Formalization of informal use cases to series of structured functional requirements (FRs) is an important step in developing dependable software. However, such conversion process is commonly labor-intensive and slow. In this work we present a fully automated pipeline that translates use-case flowcharts (as SVG and images) into rule based FR documents via a five-step process: input validation, OCR/SVG text extraction, structure detection, local large language model (LLM) drafting using Ollama, and report production. The manual use-case-to-FR workflow is compared with our automated pipeline, revealing the points in which ambiguity and omissions are likely to occur. We prepare a relatively smaller data set composed of use cases and attempt to generate structured functional requirements. To achieve this, we tested our proposed pipeline on a set of two experimental settings: one with a single SVG-based user flow to establish basic behavior and another with six SVG use-case flows at once for providing an initial assessment of robustness and scalability. This two-step evaluation facilitates a systematic analysis on the individual components’ performance as well as overall effectiveness with growing input complexity. Preliminary evaluation demonstrates on two independent reports: an overall 80.5% accuracy for a one-flowchart batch; and an overall 87.0% accuracy for six-flowchart batch. On both batches structure detection reaches 100.0% performance, while text extraction is still the main bottleneck (between 50.0% and 66.67%). The pipeline produces traceable normalized FR statements and a PDF (with issues per file and suggestions) for an analyst to review and fine-tune.
原文链接
分享
引用
