Refactoring large legacy codebases, even with industrial-strength tools, often leads to trust concerns with code owners, in particular when the codebase underwent significant changes. To provide more assurance to code owners, we integrate visual analytics into the refactoring process. This method involves transforming code into control flow graphs before and after refactoring, followed by trace equivalence analysis on these graphs. An innovative visualisation tool provides not only a comprehensive overview of the refactorings' impact across all files, but also offers detailed insights into the trace equivalence at individual file level. By presenting clear visual evidence of code equivalence before and after refactoring, our visualisation narrows the trust gap, offering refactoring experts and code owners a transparent and understandable view of the changes. We apply this visualisation on an industrial use case and discuss its effectiveness with refactoring experts.

We propose a tool and underlying technique that uses semi-parsing to extract control flow graphs from legacy source code (i.e., COBOL). Obtaining such control flow graphs is relevant in the industrial setting of legacy modernisation, to quickly demonstrate to code owners that modernisation engineers did not break their business logic. They need to be convinced that a migration did not affect the flow around critical parts of their code such as database accesses. Focusing on the control flow around embedded SQL queries and confirming that the code logic has been preserved improves customers' trust and satisfaction in the modernisation. Our proposed algorithm and approach uses fuzzy parsing as opposed to full parsing to parse mainly the control flow constructs, while delegating the full parsing of embedded languages like SQL to an external parser, and produces a control flow graph directly while skipping over most of the input in linear time. Such a fuzzy parser is easier to construct and adapt to particular languages and needs than a full parser with a visitor to elicit control flow. Comparisons are made of the fuzzy parser to an industrial-strength full parser.

Large code refactoring projects can consist of hundreds of refactoring rules that are applied iteratively to make code easier to maintain. Visualising the refactoring process can help engineers and stakeholders understand how chains of refactorings were applied and to gain more confidence in the produced result. An apparently suitable existing visualisation using log-based behavioural differencing suffers from scalability issues when applied to industrial-size cases. We propose an adapted visualisation tool that highlights those parts that really changed in-between iterations of a large refactoring process and collapses those parts that remain stable. We show that our alternative visualisation scales well on large logs of a process with many possible refactoring chains, of which significant parts are shared. Consequently, it allows engineers and stakeholders to quickly answer relevant questions about what happened during the refactoring process.