27 citations · 33 across the 18 of their papers we have counts for
11 papers · 1 filter
TileCas: Cascading Kernel Development Across Programming Abstractions
Xinyu Xiao, Zihe Song, Dezhi Ran +2
Programming abstractions have traditionally been designed for humans, but code generation is increasingly performed by models and autonomous agents. We investigate abstractions for…
BackendForge: Benchmarking Agentic End-to-End Code Generation with Backend Services
Yuzhe Guo, Mengzhou Wu, Yuan Cao +4
Large language models (LLMs) are increasingly used in agentic coding settings, where they can inspect files, execute commands, run tests, observe failures, and iteratively revise c…
From User Interface to Agent Interface: Efficiency Optimization of UI Representations for LLM Agents
Dezhi Ran, Zhi Gong, Yuzhe Guo +10
While Large Language Model (LLM) agents show great potential for automated UI navigation such as automated UI testing and AI assistants, their efficiency has been largely overlooke…
AppForge: From Assistant to Independent Developer -- Are GPTs Ready for Software Development?
Dezhi Ran, Yuan Cao, Mengzhou Wu +10
Large language models (LLMs) have demonstrated remarkable capability in function-level code generation tasks. Unlike isolated functions, real-world applications demand reasoning ov…
Beyond Pass or Fail: Multi-Dimensional Benchmarking of Foundation Models for Goal-based Mobile UI Navigation
Dezhi Ran, Mengzhou Wu, Hao Yu +15
Recent advances of foundation models (FMs) have made navigating mobile applications (apps) based on high-level goal instructions within reach, with significant industrial applicati…
DeCon: Detecting Incorrect Assertions via Postconditions Generated by a Large Language Model
Hao Yu, Tianyu Chen, Jiaming Huang +8
Recently, given the docstring for the target problem and the target function signature, large language models (LLMs) have been used not only to generate source code, but also to ge…
An Infrastructure Software Perspective Toward Computation Offloading between Executable Specifications and Foundation Models
Dezhi Ran, Mengzhou Wu, Yuan Cao +3
Foundation Models (FMs) have become essential components in modern software systems, excelling in tasks such as pattern recognition and unstructured data processing. However, their…
Skill-Adaptive Imitation Learning for UI Test Reuse
Mengzhou Wu, Hao Wang, Jun Ren +7
To alleviate the substantial cost of manually crafting user interface (UI) test cases, UI test migration aims to automatically generate test cases for a target mobile application (…
SWE-bench-java: A GitHub Issue Resolving Benchmark for Java
Daoguang Zan, Zhirong Huang, Ailun Yu +17
GitHub issue resolving is a critical task in software engineering, recently gaining significant attention in both industry and academia. Within this task, SWE-bench has been releas…
Foundation Model Engineering: Engineering Foundation Models Just as Engineering Software
Dezhi Ran, Mengzhou Wu, Wei Yang +1
By treating data and models as the source code, Foundation Models (FMs) become a new type of software. Mirroring the concept of software crisis, the increasing complexity of FMs ma…
CoderEval: A Benchmark of Pragmatic Code Generation with Generative Pre-trained Models
Hao Yu, Bo Shen, Dezhi Ran +7
Code generation models based on the pre-training and fine-tuning paradigm have been increasingly attempted by both academia and industry, resulting in well-known industrial models…