What question did this study set out to answer?

The aim is to develop a comprehensive non-functional requirement quality framework for APIs to improve software quality and user satisfaction.

April 12, 2026Open Access

A novel NFR-based conceptual quality framework for modern API industry

Key Points

The aim is to develop a comprehensive non-functional requirement quality framework for APIs to improve software quality and user satisfaction.
Explanatory sequential mixed-methods design employed.
Survey tool utilized with 8 Likert-scale items and 2 open-ended questions.
Descriptive statistics and reliability testing for quantitative analysis.
Thematic analysis applied for qualitative data assessment.
The proposed framework is effective in managing Core, Critical, and Contextual NFRs.
Expert surveys supported the feasibility and applicability of the framework.
The framework enhances API quality management and provides KPI-based quality standards.

Abstract

The modern software ecosystems employ application programming interface (API) to allow interoperability and integration across various platforms. Non-functional requirements (NFRs) as quality attributes are as vital as functional requirements (FRs) in assuring software quality and user satisfaction. API quality management is a challenge to software industry owing to poor NFRs handling during API development, resulting in cost increase, project failure and dissatisfied customers. The existing standards failed in producing a comprehensive quality framework for APIs. OpenAPI Specification (OAS) focuses on functional aspects, whereas ISO/IEC 25010:2023 emphases on traditional software quality. Hence, this study proposes a novel non-functional requirement quality framework for APIs (NFRQF-API). In compliance with ISO/IEC 25,010, the framework includes key NFRs and their influencing factors to facilitate the development of high-quality APIs. Explanatory sequential mixed-methods design was applied in this study, involving a survey tool. Data were collected using a questionnaire comprising eight Likert-scale items and two open-ended items. Descriptive statistics and reliability testing were applied for quantitative data analysis, while thematic analysis was applied to evaluate the qualitative data, which supports in achieving a comprehensive expert-based justification for the conceptual feasibility and applicability of framework. Based on the experts’ survey, analyses results demonstrated the potential effectiveness of the proposed framework in managing the Core, Critical, and Contextual NFRs in the entire API development lifecycle. This study bridges the gap between existing quality models and API quality assurance challenges. The structured expert-refined framework facilitates the enhancement of API quality management and offers KPI-based conceptual quality standards for the industry to design high-quality APIs by effectively handling critical NFR issues.

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