Bibliographic Details
| Title: |
MIP-DD: Delta Debugging for Mixed-Integer Programming Solvers. |
| Authors: |
Hoen, Alexander1 (AUTHOR) hoen@zib.de, Kamp, Dominik2 (AUTHOR) dominik.kamp@uni-bayreuth.de, Gleixner, Ambros1 (AUTHOR) gleixner@htw-berlin.de |
| Source: |
INFORMS Journal on Computing. Mar/Apr2026, Vol. 38 Issue 2, p414-423. 10p. |
| Subject Terms: |
*Open source software, Debugging, Software failures, Computer performance, Mixed integer linear programming |
| Abstract: |
The recent performance improvements in mixed-integer programming (MIP) have been accompanied by a significantly increased complexity of the codes of MIP solvers, which poses challenges in fixing implementation errors. In this paper, we introduce MIP-DD, a solver-independent tool, which to the best of our knowledge is the first open-source delta debugger for MIP. Delta debugging is a hypothesis-trial-result approach to isolate the cause of a solver failure. MIP-DD simplifies MIP instances while maintaining the undesired behavior. Preliminary versions already supported and motivated fixes for many bugs in the SCIP releases 8.0.1 to 8.1.1. In these versions, MIP-DD successfully contributed to 24 out of all 51 documented MIP-related bugfixes even for some long-known issues. In selected case studies we highlight that instances triggering fundamental bugs in SCIP can typically be reduced to a few variables and constraints in less than an hour. This makes it significantly easier to manually trace and check the solution process on the resulting simplified instances. A promising future application of MIP-DD is the analysis of performance bottlenecks, which could very well benefit from simple adversarial instances. History: Accepted by Ted Ralphs, Area Editor for Software Tools. Funding: This work was partially supported by the German Research Foundation [Grant RA 1033/3-1] and the German Federal Ministry of Education and Research [Grant 05M20ZBM]. Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplemental Information (https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2024.0844) as well as from the IJOC GitHub software repository (https://github.com/INFORMSJoC/2024.0844). The complete IJOC Software and Data Repository is available at https://informsjoc.github.io/. [ABSTRACT FROM AUTHOR] |
|
Copyright of INFORMS Journal on Computing is the property of INFORMS: Institute for Operations Research & the Management Sciences and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| Database: |
Business Source Index |