News

Recent performance improvements of mixed-integer programming (MILP) solvers went along with a significantly increased complexity of their source codes. This poses challenges in investigating solver behavior, especially if something goes wrong due to implementation errors (aka bugs). In this talk, an open-source delta-debugger for MILP solvers is presented. Delta-debugging is a general trial-and-error approach to isolate the cause of a software failure by simplifying the input data for an implemented algorithm. In practice, applying this tool within the development of the open-source MILP solver SCIP contributed to an increase of approximately 71 % more bugfixes than in the year before. As highlighted in case studies, instances which trigger bugs in reasonable time could usually be reduced to a few variables and constraints in less than an hour. The resulting input instance then makes it significantly easier to discover the root cause of the solver behavior of interest. This way, even performance analysis could already benefit of this automized approach to generate simple performance-adversarial examples.