
doi: 10.1109/ms.2004.23
Reverse engineering is the process of comprehending software and producing a model of it at a high abstraction level, suitable for documentation, maintenance, or reengineering. But from a manager's viewpoint, there are two painful problems: 1) It's difficult or impossible to predict how much time reverse engineering will require. 2) There are no standards to evaluate the quality of the reverse engineering that the maintenance staff performs. Model-driven reverse engineering can overcome these difficulties. A model is a high-level representation of some aspect of a software system. MDRE uses the features of modeling technology but applies them differently to address the maintenance manager's problems. Our approach to MDRE uses formal specification and automatic code generation to reverse the reverse-engineering process. Models written in a formal specification language called SLANG describe both the application domain and the program being reverse engineered, and interpretations annotate the connections between the two. The ability to generate a similar version of a program gives managers a fixed target for reverse engineering. This, in turn, enables better effort prediction and quality evaluation, reducing development risk.
| 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). | 34 | |
| 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. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
