Evolutionary repair of faulty software

author = "Andrea Arcuri",

title = "Evolutionary repair of faulty software",

journal = "Applied Soft Computing",

volume = "11",

number = "4",

pages = "3494--3514",

year = "2011",

ISSN = "1568-4946",

URL = "

http://crest.cs.ucl.ac.uk/fileadmin/crest/sebasepaper/Arcurid09d.pdf",

DOI = "

doi:10.1016/j.asoc.2011.01.023",

URL = "

http://www.sciencedirect.com/science/article/B6W86-5223XWX-1/2/5d81be4fc12644887723df167e134516",

keywords = "genetic algorithms, genetic programming, Repair, Fault localisation, Automated debugging, Search Based Software Engineering, Coevolution",

abstract = "Testing and fault localization are very expensive software engineering tasks that have been tried to be automated. Although many successful techniques have been designed, the actual change of the code for fixing the discovered faults is still a human-only task. Even in the ideal case in which automated tools could tell us exactly where the location of a fault is, it is not always trivial how to fix the code. In this paper we analyse the possibility of automating the complex task of fixing faults. We propose to model this task as a search problem, and hence to use for example evolutionary algorithms to solve it. We then discuss the potential of this approach and how its current limitations can be addressed in the future. This task is extremely challenging and mainly unexplored in the literature. Hence, this paper only covers an initial investigation and gives directions for future work. A research prototype called JAFF and a case study are presented to give first validation of this approach.",