Melinda Toth
Researcher at ELTE and RefactorErl project leader
Eötvös Loránd University of Budapest
Melinda Tóth is a third year PhD student at the Eötvös Loránd University (Budapest, Hungary). She has been working with Erlang since 2007 with the RefactorErl project. Melinda received her master's degree in Computer Science in 2009 from Eötvös Loránd University. Both her bachelor and master theses were based on Erlang and function related refactorings. In 2008 she spent five months at University of Kent where she worked with Wrangler. Melinda teaches Distributed Programming and Functional Languages (mostly Erlang) at the University. Her PhD research field is about data flow graphs, message passing analysis for functional languages, and impact analysis of refactorings. She is the leader of the RefactorErl project.
Melinda Toth is Giving the Following Talks
Change impact analysis
Program slicing is a well-known technique that utilizes dependency
graphs and static program analysis. Our goal is to perform change impact
analysis of Erlang programs based on the resulted program slices, that
is we want to measure the impact of any change made on the source code:
especially we want to select a subset of test cases which must be rerun
after the modification. The change can be performed manually by the
programmer or using a refactoring tool, such as RefactorErl. However
refactorings should preserve the original behaviour of the system,
developers want to be convinced about that, thus they retest the
software after some transformations. Software testing is said to be the
most expensive part of the lifecycle of software systems, so our
research focuses on selecting test cases affected by refactorings that
should be retested after the transformation.
Audience: Erlang developers and researchers
Objectives: Show the audience how you can use the change impact analysis technique to detect the subset of test cases affected by a change on the source code.
Audience: Erlang developers and researchers
Objectives: Show the audience how you can use the change impact analysis technique to detect the subset of test cases affected by a change on the source code.
