# Path-Based Function Embedding and its Application to Specification Mining

arXiv: https://arxiv.org/abs/1802.07779 · HTML: https://mlsanity.com/paper/1802.07779/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Feb 2018.

## Built on by (most cited first, 8 of 8)

- [Learning to Make Compiler Optimizations More Effective](https://mlsanity.com/paper/2102.13514/) (2021)
- [A Library for Representing Python Programs as Graphs for Machine Learning](https://mlsanity.com/paper/2208.07461/) (2022)
- [deGraphCS: Embedding Variable-based Flow Graph for Neural Code Search](https://mlsanity.com/paper/2103.13020/) (2021)
- [JEMMA: An Extensible Java Dataset for ML4Code Applications](https://mlsanity.com/paper/2212.09132/) (2022)
- [An Exploratory Literature Study on Sharing and Energy Use of Language Models for Source Code](https://mlsanity.com/paper/2307.02443/) (2023)
- [Text Classification for Task-based Source Code Related Questions](https://mlsanity.com/paper/2111.00580/) (2021)
- [Test Case Recommendations with Distributed Representation of Code Syntactic Features](https://mlsanity.com/paper/2310.03174/) (2023)
- [Type-IV Code Clone Detection via Layer-Wise Non-Contrastive Representation Learning](https://mlsanity.com/paper/2609.17338/) (2026)

## Abstract (arXiv)

Identifying the relationships among program elements is useful for program understanding, debugging, and analysis. One such relationship is synonymy. Function synonyms are functions that play a similar role in code, e.g. functions that perform initialization for different device drivers, or functions that implement different symmetric-key encryption schemes. Function synonyms are not necessarily semantically equivalent and can be syntactically dissimilar; consequently, approaches for identifying code clones or functional equivalence cannot be used to identify them. This paper presents func2vec, an algorithm that maps each function to a vector in a vector space such that function synonyms are grouped together. We compute the function embedding by training a neural network on sentences generated from random walks over an encoding of the program as a labeled pushdown system (l-PDS). We demonstrate that func2vec is effective at identifying function synonyms in the Linux kernel. Furthermore, we show how function synonyms enable mining error-handling specifications with high support in Linux file systems and drivers.