Example-based Synthesis of Static Analysis Rules

TL;DR

This paper introduces RhoSynth, a novel algorithm for automatically generating static analysis rules from code examples using graph-based logic synthesis, significantly reducing manual effort and improving rule precision.

Contribution

The paper presents RhoSynth, a new ILP-based graph alignment method for synthesizing static analysis rules from developer-provided examples, outperforming existing approaches.

Findings

Successfully synthesized over 30 Java rules with >75% precision

Rules deployed in real-world code review system

Outperforms recent program synthesis baselines

Abstract

Static Analysis tools have rules for several code quality issues and these rules are created by experts manually. In this paper, we address the problem of automatic synthesis of code quality rules from examples. We formulate the rule synthesis problem as synthesizing first order logic formulas over graph representations of code. We present a new synthesis algorithm RhoSynth that is based on Integer Linear Programming-based graph alignment for identifying code elements of interest to the rule. We bootstrap RhoSynth by leveraging code changes made by developers as the source of positive and negative examples. We also address rule refinement in which the rules are incrementally improved with additional user-provided examples. We validate RhoSynth by synthesizing more than 30 Java code quality rules. These rules have been deployed as part of a code review system in a company and their precision exceeds 75% based on developer feedback collected during live code-reviews. Through comparisons with recent baselines, we show that current state-of-the-art program synthesis approaches are unable to synthesize most of these rules.