Statistical models to accelerate software development by means of iterative compilation

Minimization of data-processing time and reduction of software-development time are important practical problems to be tackled by modern computer science. This paper presents the authors’ proposal of a family of statistical models for the estimation of program execution time, which is an approach focused on both of the above problems at the same time. The family consists of a general model and specific models and has been elaborated based on empirical data collected for pattern-program loops representing some arbitrarily selected features related to the program structure and the specificity of a program-execution environment. The paper presents steps to elaborate the aforementioned family as well as the results of the carried-out experimental research. The paper demonstrates how the elaborated models can be applied in iterative compilation for optimization purposes, allowing us to reduce the time of software development and produce code with minimal execution time.