VeranstaltungsortN.0.43Veranstalter Institut für VolkswirtschaftslehreBeschreibungGrowing interest in the analysis of interrelationships between income distribution and economic growth has recently stimulated new theoretical as well as empirical research. Measures such as head-count ratio for poverty index or widely used Gini coefficient are aggregated indicators describing the general extent of inequality and without deeper insight into income distribution among the households. To derive an indicator accounting for income distribution among the income groups, we propose a new approach based on an output oriented DEA model with inputs equal unit and weights restrictions imposed so as to favor higher income share in lower quantiles. We demonstrate the merit of this approach on the quintile income breakdown data of the European countries. Prioritizing lower income groups´ welfare, countries – e.g. Slovenia and Slovakia – can be equally favored by the new proposed indicator while assessed differently by the Gini index. Intertemporal analysis reveals a slight deterioration of income distribution over the period of 2007 – 2016 in a Rawlsian sense.Vortragende(r)o.Univ.-Prof. Dr. Mikulas LuptacikWirtschaftsuniversität Bratislava, Wirtschaftsuniversität Wien, IWIKontaktChristina Kopetzky (vwl2@aau.at)

VeranstaltungsortN.0.43Veranstalter Institut für VolkswirtschaftslehreBeschreibungWelche Gesichtspunkte sollte ein junger, am Beginn seiner Karriere stehender Wissenschaftler berücksichtigen, um ungewollte, harte Landungen zu vermeiden? Mit welchen Fakten über Ungleichheiten in der Wissensproduktion sollte eine Berufungskommission vertraut sein, um Kandidaten und Kandidatinnen richtig einzuschätzen? Deutet ein Rückgang an Publikationen in der Lebensmitte auf ein rasches Karriereende hin oder lediglich auf einen temporären Einbruch?Mit diesen und ähnlichen Fragestellungen beschäftigt sich eine im Entstehen begriffene „Wissenschaft von den Wissenschaften“. Erkenntnisse daraus werden im Vortrag eher bruchstückhaft als in systematischer Weise vorgestellt. Es ist zu hoffen, dass Einsichten über die „science production“ zur Bildung künftiger Modelle, sei es deskriptiver oder normativer Art, und in weiterer Folge zu Lösungsansätzen für etwaige Probleme führen können.Vortragende(r)em.o.Univ.-Prof. Dr. Gustav FeichtingerTechnische Universität WienKontaktChristina Kopetzky (vwl2@aau.at)

VeranstaltungsortN.2.01Veranstalter Institut für MathematikBeschreibungTitel: Nonlinear Energy Network and Heuristic Methods forLarge-scale MINLPKurzfassung:In this talk I will introduce a nonlinear maximization problem for a simpleenergy network instance. The network consists of machines to produceheat and a storage tank and it is formulated as a mixed-integer nonlinearprogramming problem (MINLP). This problem is NP-hard, a large-scaleMINLP cannot be solved efficiently by nonlinear solvers. In this talk, I willexplain the formulation of the model, the difficulties of this problem andthe methods used to solve this problem in practice.Vortragende(r)Shudian ZhaoKontaktSenka Haznadar (senka.haznadar@aau.at)

VeranstaltungsortS.1.37Veranstalter Fakultät für Technische WissenschaftenBeschreibungIn the past decade, research on test-suite-based automatic program repair has grown significantly. Each year, new approaches and implementations are featured in major software engineering venues. However, most of those approaches are evaluated on a single benchmark of bugs, which are also rarely reproduced by other researchers. In this paper, we present a large-scale experiment using 11 Java test-suite-based repair tools and 2,141 bugs from 5 benchmarks. Our goal is to have a better understanding of the current state of automatic program repair tools on a large diversity of benchmarks. Our investigation is guided by the hypothesis that the repairability of repair tools might not be generalized across different benchmarks. We found that the 11 tools 1) are able to generate patches for 21% of the bugs from the 5 benchmarks, and 2) have better performance on Defects4J compared to other benchmarks, by generating patches for 47% of the bugs from Defects4J compared to 10-30% of bugs from the other benchmarks. Our experiment comprises 23,551 repair attempts, which we used to find causes of non-patch generation. These causes are reported in this presentation, which can help repair tool designers to improve their approaches and tools. This work was presented at ESEC/FSE19 and was given an ACM SIGSOFT Distinguished Paper Award.Vortragende(r)Assoc.-Prof. Rui AbreuKontaktChristian Timmerer (christian.timmerer@itec.aau.at)