Title
Symbolic abstract data type inference.
Abstract
Formal specification is a vital ingredient to scalable verification of software systems. In the case of efficient implementations of concurrent objects like atomic registers, queues, and locks, symbolic formal representations of their abstract data types (ADTs) enable efficient modular reasoning, decoupling clients from implementations. Writing adequate formal specifications, however, is a complex task requiring rare expertise. In practice, programmers write reference implementations as informal specifications. In this work we demonstrate that effective symbolic ADT representations can be automatically generated from the executions of reference implementations. Our approach exploits two key features of naturally-occurring ADTs: violations can be decomposed into a small set of representative patterns, and these patterns manifest in executions with few operations. By identifying certain algebraic properties of naturally-occurring ADTs, and exhaustively sampling executions up to a small number of operations, we generate concise symbolic ADT representations which are complete in practice, enabling the application of efficient symbolic verification algorithms without the burden of manual specification. Furthermore, the concise ADT violation patterns we generate are human-readable, and can serve as useful, formal documentation.
Year
DOI
Venue
2016
10.1145/2914770.2837645
POPL
Keywords
Field
DocType
Reliability,Verification,Concurrency,Refinement,Linearizability
Linearizability,Abstract data type,Programming language,Computer science,Inference,Concurrency,Formal specification,Software system,Theoretical computer science,Implementation,Scalability
Conference
Volume
Issue
ISSN
51
1
0362-1340
Citations 
PageRank 
References 
1
0.37
11
Authors
2
Name
Order
Citations
PageRank
Michael Emmi136521.76
Constantin Enea2162.32