mlsanityData to 7 Oct 2026

The Future of AI-Driven Software Engineering

arXiv 2406.07737 ↗First posted 11 Jun 2024cs.SE cs.AI cs.LGcited by 23

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Abstract (arXiv)

A paradigm shift is underway in Software Engineering, with AI systems such as LLMs playing an increasingly important role in boosting software development productivity. This trend is anticipated to persist. In the next years, we expect a growing symbiotic partnership between human software developers and AI. The Software Engineering research community cannot afford to overlook this trend; we must address the key research challenges posed by the integration of AI into the software development process. In this paper, we present our vision of the future of software development in an AI-driven world and explore the key challenges that our research community should address to realize this vision.

Key facts. Cited by 23 papers in the map (data through 7 Oct 2026). Builds on 38 of its 118 references that are in the map. First posted on arXiv 11 Jun 2024.

Builds on

38 of 118 references.

References · 38

  1. 2021Evaluating Large Language Models Trained on Codecited by 8,053
  2. 2023The Rise and Potential of Large Language Model Based Agents: A Surveycited by 1,422
  3. 2023Is Your Code Generated by ChatGPT Really Correct? Rigorous Evaluation of Large Language Models for Code Generationcited by 1,332
  4. 2021Asleep at the Keyboard? Assessing the Security of GitHub Copilot's Code Contributionscited by 417
  5. 2023Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyondcited by 409
  6. 2023An Empirical Evaluation of Using Large Language Models for Automated Unit Test Generationcited by 193
  7. 2023Large Language Models for Software Engineering: Survey and Open Problemscited by 178
  8. 2023From Words to Watts: Benchmarking the Energy Costs of Large Language Model Inferencecited by 168
  9. 2023Software Testing with Large Language Models: Survey, Landscape, and Visioncited by 163
  10. 2023InferFix: End-to-End Program Repair with LLMscited by 113
  11. 2024On Protecting the Data Privacy of Large Language Models (LLMs): A Surveycited by 91
  12. 2023No More Manual Tests? Evaluating and Improving ChatGPT for Unit Test Generationcited by 82
26 more
  1. 2022Less Training, More Repairing Please: Revisiting Automated Program Repair via Zero-shot Learningcited by 76
  2. 2023A Large-Scale Survey on the Usability of AI Programming Assistants: Successes and Challengescited by 75
  3. 2024Automated Unit Test Improvement using Large Language Models at Metacited by 73
  4. 2020Metamorphic Testing: A New Approach for Generating Next Test Casescited by 71
  5. 2023Evaluating the Code Quality of AI-Assisted Code Generation Tools: An Empirical Study on GitHub Copilot, Amazon CodeWhisperer, and ChatGPTcited by 71
  6. 2023Large Language Models are Few-Shot Summarizers: Multi-Intent Comment Generation via In-Context Learningcited by 71
  7. 2024RepoAgent: An LLM-Powered Open-Source Framework for Repository-level Code Documentation Generationcited by 69
  8. 2023Using Large Language Models to Generate JUnit Tests: An Empirical Studycited by 53
  9. 2023Effective Test Generation Using Pre-trained Large Language Models and Mutation Testingcited by 51
  10. 2022Pynguin: Automated Unit Test Generation for Pythoncited by 49
  11. 2024Iterative Refinement of Project-Level Code Context for Precise Code Generation with Compiler Feedbackcited by 45
  12. 2023Advancing Requirements Engineering through Generative AI: Assessing the Role of LLMscited by 42
  13. 2024Fine-Tuning and Prompt Engineering for Large Language Models-based Code Review Automationcited by 23
  14. 2024TOGLL: Correct and Strong Test Oracle Generation with LLMscited by 23
  15. 2023Small Language Models Fine-tuned to Coordinate Larger Language Models improve Complex Reasoningcited by 16
  16. 2023Unit Test Generation using Generative AI : A Comparative Performance Analysis of Autogeneration Toolscited by 13
  17. 2021EvoSpex: An Evolutionary Algorithm for Learning Postconditionscited by 6
  18. 2021APIzation: Generating Reusable APIs from StackOverflow Code Snippetscited by 6
  19. 2023Can ChatGPT advance software testing intelligence? An experience report on metamorphic testingcited by 6
  20. 2022Supervised Semantic Similarity-based Conflict Detection Algorithm: S3CDAcited by 5
  21. 2023MR-Scout: Automated Synthesis of Metamorphic Relations from Existing Test Casescited by 4
  22. 2023On the Potential and Limitations of Few-Shot In-Context Learning to Generate Metamorphic Specifications for Tax Preparation Softwarecited by 3
  23. 2023GenMorph: Automatically Generating Metamorphic Relations via Genetic Programmingcited by 3
  24. 2021GAssert: A Fully Automated Tool to Improve Assertion Oraclescited by 2
  25. 2022Together or Apart? Investigating a mediator bot to aggregate bot's comments on pull requestscited by 2
  26. 2024LLMs and Stack Overflow Discussions: Reliability, Impact, and Challengescited by 2

