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S. Oliveira

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Review Open access 2026

A Systematic Mapping-Based Support Instrument for Implementing the Ensuring Quality Capability Area in CMMI 3.0

: This paper investigates how the Ensuring Quality capability area of Capability Maturity Model Integration (CMMI) 3.0 has been operationalized in academic research. A systematic mapping study grounded in the principles of Systematic Literature Review was conducted to identify and classify research contributions re-lated to Requirements Development and Management (RDM), Process Quality Assurance (PQA), Verification and Validation (VV), and Peer Review (PR). A total of 34 primary studies were selected and analyzed according to addressed practice areas, targeted maturity levels, organizational contexts, and types of empirical evidence. The results reveal a predominance of implementation-oriented approaches, particularly focused on intermediate maturity levels, with strong representation of RDM and PQA practices. From the synthesis of the extracted evidence, 120 structured findings were identified and organized into six integrative dimensions, including implementation steps, tools, methodologies, artifacts, validation models, and organizational roles. Based on this synthesis, a support instrument is proposed to consolidate dispersed research evidence and assist organizations in implementing Ensuring Quality practices within CMMI 3.0 environments..

Larissa de Paula Garcia, S. Oliveira · 0 citations
Open access Jul 2026

The Use of Generative AI Tools by Requirements Engineers: An Interview with Industry Professionals

This paper investigates how Generative Artificial Intelligence (GenAI) grounded in Large Language Models (LLMs) are being employed to support activities within Requirements Engineering (RE). Based on interviews conducted with software engineering professionals, the findings indicate that GenAI tools are particularly valuable during requirements elicitation and specification, contributing to improved productivity and reduced operational effort, especially when addressing Functional Requirements (FRs). Despite these benefits, participants also reported important limitations, including sensitivity to prompt formulation, generation of overly generic outputs, and limited capability to adequately support Non-Functional Requirements (NFRs).

J. V. Ferreira, C. Portela, S. Oliveira · 0 citations

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