CompareT

CompareT is a software framework that enables transparent, reproducible side-by-side comparisons of items across multiple criteria. It is designed for use in product benchmarking, algorithm evaluation, and academic research, where decision-makers need to articulate and quantify trade-offs between alternatives. At its core, CompareT provides a data model for items and criteria, a rule engine for scoring and weighting, and visualization and reporting tools to communicate results. Users can define criteria (numeric, categorical, or derived), assign weights, normalize disparate scales, apply scoring rules, and aggregate scores through selectable methods such as weighted sums or more advanced multi-criteria techniques. The platform maintains an audit trail of data, criteria definitions, and scoring decisions to support reproducibility.

CompareT is implemented as a modular, extensible framework with a web-based interface and a RESTful API. It supports importing data from common formats (CSV, JSON) and exporting results for further analysis. Its plugin architecture allows integration with external data sources, visualization libraries, and decision-support workflows.

History and development: CompareT emerged from a community of data scientists and software engineers who began collaborative development in 2017. The first public release appeared in 2018, with feature expansions over subsequent years including advanced normalization, sensitivity analysis, and enterprise authentication. It is distributed under an open-source license, inviting community contributions.

Reception and limitations: The tool is noted for improving transparency and reproducibility in comparative analyses. Limitations include the subjective nature of criteria selection and weighting, potential bias in the scoring model, and scalability concerns for very large datasets.

See also: decision analysis, multiple criteria decision analysis, benchmarking, scoring models.