A tool for generating reference pairwise comparisons for benchmarking interactive methods

The framework's release version 1.05, dated August 30, 2025.

This update introduces several moderate changes (see below) and includes a new tutorial: "Tutorial 12: A tool for generating reference pairwise comparisons for benchmarking interactive methods."

• Framework: From now on, the library is additionally available as a Jar, which can be downloaded from the project's home page (only the most recent versions will be kept on the server).
• Framework: From now on, the library version number includes the date associated with the push to the repository (e.g., 1.04.30.06.2025; i.e., the last three elements represent the day, month, and year).
• Tutorials: A new tutorial: "Tutorial 12: A tool for generating reference pairwise comparisons for benchmarking interactive methods," was added.
• Libraries: Polyrun library added as a part of this project.
• IMPORTANT: Experimentation: names (getFileSuffix) of several Excel-based results analyzers (e.g., io.cross.excel.FinalStatisticsXLSX) changed (see the source codes).
• Experimentation: io.cross.excel: A few new analyzers added: GenerationRankerXLS (or XLSX) and GenerationStatisticsXLS (or XLSX). They perform similarly to their "Final..." counterparts but concern presenting results attained by the examined methods at specified generations.
• Experimentation: Results analyzers in io.cross: Minor update in processing; the implementations were exhaustively creating new cell styles (CellStyle), even when the styles for different cells were supposed to be the same. It ultimately led to errors when parsing large input data sets. This bug is now fixed.
• DecisionSupport: system.AbstractReport: changes _processingTime from long to double to introduce more precision.
• DecisionSupport: relation.PO: This class represents a relation of potential optimality, and it introduces some basic functionalities.
• DecisionSupport: model.constructor.abstractConstructor.getReport() changed into instantiateReport().
• DecisionSupport: model.constructor.value.rs.ers: Minor tweaks. E.g. ERS now measures after how many iterations a desired number of compatible models has been found.
• Utils: statistics: a few new statistics added (e.g., MinInRange).