Research Intern: Machine Learning Driven Software Bug Detection
OracleAu-au,australia-brisbaneUpdate time: February 26,2020
Job Description
The objective of this internship is to detect program bugs through semantic modelling of source code. As bug detection is usually considered as a classification problem, it is crucial to select suitable features that can distinguish buggy programs from bug-free ones. However, identifying such discriminating features through manual analysis or heuristics still remain challenging.
This internship will explore deep learning techniques to model source code such that program semantics are precisely captured. Graphs are the basic data-structure for any analysis of programs, hence, graph-based source code representation is ideal for bug detection. Programs are represented as abstract syntax tree, control-flow or data-flow graph and neural graph embedding technique is applied to learn a vector representation of programs. Finally, machine learning classifier (e.g, SVM) is used to detect whether a program is buggy or bug-free.
Duties You will\:
• Ability to explore and summarise scientific literature in this field
• Select appropriate datasets and conduct data cleaning
• Extend existing Machine Learning framework developed in-house
• Conduct experiments and compare with published models/results
• Meet with your supervisor daily for guidance and to discuss ways to solve the problem;
• Attend team meetings and give updates on your work;
• Present your findings and outcomes to the group.
• Ability to explore and summarise scientific literature in this field
• Select appropriate datasets and conduct data cleaning
• Extend existing Machine Learning framework developed in-house
• Conduct experiments and compare with published models/results
• Meet with your supervisor daily for guidance and to discuss ways to solve the problem;
• Attend team meetings and give updates on your work;
• Present your findings and outcomes to the group.
Prerequisites\:
• Currently enrolled in a PhD or research-based Masters degree in Computer Science or Software
Engineering.
• Have a good understanding of program analysis concepts, especially program representation techniques (e.g., Abstract Syntax Tree (AST), Control-Flow Graph (CFG), etc.),
• Have a good background in machine learning,
• Be proficient in Python
• Have a good understanding of Java and/or C/C ,
• Demonstrated ability to work independently and collaboratively
• Understanding of Natural Language Processing (NLP) concepts and techniques and hands-on experience with popular deep learning frameworks (e.g., Tensorflow, PyTorch, etc...) will be beneficial
!|!This job code is utilized for the majority of our temporary hires. The individual is performing hourly job duties as defined under the Fair Labor Standards Act.• Currently enrolled in a PhD or research-based Masters degree in Computer Science or Software
Engineering.
• Have a good understanding of program analysis concepts, especially program representation techniques (e.g., Abstract Syntax Tree (AST), Control-Flow Graph (CFG), etc.),
• Have a good background in machine learning,
• Be proficient in Python
• Have a good understanding of Java and/or C/C ,
• Demonstrated ability to work independently and collaboratively
• Understanding of Natural Language Processing (NLP) concepts and techniques and hands-on experience with popular deep learning frameworks (e.g., Tensorflow, PyTorch, etc...) will be beneficial
!|!
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