Design and Evaluation of TechLedger for Software Service Discovery and Comparison
Abstract
TechLedger is a web application for discovering, researching, saving, and comparing software services. It addresses a practical problem in technology selection: information about capabilities, releases, and pricing is spread across vendor sites, and users must keep their own shortlist while reviewing it. The application combines a React and TypeScript interface with a bundled catalog, Gemini-assisted research, and account workspaces stored in Neon PostgreSQL. This paper describes the implementation and examines the public repository at commit 5425d313. Static checks identify 81 services across 12 categories, of which 70 use template defaults for versions, pricing, and capabilities. Seven diagnostic queries illustrate the limits of substring search, and source inspection identifies a mismatch between verification labels and the evidence stored in a profile. These findings support a design that separates missing values from known facts and records evidence for individual fields. The paper also explains how saved services and comparison support a personal software stack. No user study or live research accuracy test is reported.
