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Automatic Bug Fix Recommendation: improving Software Repair and Reducing Time-to-Fix Delays in Software Development Projects

Financement: Fonds National de la Recherche > CORE
Date de début: 1 février 2016
Date de fin: 30 janvier 2019

Description

There is today a momentum of automatic program repair, a research field where various approaches are devised to auto- matically fix programs once a fault is detected. Such approaches attempt to patch a program in a way that makes it pass all the tests. So far, there are no reports of adoption of these approaches in the industry. Indeed, currently, automatic program repair is a young and immature research field, and it has a number of caveats including the fact that: (1) only a limited set of fault types are considered, (2) the proposed fixes can be perceived as alien code and may be out of tune with the rest of the code and (3) there is no guarantee that this fix should be maintained or that it definitely fixes the bug.

The industry standard remains to thoroughly review bug reports and manually write corresponding fixes. Developers thus require new approaches and tools to help them readily understand bug report and infer the appropriate fix so as to (1) reduce the time-to-fix delay and (2) produce homogeneous code that is easy to maintain.

The RECOMMEND project aims at designing and building a bug fix recommendation system for software development projects. The system will be independent from any programming language. We will leverage information retrieval tech- niques and machine learning techniques to identify, from the history of a project or of similar projects, examples of fixes which can be proposed to address a newly submitted bug report. 

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