner game for Android coded in Java and XML and developed in Android Studio. In the game, the player controls a frog that jumps from lily pad to lily pad to avoid logs moving toward the player. The player must also maneuver the lily pads as they can randomly disappear. There are three difficulties in the game that vary the disappearance rate of lily pads as well as the frequency and acceleration rate of the log obstacles. The game also has a scoring system and saves the high score locally …

Data For The Review Of Gamified Fitness Tracker Apps, Aatish Neupane, Derek Hansen, Anud Sharma, Jerry Alan Fails

ScholarsArchive Data

This is a supplemental dataset to a paper that reviews 103 gamified fitness tracker apps and analyzes the presence and usage of various game elements. This dataset contains the list of those apps that were reviewed. It also contains the coding that represents the presence of difference game elements.

Advanced Security Analysis For Emergent Software Platforms, Mohannad Alhanahnah

School of Computing: Dissertations, Theses, and Student Research

Emergent software ecosystems, boomed by the advent of smartphones and the Internet of Things (IoT) platforms, are perpetually sophisticated, deployed into highly dynamic environments, and facilitating interactions across heterogeneous domains. Accordingly, assessing the security thereof is a pressing need, yet requires high levels of scalability and reliability to handle the dynamism involved in such volatile ecosystems.

This dissertation seeks to enhance conventional security detection methods to cope with the emergent features of contemporary software ecosystems. In particular, it analyzes the security of Android and IoT ecosystems by developing rigorous vulnerability detection methods. A critical aspect of this work is the …

Towards Generating Transformation Rules Without Examples For Android Api Replacement, Ferdian Thung, Hong Jin Kang, Lingxiao Jiang, David Lo

Research Collection School Of Computing and Information Systems

Deprecation of APIs in software libraries is common when library maintainers make changes to a library and will no longer support certain APIs in the future. When deprecation occurs, developers whose programs depend on the APIs need to replace the usages of the deprecated APIs sooner or later. Often times, software documentation specifies which new APIs the developers should use in place of a deprecated API. However, replacing the usages of a deprecated API remains a challenge since developers may not know exactly how to use the new APIs. The developers would first need to understand the API changes before …

Sensitive Behavior Analysis Of Android Applications On Unrooted Devices In The Wild, Xiaoxiao Tang

Dissertations and Theses Collection (Open Access)

Dynamic analysis is widely used in malware detection, taint analysis, vulnerability detection, and other areas for enhancing the security of Android. Compared to static analysis, dynamic analysis is immune to common code obfuscation techniques and dynamic code loading. Existing dynamic analysis techniques rely on in-lab running environment (e.g., modified systems, rooted devices, or emulators) and require automatic input generators to execute the target app. However, these techniques could be bypassed by anti-analysis techniques that allow apps to hide sensitive behavior when an in-lab environment is detected through predefined heuristics (e.g., IMEI number of the device is invalid). Meanwhile, current input …

Building Recommendation Systems, Orion Davis

Williams Honors College, Honors Research Projects

Recommendation systems are pieces of software that suggest new items to a user. There are many moving parts to these systems including data, the actual recommendation model, processing data and finally displaying data. This project explores the role each part plays in the overall system and how to develop a recommendation system for beer from scratch. This project highlights the algorithm behind the recommendations and a user facing Android application.

Alat Ukur Berat Badan, Tinggi Badan Dan Suhu Badan Di Posyandu Berbasis Android, Tri Hamdani Agung Cahyono, Eko Agus Suprayitno

Elinvo (Electronics, Informatics, and Vocational Education)

Perkembangan ilmu pengetahuan dan teknologi semakin meningkat terutama di bidang elektronika. Hal tersebut menginspirasi peneliti untuk membuat alat yang bersifat ekonomis dan efisien, sehingga mempunyai fungsi utama yaitu untuk mempermudah suatu pekerjaan kader posyandu. Sistem Alat ukur berat badan, tinggi badan dan suhu badan di posyandu berbasis android merupakan pengembangan dari peneliti sebelumnya yang didukung dengan tampilan data angka yang muncul di android untuk mempermudah kader posyandu dalam melihat atau mengamati data angka pada bayi di posyandu. Perancangan alat terdiri dari arduino uno sebagai pengolah data, sensor load cell (berat), sensor ultrasonik (tinggi) dan sensor ds18b20 (suhu) kemudian data angka …

