LLM 기반 요구사항-코드 의미 정합성 분석을 통한 소프트웨어 완성도 평가 모델

초록

Software completeness evaluation is important for software quality assurance, maintenance verification, outsourced software inspection, and public software project assessment. Existing approaches have limitations in evaluating whether software implementations semantically satisfy user requirements. This paper proposes an LLM-based software appraisal model that evaluates software completeness based on semantic alignment between requirements and source code. The proposed model extracts functional information from natural language requirements, analyzes semantic information from source code, and evaluates requirement-implementation alignment using embedding-based similarity and LLM-based reasoning. In addition, the model detects missing and over-implemented functionalities and automatically generates explainable evaluation reports. Experimental results show that the proposed model outperforms conventional keyword-based traceability approaches and improves the explainability and automation of software completeness evaluation. The proposed approach can be applied to software auditing, maintenance evaluation, outsourced software verification, and public software quality assessment.

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