Abstract
Model transformations (MT), as with any other software artifact,
may contain quality flaws. Even if a transformation is functionally
correct, such flaws will impair maintenance activities such as enhancement
and porting. The concept of technical debt (TD) models the impact
of such flaws as a burden carried by the software which must either be
settled in a ‘lump sum’ to eradicate the flaw, or paid in the ongoing
additional costs of maintaining the software with the flaw. In this paper
we investigate the characteristics of technical debt in model transformations,
analysing a range of MT cases in different MT languages, and
using measures of quality flaws or ‘bad smells’ for MT, adapted from
code measures.
Based on these measures we identify significant differences in the level
and kinds of technical debt in different MT languages, and we propose
ways in which TD can be reduced.
may contain quality flaws. Even if a transformation is functionally
correct, such flaws will impair maintenance activities such as enhancement
and porting. The concept of technical debt (TD) models the impact
of such flaws as a burden carried by the software which must either be
settled in a ‘lump sum’ to eradicate the flaw, or paid in the ongoing
additional costs of maintaining the software with the flaw. In this paper
we investigate the characteristics of technical debt in model transformations,
analysing a range of MT cases in different MT languages, and
using measures of quality flaws or ‘bad smells’ for MT, adapted from
code measures.
Based on these measures we identify significant differences in the level
and kinds of technical debt in different MT languages, and we propose
ways in which TD can be reduced.
| Original language | English |
|---|---|
| Journal | Lecture Notes in Computer Science |
| Publication status | Published - 1 Jun 2018 |
Keywords
- Software Quality