Distributed Parallelizability Analysis of Legacy Code

摘要

With the emergence of cloud computing and big data, migrating legacy systems to a cloud platform has become a trend. To make full use of the parallel advantage of cloud computing, it is necessary to refactor the legacy code according to the programming model of cloud computing. Before that, the parallelizability analysis is the first thing to do. In this paper, an approach is proposed for the distributed parallelizability analysis of legacy code, which is based on the analysis of dependency between loop iterations. According to the categories of the traditional dependency, the dependency between loop iterations is divided into three types, and the judgment rules of the dependency between loop iterations are proposed. Then a Distributed Parallelizability Analysis Tool (DPAT) based on Abstract Syntax Tree (AST) was developed to identify and annotate the parallelizable loops. Experimental results show that the approach can effectively identify the parallelizable code fragments, which will be the target objects of refactoring. In contrast to the existing approaches, our method can identify parallelizability between loop iterations and not limit the type of the loop.