Intelligent Software Process - API Recommendation - LLM-assisted Developer Tools

Meng Shuai

Member of the PRiSE Research Group, Anhui Polytechnic University

My research direction is Intelligent Software Process - API Recommendation. I study how novice programmers express incomplete software-development intents and how intelligent systems can recover those intents to provide reliable API recommendations.

View Research Public CV

Research Focus

Intelligent Software Process - API Recommendation

I focus on API recommendation in intelligent software processes, especially the gap between vague natural-language programming needs and reliable API-level development support.

  • Intelligent Software Process - API Recommendation
  • API recommendation for novice programmers
  • LLM-assisted software engineering
  • intent modeling and semantic retrieval
  • developer tools and intelligent programming support
  • IEEE Transactions on Reliability paper accepted; second author and corresponding author.
  • IEEE Transactions on Services Computing paper under revise and resubmit; first author.
  • Automated Software Engineering journal submission under review; second author and corresponding author.
  • Hands-on engineering experience in Spring Cloud, Vue, warehouse MES systems, and AI application prototyping.

Publications and Manuscripts

Research Output

The current research line centers on API recommendation, consensus learning, heterogeneous information, and explainable LLM-enhanced reasoning.

01

API Recommendation for Novice Programmers: From Clear Expressions to Effective Results

IEEE Transactions on Reliability - Accepted

Second author and corresponding author

This work proposes IOCAPI, an intent-oriented and context-aware API recommendation method. It uses I/O examples to model user intent and connects LLM generation with task-semantic recovery, turning implicit user needs into structured constraints for explainable API recommendation.

  • API recommendation
  • intent modeling
  • I/O examples
  • LLM reasoning
02

API Recommendation based on Consensus Learning for Novice Programmers

IEEE Transactions on Services Computing - Revise and Resubmit

First author

This work proposes CoLAR, a consensus-learning framework that integrates external semantic retrieval with the internal knowledge of large language models. It builds multiple reasoning paths, votes over candidate APIs, and improves robustness for short or incomplete novice queries.

  • consensus learning
  • semantic retrieval
  • LLM knowledge
  • robust ranking
03

API Recommendation for Novice Programmers with Consensus Learning using Heterogeneous Information

Automated Software Engineering - Under Review

Second author and corresponding author

This work proposes CoHAPI, a Java API recommendation framework that learns complementary recommendation branches from Stack Overflow Q&A data and GitHub code comments. It uses rank-fusion consensus and semantic verification to improve stability under incomplete natural-language queries.

  • heterogeneous information
  • Stack Overflow
  • GitHub comments
  • contrastive reranking

Engineering Practice

Projects with Research and System Value

The project section emphasizes implementation depth, system responsibility, and how engineering practice supports long-term software-engineering research.

AI Alumni Time Machine preview

Research-driven product prototype - 2026 - Present

AI Alumni Time Machine

An AI-powered alumni service project for university history museums, alumni centers, anniversaries, and graduation scenarios. The system explores youthful portrait generation, campus-scene fusion, historical group-photo retrieval, and personalized commemorative content generation.

Role: Served as project lead, responsible for product planning, system architecture, core feature development, and team coordination from idea validation to prototype delivery.

Outcome: Built an experience-oriented prototype with public-facing project materials and a demonstrable system flow.

  • AI image generation
  • face retrieval
  • interactive web system
  • product prototyping
Warehouse MES Management System preview

Industry internship project - May 2025 - Nov 2025

Warehouse MES Management System

A warehouse management system for Anhui Meirui'er Filter Co., Ltd., covering inventory management, inbound and outbound workflows, batch tracking, stock alerts, and operational dashboards.

Role: Participated as a core developer, designing and implementing key business modules on both backend microservices and frontend visualization pages.

Outcome: Supported high-frequency daily material-flow operations and improved the digital management capability of warehouse workflows.

  • Spring Cloud
  • Vue 2
  • microservices
  • inventory management
  • data visualization

Education

Academic Training

2024 - Present

M.S. in Software Engineering

Anhui Polytechnic University

Research direction: Intelligent Software Process - API Recommendation.

2020 - 2024

B.E. in Data Science and Big Data Technology

Anhui Polytechnic University

Served as president of the Computer Association and participated in programming contests, volunteer service, and student technology activities.

Leadership

Service and Community

Undergraduate period

President, Computer Association

Organized programming lectures, freshman outreach, contest explanations, computer-maintenance volunteer services, and community technology activities.

Student service activities

Computer Maintenance Volunteer Service

Participated in and organized public-interest technology services that connected computing skills with campus and community needs.

Selected Honors

Awards and Certificates

Representative awards are shown with selected public certificate previews.