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Understanding Source Code Variability in Cloned Android Families: An Empirical Study on 75 Families
2019
2019 26th Asia-Pacific Software Engineering Conference (APSEC)
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We perform an empirical study on 75 android families to gain insights about observable phenomena related to the commonality and variability between the source code of PVs of these families. ...
In particular, we study three research questions to identify the commonality and variability related to the organization of source code files, cloning Java methods, and configuration parameters of AndroidManifest.xml ...
CONCLUSION AND FUTURE WORKS We performed an empirical study on 75 android families developed using clone-and-own approach in fork-based development. ...
doi:10.1109/apsec48747.2019.00047
dblp:conf/apsec/ShatnawiZM19
fatcat:juz3d7cl3zf5riz2zc5hk7orym
A Survey of Android Malware Static Detection Technology Based on Machine Learning
2021
Mobile Information Systems
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In this paper, we investigated Android applications' structure, analysed various sources of static features, reviewed the machine learning methods for detecting Android malware, studied the advantages ...
To detect Android malware, researchers have proposed various techniques, among which the machine learning-based methods with static features of apps as input vectors have apparent advantages in code coverage ...
malware detection, familial clustering, app clone detection, and app recommendation tasks. ...
doi:10.1155/2021/8896013
doaj:9dc548d197fd404fbcd4ee962f374bde
fatcat:mbuavifbmzfmjm3shzm4wcbm4a
The MalSource Dataset: Quantifying Complexity and Code Reuse in Malware Development
[article]
2018
arXiv
pre-print
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study the extent to which code reuse is present in our dataset. ...
We detect a significant number of code clones across malware families and report which features and functionalities are more commonly shared. ...
CONCLUSION In this paper, we have presented a study on the evolution of malware source code over the last four decades, as well as a study of source code reuse among malware families. ...
arXiv:1811.06888v1
fatcat:3vjjtk2eqngvfgro2btqepvwai
Self-protection of Android systems from inter-component communication attacks
2018
Proceedings of the 33rd ACM/IEEE International Conference on Automated Software Engineering - ASE 2018
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In Chapter 4, we show, via a large-scale empirical study, the effect of code obfuscation on Android apps and anti-malware products. ...
A Large-Scale Empirical Study on the Effects of Code Obfuscations on Android Apps and Anti-Malware Products. Mahmoud Hammad, Hamid Bagheri, and Sam Malek. ...
The experimental evaluations show that RevealDroid achieves an accuracy of 98% in detection of malware and an accuracy of 95% in determination of their families. ...
doi:10.1145/3238147.3238207
dblp:conf/kbse/HammadGM18
fatcat:qht4e54ehjfltlht6wjuwzsata
Machine Learning-Based Routing and Wavelength Assignment in Software-Defined Optical Networks
2019
IEEE Transactions on Network and Service Management
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For this, different parts of the source code of any two applications are compared to look for hints on whether they have been cloned. ...
While previous work mainly focuses on other characteristics of Android apps, like application code or behavior, our aim is to study meta-data and use it in the detection of malware applications. ...
doi:10.1109/tnsm.2019.2927867
fatcat:or3lhqdqbnas3cztwkqr5ykhhq
Identifying Major Research Areas and Minor Research Themes of Android Malware Analysis and Detection Field Using LSA
2021
Complexity
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An empirical overview of contemporary machine learning methods, which have the potential to expedite evidence synthesis within research literature, has been explained. ...
TRENDMINER uncovered the intellectual structure of a corpus of 444 abstracts of research articles (published during 2010–2019) on Android malware analysis and detection. ...
on an Android device. ...
doi:10.1155/2021/4551067
fatcat:nb5q2ult5fg55fs4c5sasz6fii
A Comprehensive Review of Android Security: Threats, Vulnerabilities, Malware Detection, and Analysis
2022
Security and Communication Networks
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The popularity and open-source nature of Android devices have resulted in a dramatic growth of Android malware. ...
Most of the researchers have focused on Android system security. ...
An attacker can embed malicious code in the original source code and repack the APK file. Figure 21(a) shows control flow graph of malicious source code. ...
doi:10.1155/2022/7775917
fatcat:ux2eun5y4bbfxlqkc36glj2fxq
Rebooting Research on Detecting Repackaged Android Apps: Literature Review and Benchmark
[article]
2018
arXiv
pre-print
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Repackaging is a serious threat to the Android ecosystem as it deprives app developers of their benefits, contributes to spreading malware on users' devices, and increases the workload of market maintainers ...
