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Using Deep Learning to find bugs

Full-time PhD studentship funded by Huawei

Description

Much of the time and cost in developing software is spent fixing bugs reported by users or testers. Due to staff turnover, outsourcing, and the complexity and size of software systems, developers may not be familiar with the code they have to fix, further increasing time and cost. 

Our state-of-the-art search engine (Dilshener et al 2018) helps developers find the source of errors more quickly: given a bug report, it suggests (in ranked order, like a web search engine) which files may need to be fixed. Our approach uses heuristics rather than past history. The aim of this PhD research is to use deep learning to improve the accuracy of finding bugs and to adapt the search engine to the codebase being analysed.

This full-time PhD research will be carried out in collaboration with Huawei, which is funding the Empirical Data-Driven Bug Localisation in Software Development (EDBL) project, of which this PhD is a part of.

 

Skills Required

  • Strong software development skills, preferably in Python
  • Good communication and documentation skills
  • Knowledge of machine learning techniques
  • Experience of creating datasets and experimental design is useful

 

Background reading

  • T. Dilshener, M. Wermelinger, Y. Yu (2018). Locating bugs without looking back. Automated Software Engineering, 25(3) pp. 383–434. http://oro.open.ac.uk/51576

 

Contacts

Dr Yijun Yu (yijun.yu@open.ac.uk) or Dr Michel Wermelinger (michel.wermelinger@open.ac.uk)

 

Key dates

Application cut-off date: 9 July 2021

Expected start date: 1 February 2022 or sooner if possible

The successful candidate is expected to live within 40 miles of Milton Keynes

 

How to apply

For application guidance, please visit here.

 

 

 

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