This article presents a survey on automatic software repair. Automatic software repair
consists of automatically finding a solution to software bugs without human intervention. This …

Genetic improvement (GI) uses automated search to find improved versions of existing
software. We present a comprehensive survey of this nascent field of research with a focus …

Debugging software failures is still a painful, time consuming, and expensive process. For
instance, recent studies showed that debugging activities often account for about 50% of the …

As the field of data science continues to grow, there will be an ever-increasing demand for
tools that make machine learning accessible to non-experts. In this paper, we introduce the …

The effectiveness of search-based automated program repair is limited in the number of
correct patches that can be successfully generated. There are two causes of such limitation …

Evolution provides a creative fount of complex and subtle adaptations that often surprise the
scientists who discover them. However, the creativity of evolution is not limited to the natural …

We analyze reported patches for three existing generate-and-validate patch generation
systems (GenProg, RSRepair, and AE). The basic principle behind generate-and-validate …

Over the past decade, data science and machine learning has grown from a mysterious art
form to a staple tool across a variety of fields in academia, business, and government. In this …

There are more bugs in real-world programs than human programmers can realistically
address. This paper evaluates two research questions:“What fraction of bugs can be …

Automated program repair is the problem of automatically fixing bugs in programs in order to
significantly reduce the debugging costs and improve the software quality. To address this …