We study one dimension in program evolution, namely the evolution of the datatype declarations in a program. To this end, a suite of basic transformation operators is designed. We cover structure-preserving refactorings, but also structure-extending and -reducing adaptations. Both the object programs that are subject to datatype transformations, and the meta programs that encode datatype transformations are functional programs.
Formal program transformation @cite_0 separates two concerns: the development of an initial, maybe inefficient program the correctness of which can easily be shown, and the stepwise derivation of a better implementation in a semantics-preserving manner. Partsch's textbook @cite_8 describes the formal approach to this kind of software development. Pettorossi and Proietti study typical transformation rules (for functional and logic) programs in @cite_17 . Formal program transformation, in part, also addresses datatype transformation @cite_3 , say data refinement. Here, one gives different axiomatisations or implementations of an abstract datatype which are then related by well-founded transformation steps. This typically involves some amount of mathematical program calculation. By contrast, we deliberately focus on the more syntactical transformations that a programmer uses anyway to adapt evolving programs.
@cite_0 @cite_17 @cite_3 @cite_8
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Program transformation is used in a wide range of applications including compiler construction, optimization, program synthesis, refactoring, software renovation, and reverse engineering. Complex program transformations are achieved through a number of consecutive modications of a program. Transformation rules dene basic modications. A transformation strategy is an algorithm for choosing a path in the rewrite relation induced by a set of rules. This paper surveys the support for the denition of strategies in program transformation systems. After a discussion of kinds of program transformation and choices in program representation, the basic elements of a strategy system are discussed and the choices in the design of a strategy language are considered. Several styles of strategy systems as provided in existing languages are then analyzed. A system of rules for transforming programs is described, with the programs in the form of recursion equations. An initially very simple, lucid, and hopefully correct program is transformed into a more efficient one by altering the recursion structure. Illustrative examples of program transformations are given, and a tentative implementation is described. Alternative structures for programs are shown, and a possible initial phase for an automatic or semiautomatic program-manipulation system is indicated. Software engineers are faced with a dilemma. They want to write general and wellstructured programs that are flexible and easy to maintain. On the other hand, generality has a price: efficiency. A specialized program solving a particular problem is often significantly faster than a general program. However, the development of specialized software is time-consuming, and is likely to exceed the production of today’s programmers. New techniques are required to solve this so-called software crisis. Partial evaluation is a program specialization technique that reconciles the benefits of generality with efficiency. This thesis presents an automatic partial evaluator for the Ansi C programming language. The content of this thesis is analysis and transformation of C programs. We develop several analyses that support the transformation of a program into its generating extension. A generating extension is a program that produces specialized programs when executed on parts of the input. The thesis contains the following main results. • We develop a generating-extension transformation, and describe specialization of the various parts of C, including pointers and structures. • We develop constraint-based inter-procedural pointer and binding-time analysis. Both analyses are specified via non-standard type inference systems, and implemented by constraint solving. • We develop a side-effect and an in-use analysis. These analyses are developed in the classical monotone data-flow analysis framework. Some intriguing similarities with constraint-based analysis are observed. • We investigate separate and incremental program analysis and transformation. Realistic programs are structured into modules, which break down inter-procedural analyses that need global information about functions. • We prove that partial evaluation at most can accomplish linear speedup, and develop an automatic speedup analysis. • We study the stronger transformation technique driving, and initiate the development of generating super-extensions. The developments in this thesis are supported by an implementation. Throughout the chapters we present empirical results. Semantics-preserving program transformations, such as refactorings and optimisations, can have a significant impact on the effectiveness of symbolic execution testing and analysis. Furthermore, semantics-preserving transformations that increase the performance of native execution can in fact decrease the scalability of symbolic execution. Similarly, semantics-altering transformations, such as type changes and object size modifications, can often lead to substantial improvements in the testing effectiveness achieved by symbolic execution in the original program. As a result, we argue that one should treat program transformations as first-class ingredients of scalable symbolic execution, alongside widely-accepted aspects such as search heuristics and constraint solving optimisations. First, we propose to understand the impact of existing program transformations on symbolic execution, to increase scalability and improve experimental design and reproducibility. Second, we argue for the design of testability transformations specifically targeted toward more scalable symbolic execution.