Eye Pressure Monitior, Andrea Nella Levy

Computer Engineering

The document describes a mobile application that takes information from an attached device which tests eye pressure. The device consists of an IOIO board connected to a custom device that measures the frequency of a given waveform. The device was designed by another student for their senior project, which I am taking over. This device is connected to an IOIO board which is a board designed by a Google employee which works with an android phone in order to create applications that work with embedded systems. The board comes with an API and connects to the phone via a micro-USB. …

An Algorithmic Approach To Creating Effective Study Groups Using A Smart Phone App, Kelvin J. Rosado-Ayala

Honors College Theses

For many students entering college, meeting new people and studying are a common struggle. Study groups are generally recommended, especially if the groups are comprised of members with complementary personality traits. But the challenge still remains, how do freshmen or transfer students find and form these heterogeneous study groups. In order to help alleviate this issue, an Android application was developed to automatically create study groups for students. Using basic information provided by students upon registration, the algorithm is able to automatically find matching group members. The application was designed using an agile life cycle model over the course of …

Advanced Malware Detection For Android Platform, Ke Xu

Dissertations and Theses Collection (Open Access)

In the first quarter of 2018, 75.66% of smartphones sales were devices running An- droid. Due to its popularity, cyber-criminals have increasingly targeted this ecosys- tem. Malware running on Android severely violates end users security and privacy, allowing many attacks such as defeating two factor authentication of mobile bank- ing applications, capturing real-time voice calls and leaking sensitive information. In this dissertation, I describe the pieces of work that I have done to effectively de- tect malware on Android platform, i.e., ICC-based malware detection system (IC- CDetector), multi-layer malware detection system (DeepRefiner), and self-evolving and scalable malware detection system (DroidEvolver) …

Ksugo, Chase Godwin

KSU Journey Honors College Capstones and Theses

KSUGo seeks to better enable students to interact with their community, maintain a level of safety on and off campus, improve their course management skills, and increase information propagation among students and campus officials. Currently, Kennesaw State does not have a dedicated general purpose native application on any mobile device platform for students, faculty, or staff to use for improving their everyday Kennesaw State experience. This project seeks to rectify that need by providing a native application with support for the Android platform.

Analisis Aplikasi Jadwal Perkuliahan Berbasis Android, Daniswara Galuh Sukmandari

Elinvo (Electronics, Informatics, and Vocational Education)

Penelitian ini bertujuan untuk menganalisis kualitas perangkat lunak pada aplikasi mobile jadwal perkuliahan berdasarkan standar kualitas ISO 25010 ysng mencakup aspek funtional suitability, compatibility, usability, dan performance efficiency. Metode yang digunakan dalam penelitian adalah Research and Development (R&D) dengan model waterfall. Hasil dari penelitian adalah aplikasi jadwal perkuliahan telah memenuhi standar kualitas perangkat lunak berdasarkan standar ISO 25010. Pengujian functional suitabilitymendapatkan hasil sebesar 100% yang berarti fungsi aplikasi telah berjalan dengan benar.Pengujian compatibilitymendapatkan hasil sebesar 100%. Pengujian usabilitymendapatkan hasil sebesar 79,63% dengan kategori Layak. Pengujian performance efficiencymendapatkan rata-rata waktu launchingsebesar 2,048 detik dan 0,095 detik untuk rata-rata waktu rendering

Evaluasi Kualitas Aplikasi Mobile Kamus Istilah Jaringan Pada Platform Android Dengan Standar Iso/Iec 25010, Rohmad Dwi Jayanto

Elinvo (Electronics, Informatics, and Vocational Education)

Penelitian ini bertujuan untuk menguji aplikasi mobile kamus istilah jaringan komputer pada platform android menggunakan standar kualitas perangkat lunak ISO/IEC 25010 pada aspek functional suitability, compatibility, performance efficiency, danusability. Metode yang digunakan adalah research and development. Hasil dari penelitian ini menunjukkan bahwa aplikasi telah memenuhi standar ISO/IEC 25010 pada aspek (1) functional suitability seluruh fungsi dari aplikasi berjalan 100% yang artinya tidak ada fungsi yang gagal saat dilakukan pengujian, (2) compatibility aplikasi kompatibel 100% darisisico-existence, berbagai sistem operasi dan tipe perangkat yang digunakan untuk pengujian, (3) performance efficiency aplikasi berhasil dijalankan di 436 dari 452 perangkatuji AWS Device …