High-fidelity metaprogramming with separator syntax trees

Many metaprogramming tasks, such as refactorings, automated bug fixing, or large-scale software renovation, require high-fidelity source code transformations-transformations which preserve comments and layout as much as possible. Abstract syntax trees (ASTs) typically abstract from such details, and hence would require pretty printing, destroying the original program layout. Concrete syntax trees (CSTs) preserve all layout information, but transformation systems or parsers that support CSTs are rare and can be cumbersome to use. In this paper we present separator syntax trees (SSTs), a lightweight syntax tree format, that sits between AST and CSTs, in terms of the amount of information they preserve. SSTs extend ASTs by recording textual layout information separating AST nodes. This information can be used to reconstruct the textual code after parsing, but can largely be ignored when implementing high-fidelity transformations. We have implemented SSTs in Rascal, and show how it enables the concise definition of high-fidelity source code transformations using a simple refactoring for C++

Large-scale semi-automated migration of legacy C/C++ test code

This is an industrial experience report on a large semi-automated migration of legacy test code in C and C++. The particular migration was enabled by automating most of the maintenance steps. Without automation this particular large-scale migration would not have been conducted, due to the risks involved in manual maintenance (risk of introducing errors, risk of unexpected rework, and loss of productivity). We describe and evaluate the method of automation we used on this real-world case. The benefits were that by automating analysis, we could make sure that we understand all the relevant details for the envisioned maintenance, without having to manually read and check our theories. Furthermore, by automating transformations we could reiterate and improve over complex and large scale source code updates, until they were “just right.” The drawbacks were that, first, we have had to learn new metaprogramming skills. Second, our automation scripts are not readily reusable for other contexts; they were necessarily developed for this ad-hoc maintenance task. Our analysis shows that automated software maintenance as compared to the (hypothetical) manual alternative method seems to be better both in terms of avoiding mistakes and avoiding rework because of such mistakes. It seems that necessary and beneficial source code maintenance need not to be avoided, if software engineers are enabled to create bespoke (and ad-hoc) analysis and transformation tools to support it

usethesource/rascal-eclipse: 0.23.0

Eclipse IMP based IDE for the Rascal meta-programming language. See rascal project for Wiki, Issues and such