The FermaT Transformation Engine is an industrial strength toolset for the migration of Assembler and Cobol based legacy systems to C. It uses an intermediate language and several dozen mathematical proven transformations to raise the abstraction level of a source code or to restructure and simplify it as needed. The actual program transformation process with the aid of this toolset is semi-automated which means that a maintainer has not only to apply one transformation after another but also to evaluate the transformation result. This can be a very difficult task especially if the given program is very large and if a lot of transformations have to be applied. Moreover, it cannot be assured that a transformation target will be achieved because it relies on the decisions taken by the respective maintainer which in turn are based on his personal knowledge. Even a small mistake can lead to a failure of the entire program transformation process which usually causes an extensive and time consuming backtrack. Furthermore, it is difficult to compare the results of different transformation sequences applied on the same program. To put it briefly, the manual approach is inflexible and often hard to use especially for maintainers with little knowledge about transformation theory. There already exist different approaches to solve these well known problems and to simplify the accessibility of the FermaT Transformation Engine. One recently presented approach is based on a particular prediction technique whereas another is based on various search tactics. Both intend to automatise the program transformation process. However, the approaches solve some problems but not without introducing others. On the one hand, the prediction based approach is very fast but often not able to provide a transformation sequence which achieves the defined program transformation targets. The results depend a lot on the algorithms which analyse the given program and on the knowledge which is available to make the right decisions during the program transformation process. On the other hand, the search based approach usually finds suitable results in terms of the given target but only in combination with small programs and short transformation sequences. It is simply not possible to perform an extensive search on a large-scale program in reasonable time. To solve the described problems and to extend the operating range of the FermaT Transformation Engine, this thesis proposes a constraint based program transformation system. The approach is semi-automated and provides the possibility to outline an entire program transformation process on the basis of constraints and transformation schemes. In this context, a constraint is a condition which has to be satisfied at some point during the application of a transformation sequence whereas a transformation scheme defines the search space which consists of a set of transformation sequences. After the constraints and the scheme have been defined, the system uses a unique knowledge-based prediction technique followed by a particular search tactic to reduce the number of transformation sequences within the search space and to find a transformation sequence which is applicable and which satisfies the given constraints. Moreover, it is possible to describe those transformation schemes with the aid of a formal language. The presented thesis will provide a definition and a classification of constraints for program transformations. It will discuss capabilities and effects of transformations and their value to define transformation sets. The modelling of program transformation processes with the aid of transformation schemes which in turn are based on finite automata will be presented and the inclusion of constraints into these schemes will be explained. A formal language to describe transformation schemes will be introduced and the automated construction of these schemes from the language will be shown. Furthermore, the thesis will discuss a unique prediction technique which uses the capabilities of transformations, an evaluation of the transformation sequences on the basis of transformation effects and a particular search tactic which is related to linear and tree search tactics. The practical value of the presented approach will be proven with the aid of three medium-scale case studies. The first one will show how to raise the abstraction level whereas the second one will show how to decrease the complexity of a particular program. The third one will show how to increase the execution speed of a selected program. Moreover, the work will be summarised and evaluated on the basis of the research questions. Its limitations will be disclosed and some suggestion for future work will be made.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:516079 |
| Date | January 2009 |
| Creators | Natelberg, Stefan |
| Publisher | De Montfort University |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://hdl.handle.net/2086/2923 |
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