Yu, Yijun; Bandara, Arosha; Tun, Thein Than and Nuseibeh, Bashar
(2011).
|
Due to copyright restrictions, this file is not available for public download Click here to request a copy from the OU Author. |
| URL: | http://doi.acm.org/10.1145/2070821.2070828 |
|---|---|
| DOI (Digital Object Identifier) Link: | http://dx.doi.org/doi:10.1145/2070821.2070828 |
| Google Scholar: | Look up in Google Scholar |
Abstract
Software developers are often concerned with particular changes that are relevant to their current tasks: not all changes to evolving software are equally important. Specified at the language-level, we have developed an automated technique to detect only those changes that are deemed meaningful, or relevant, to a particular development task [1]. In practice, however, it is realised that programmers are not always familiar with the production rules of a programming language. Rather, they may prefer to specify the meaningful changes using concrete program examples. In this position paper, we are proposing an inductive learning procedure that involves the programmers in constructing such language-level
specifications through examples. Using the efficiently generated meaningful changes detector, programmers are presented with quicker feedback for adjusting the learnt specifications. An illustrative example is used to show how such an inductive learning procedure might be applied.
| Item Type: | Conference Item |
|---|---|
| Copyright Holders: | 2011 ACM Press |
| Funders: | Microsoft SEIF, EU FP7 Security Engineering of Lifelong Evolvable Systems (SecureChange) |
| Academic Unit/Department: | Mathematics, Computing and Technology > Computing |
| Interdisciplinary Research Centre: | Centre for Research in Computing (CRC) |
| Item ID: | 30523 |
| Depositing User: | Arosha Bandara |
| Date Deposited: | 11 Jan 2012 13:52 |
| Last Modified: | 10 Dec 2012 22:29 |
| URI: | http://oro.open.ac.uk/id/eprint/30523 |
Actions (login may be required)
| View Item | |
| Report issue / request change |