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 1; 2025: 7; 2026: 15.

23 papers.

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  1. 2025Beyond Final Code: A Process-Oriented Error Analysis of Software Development Agents in Real-World GitHub Scenarioscited by 14
  2. 2024LLMs: A Game-Changer for Software Engineers?cited by 11
  3. 2025Generative AI and Empirical Software Engineering: A Paradigm Shiftcited by 9
  4. 2026LLMLOOP: Improving LLM-Generated Code and Tests through Automated Iterative Feedback Loopscited by 8
  5. 2025The Future of Generative AI in Software Engineering: A Vision from Industry and Academia in the European GENIUS Projectcited by 4
  6. 2025Semantic Commit: Helping Users Update Intent Specifications for AI Memory at Scalecited by 3
  7. 2026Are We All Using Agents the Same Way? An Empirical Study of Core and Peripheral Developers Use of Coding Agentscited by 3
  8. 2026Understanding LLM-Driven Test Oracle Generationcited by 2
  9. 2026Agentic Pipelines in Embedded Software Engineering: Emerging Practices and Challengescited by 2
  10. 2026LLMORPH: Automated Metamorphic Testing of Large Language Modelscited by 2
  11. 2025A Research Roadmap for Augmenting Software Engineering Processes and Software Products with Generative AIcited by 1
  12. 2026From Junior to Senior: Allocating Agency and Navigating Professional Growth in Agentic AI-Mediated Software Engineeringcited by 1
11 more
  1. 2026Lore: Repurposing Git Commit Messages as a Structured Knowledge Protocol for AI Coding Agentscited by 1
  2. 2026MR-Coupler: Automated Metamorphic Test Generation via Functional Coupling Analysiscited by 1
  3. 2026SelfHeal: Empirical Fix Pattern Analysis and Bug Repair in LLM Agentscited by 1
  4. 2026Model-Driven Discipline for Multi-Agent LLMs: Requirement-to-Verification Generation of Traceable System Modelscited by 1
  5. 2025Beyond Autocomplete: Designing CopilotLens Towards Transparent and Explainable AI Coding Agentscited by 0
  6. 2025Toward Explaining Large Language Models in Software Engineering Taskscited by 0
  7. 2026From Untestable to Testable: Metamorphic Testing in the Age of LLMscited by 0
  8. 2026Vibe-driven model-based engineeringcited by 0
  9. 2026Can Open-Source LLM Agents Replace Static Application Security Testing Tools? An Empirical Assessmentcited by 0
  10. 2026AI-driven Software Development: A Pragmatic Path to Agentic Development Processescited by 0
  11. 2026Commenting with Copilot: A Taxonomy and Multi-Year Analysis of Student Code-Generation Specificationscited by 0