- Database Reverse Engineering based on Association Rule Mining
- Automatic Structure Discovery for Large Source Code
- Utilizing Static Analysis and Code Generation to Accelerate Neural Networks
- Neural Turing Machines
- Automated detection and classification of cryptographic algorithms in binary programs through machine learning
- On End-to-End Program Generation from User Intention by Deep Neural Networks
- When Coding Style Survives Compilation: De-anonymizing Programmers from Executable Binaries
- Building Machines That Learn and Think Like People
- Boda-RTC: Productive Generation of Portable, Efficient Code for Convolutional Neural Networks on Mobile Computing Platforms
- Differentiable Functional Program Interpreters
- Differentiable Programs with Neural Libraries
- TERPRET: A Probabilistic Programming Language for Program Induction
- Auto-Documenation for Software Development
- RobustFill: Neural Program Learning under Noisy I/O
- Data Driven Exploratory Attacks on Black Box Classifiers in Adversarial Domains
- A Syntactic Neural Model for General-Purpose Code Generation
- Making Neural Programming Architectures Generalize via Recursion
- pix2code: Generating Code from a Graphical User Interface Screenshot
- Sorting and Transforming Program Repair Ingredients via Deep Learning Code Similarities
- Automatic feature learning for vulnerability prediction
- Automatically Generating Commit Messages from Diffs using Neural Machine Translation
- BOOK: Storing Algorithm-Invariant Episodes for Deep Reinforcement Learning
- Inferring Generative Model Structure with Static Analysis
- A Survey of Machine Learning for Big Code and Naturalness
- FairFuzz: Targeting Rare Branches to Rapidly Increase Greybox Fuzz Testing Coverage
- BinPro: A Tool for Binary Source Code Provenance
- DLPaper2Code: Auto-generation of Code from Deep Learning Research Papers
- DeepAPT: Nation-State APT Attribution Using End-to-End Deep Neural Networks
- VulDeePecker: A Deep Learning-Based System for Vulnerability Detection
- A Survey on Compiler Autotuning using Machine Learning
- Recent Advances in Neural Program Synthesis
- Comment Generation for Source Code: Survey
- Neural Program Search: Solving Programming Tasks from Description and Examples
- Code smells
- Predicting Software Defects Through SVM: An Empirical Approach
- Estimating defectiveness of source code: A predictive model using GitHub content
- code2vec: Learning Distributed Representations of Code
- Neural-Guided Deductive Search for Real-Time Program Synthesis from Examples
- EMBER: An Open Dataset for Training Static PE Malware Machine Learning Models
- Deep Probabilistic Programming Languages: A Qualitative Study
- Ariadne: Analysis for Machine Learning Programs
- Deep Learning in Software Engineering
- DeepMutation: Mutation Testing of Deep Learning Systems
- Neural Code Comprehension: A Learnable Representation of Code Semantics
- Automatically Assessing Vulnerabilities Discovered by Compositional Analysis
- A Survey of Reverse Engineering and Program Comprehension
manjunath5496/Source-Code-Analysis-Papers
"Nothing in physics seems so hopeful to as the idea that it is possible for a theory to have a high degree of symmetry was hidden from us in everyday life. The physicist's task is to find this deeper symmetry."— Steven Weinberg