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Final published version
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
| Publication date | 14/11/2017 |
|---|---|
| Host publication | Proceedings - 2017 IEEE 28th International Symposium on Software Reliability Engineering Workshops, ISSREW 2017 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 44-47 |
| Number of pages | 4 |
| ISBN (electronic) | 9781538623879 |
| <mark>Original language</mark> | English |
| Event | 28th IEEE International Symposium on Software Reliability Engineering Workshops, ISSREW 2017 - Toulouse, France Duration: 23/10/2017 → 26/10/2017 |
| Conference | 28th IEEE International Symposium on Software Reliability Engineering Workshops, ISSREW 2017 |
|---|---|
| Country/Territory | France |
| City | Toulouse |
| Period | 23/10/17 → 26/10/17 |
| Conference | 28th IEEE International Symposium on Software Reliability Engineering Workshops, ISSREW 2017 |
|---|---|
| Country/Territory | France |
| City | Toulouse |
| Period | 23/10/17 → 26/10/17 |
Defect prediction has been the subject of a great deal of research over the last two decades. Despite this research it is increasingly clear that defect prediction has not transferred into industrial practice. One of the reasons defect prediction remains a largely academic activity is that there are no defect prediction tools that developers can use during their day-to-day development activities. In this paper we describe the defect prediction tool that we have developed for industrial use. Our ELFF tool seamlessly plugs into the IntelliJ IDE and enables developers to perform regular defect prediction on their Java code. We explain the state-of-art defect prediction that is encapsulated within the ELFF tool and describe our evaluation of ELFF in a large UK telecommunications company.