In the space of six years, the research around this specific issue has produced 57 approaches which do not readily scale to millions of apps or are only evaluated on private datasets without, in general ...
The authors would like to thank the anonymous reviewers who have provided insightful and constructive comments that have led to important improvements in several parts of the manuscript. ...
arXiv:1811.08520v1
fatcat:zjpauswnn5fprdqdnetp3zbhfu
A Survey on Deep Learning for Software Engineering
[article]
2020
arXiv
pre-print
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To fill this gap, we performed a survey to analyse the relevant studies published since 2006. We first provide an example to illustrate how deep learning techniques are used in SE. ...
There are many factors, e.g., deep learning model selection, internal structure differences, and model optimization techniques, that may have an impact on the performance of DNNs applied in SE. ...
[36, 42, 75, 80, 103] . 7.6.1 Code clone detection. ...
arXiv:2011.14597v1
fatcat:pcyg6zbnm5bc3g4yhjomcnye3y
An Empirical Study on the Usage of Transformer Models for Code Completion
[article]
2021
arXiv
pre-print
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We present a large-scale study exploring the capabilities of state-of-the-art Transformer-based models in supporting code completion at different granularity levels, including single tokens, one or multiple ...
Thus, little is known about the performance of state-of-the-art code completion approaches in more challenging scenarios in which, for example, an entire code block must be generated. ...
To build the Android dataset we adopted a similar procedure. We cloned the set of 8,431 open-source Android apps from GitHub available in the AndroidTimeMachine dataset [28] . ...
arXiv:2108.01585v1
fatcat:le2gets3rzctxd5wlobbiooium
Android Mobile Malware Detection Using Machine Learning: A Systematic Review
2021
Electronics
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With the increasing use of mobile devices, malware attacks are rising, especially on Android phones, which account for 72.2% of the total market share. ...
Finally, the ML-based methods for detecting source code vulnerabilities are discussed, because it might be more difficult to add security after the app is deployed. ...
The empirical analysis conducted in [112] identified the static software metrics' correlation and the most informative metrics which can be used to find code vulnerability related to Android source codes ...
doi:10.3390/electronics10131606
fatcat:jpbsq7j6p5dtrpzkincfi2obpe
Predictive Models in Software Engineering: Challenges and Opportunities
[article]
2020
arXiv
pre-print
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There have been a large number of primary studies that apply predictive models and that present well-preformed studies and well-desigeworks in various research domains, including software requirements, ...
Predictive models are one of the most important techniques that are widely applied in many areas of software engineering. ...
[139] conducted an empirical study on six open-source Java systems to investigate the life expectancy of clones. ...
arXiv:2008.03656v1
fatcat:fe7ylphujfbobeo3g5yevniiei
Research on Third-Party Libraries in AndroidApps: A Taxonomy and Systematic LiteratureReview
[article]
2021
arXiv
pre-print
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Third-party libraries (TPLs) have been widely used in mobile apps, which play an essential part in the entire Android ecosystem. However, TPL is a double-edged sword. ...
To this end, we conduct the first systematic literature review on Android TPL-related research. ...
[82] conducted an empirical study regarding the ad library updates in Android apps. ...
arXiv:2108.03787v1
fatcat:jnj4kvlkuzg3hbgy4pl5wpvle4
Usage and Attribution of Stack Overflow Code Snippets in GitHub Projects
[article]
2018
arXiv
pre-print
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We present results of a large-scale empirical study analyzing the usage and attribution of non-trivial Java code snippets from SO answers in public GitHub (GH) projects. ...
We found that at most 1.8% of all analyzed repositories containing code from SO used the code in a way compatible with CC BY-SA 3.0. ...
et al, 2014) , the code clone detector we used in the second phase of our study. ...
arXiv:1802.02938v4
fatcat:55nhx2mjd5hm5j65okgnmofvhy
A Survey on Machine Learning Techniques for Source Code Analysis
[article]
2021
arXiv
pre-print
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Objective: We aim to summarize the current knowledge in the area of applied machine learning for source code analysis. ...
A large number of studies poses challenges to the community to understand the current landscape. ...
Studies in this category prepare a dataset containing source code samples classified as clones or non-clones. ...
arXiv:2110.09610v1
fatcat:jc6c3jnxcbekfbssyy7hn3zwxa
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