
Source code modification is one of the most frequent operations which developers perform in software life cycle. Such operation can be performed in order to add new functionality, fix bugs or bad code style, optimize performance, increase readability, etc. During the modification of existing source code developer needs to find parts of code, which meet to some conditions, and change it according to some rules. Usually developers perform such operations repeatedly by hand using primitive search/replace mechanisms and “copy and paste programming”, and that is why manual modification of large-scale software systems is a very error-prone and time-consuming process. Automating source code modifications is one of the possible ways of coping with this problem because it can considerably decrease both the amount of errors and the time needed in the modification process.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 1 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
