Predictive models in software engineering: Challenges and opportunities

Y Yang, X **a, D Lo, T Bi, J Grundy… - ACM Transactions on …, 2022 - dl.acm.org
Predictive models are one of the most important techniques that are widely applied in many
areas of software engineering. There have been a large number of primary studies that …

Deep learning methods for malware and intrusion detection: A systematic literature review

R Ali, A Ali, F Iqbal, M Hussain… - Security and …, 2022 - Wiley Online Library
Android and Windows are the predominant operating systems used in mobile environment
and personal computers and it is expected that their use will rise during the next decade …

“Leagile” software development: An experience report analysis of the application of lean approaches in agile software development

X Wang, K Conboy, O Cawley - Journal of Systems and Software, 2012 - Elsevier
In recent years there has been a noticeable shift in attention from those who use agile
software development toward lean software development, often labelled as a shift “from …

[HTML][HTML] Explainable malware detection system using transformers-based transfer learning and multi-model visual representation

F Ullah, A Alsirhani, MM Alshahrani, A Alomari… - Sensors, 2022 - mdpi.com
Android has become the leading mobile ecosystem because of its accessibility and
adaptability. It has also become the primary target of widespread malicious apps. This …

Effective, Platform-Independent GUI Testing via Image Embedding and Reinforcement Learning

S Yu, C Fang, X Li, Y Ling, Z Chen, Z Su - ACM Transactions on …, 2024 - dl.acm.org
Software applications (apps) have been playing an increasingly important role in various
aspects of society. In particular, mobile apps and web apps are the most prevalent among all …

Malbert: Using transformers for cybersecurity and malicious software detection

A Rahali, MA Akhloufi - arxiv preprint arxiv:2103.03806, 2021 - arxiv.org
In recent years we have witnessed an increase in cyber threats and malicious software
attacks on different platforms with important consequences to persons and businesses. It …

A systematic overview of android malware detection

L Mei**, F Zhiyang, W Junfeng, C Luyu… - Applied Artificial …, 2022 - Taylor & Francis
Due to the completely open-source nature of Android, the exploitable vulnerability of
malware attacks is increasing. To stay ahead of other similar review work attempting to deal …

Malbert: Malware detection using bidirectional encoder representations from transformers

A Rahali, MA Akhloufi - 2021 IEEE International Conference on …, 2021 - ieeexplore.ieee.org
In recent years we have witnessed an increase in cyber threats and malicious software
attacks on different platforms with important consequences to persons and businesses. It …

Androct: ten years of app call traces in android

W Li, X Fu, H Cai - … IEEE/ACM 18th International Conference on …, 2021 - ieeexplore.ieee.org
Data-driven approaches have proven to be promising in mobile software analysis, yet these
approaches rely on sizable and quality datasets. For Android app analysis in particular …

Mixed signals: Analyzing software attribution challenges in the android ecosystem

K Hageman, Á Feal, J Gamba, A Girish… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
The ability to identify the author responsible for a given software object is critical for many
research studies and for enhancing software transparency and accountability. However, as …