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Answer set programming (ASP) and planning are two widely used paradigms forsolving logic programs with declarative programming. In both cases, the qualityof the input programs has a major influence on the quality and performance ofthe solving or planning process. Hence, programmers need to understand how tomake their programs efficient and still correct. In my PhD studies, I explorehow input programs can be improved and verified automatically as a means tosupport programmers. One of my research directions consists in discoveringinvariants in planning programs without human support, which I implemented in asystem called ginkgo. Studying dynamic systems in greater depth, I thendeveloped plasp 3 with members of my research group, which is a significantstep forward in effective planning in ASP. As a second research direction, I amconcerned with automating the verification of ASP programs against formalspecifications. For this joint work with Lifschitz's group at the University ofTexas, I developed a verification system called anthem. In my future PhDstudies, I will extend my research concerning the discovery and verification ofASP and planning problems.

Discovering and Proving Invariants in Answer Set Programming and Planning