  Answer set programming (ASP) and planning are two widely used paradigms for
solving logic programs with declarative programming. In both cases, the quality
of the input programs has a major influence on the quality and performance of
the solving or planning process. Hence, programmers need to understand how to
make their programs efficient and still correct. In my PhD studies, I explore
how input programs can be improved and verified automatically as a means to
support programmers. One of my research directions consists in discovering
invariants in planning programs without human support, which I implemented in a
system called ginkgo. Studying dynamic systems in greater depth, I then
developed plasp 3 with members of my research group, which is a significant
step forward in effective planning in ASP. As a second research direction, I am
concerned with automating the verification of ASP programs against formal
specifications. For this joint work with Lifschitz's group at the University of
Texas, I developed a verification system called anthem. In my future PhD
studies, I will extend my research concerning the discovery and verification of
ASP and planning problems.
