Skeletal program enumeration for rigorous compiler testing

Author:

Zhang Qirun1,Sun Chengnian1,Su Zhendong1

Affiliation:

1. University of California at Davis, USA

Abstract

A program can be viewed as a syntactic structure P (syntactic skeleton) parameterized by a collection of identifiers V (variable names). This paper introduces the skeletal program enumeration (SPE) problem: Given a syntactic skeleton P and a set of variables V , enumerate a set of programs P exhibiting all possible variable usage patterns within P. It proposes an effective realization of SPE for systematic, rigorous compiler testing by leveraging three important observations: (1) Programs with different variable usage patterns exhibit diverse control- and data-dependence, and help exploit different compiler optimizations; (2) most real compiler bugs were revealed by small tests (i.e., small-sized P) — this “small-scope” observation opens up SPE for practical compiler validation; and (3) SPE is exhaustive w.r.t. a given syntactic skeleton and variable set, offering a level of guarantee absent from all existing compiler testing techniques. The key challenge of SPE is how to eliminate the enormous amount of equivalent programs w.r.t. α-conversion. Our main technical contribution is a novel algorithm for computing the canonical (and smallest) set of all non-α-equivalent programs. To demonstrate its practical utility, we have applied the SPE technique to test C/C++ compilers using syntactic skeletons derived from their own regression test-suites. Our evaluation results are extremely encouraging. In less than six months, our approach has led to 217 confirmed GCC/Clang bug reports, 119 of which have already been fixed, and the majority are long latent despite extensive prior testing efforts. Our SPE algorithm also provides six orders of magnitude reduction. Moreover, in three weeks, our technique has found 29 CompCert crashing bugs and 42 bugs in two Scala optimizing compilers. These results demonstrate our SPE technique’s generality and further illustrate its effectiveness.

Funder

NSF

Google Faculty Research Award

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Graphics and Computer-Aided Design,Software

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