Abstract
Transactional memory (TM) facilitates the development of concurrent applications by letting a programmer designate certain code blocks as atomic. The common approach to stating TM correctness is through a consistency condition that restricts the possible TM executions. Unfortunately, existing consistency conditions fall short of formalizing the intuitive semantics of atomic blocks through which programmers use a TM. To close this gap, we formalize programmer expectations as observational refinement between TM implementations. This states that properties of a program using a concrete TM implementation can be established by analyzing its behavior with an abstract TM, serving as a specification of the concrete one. We show that a variant of Transactional Memory Specification (TMS), a TM consistency condition, is equivalent to observational refinement for a programming language where local variables are rolled back upon a transaction abort. We thereby establish that TMS is the weakest acceptable condition for this case. We then propose a new consistency condition, called Strong Transactional Memory Specification (STMS), and show that it is equivalent to observational refinement for a language where local variables are not rolled back upon aborts. Finally, we show that under certain natural assumptions on TM implementations, STMS is equivalent to a variant of a well-known condition of opacity. Our results suggest a new approach to evaluating TM consistency conditions and enable TM implementors and language designers to make better-informed decisions.
Original language | English |
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Article number | Y |
Journal | Journal of the ACM |
Volume | 65 |
Issue number | 1 |
DOIs | |
State | Published - Jan 2018 |
Keywords
- Transactions
- correctness conditions
- opacity
- Transactional Memory Specification
- TMS
- Strong Transactional Memory Specification
- STMS
- atomicity
All Science Journal Classification (ASJC) codes
- Software
- Control and Systems Engineering
- Information Systems
- Hardware and Architecture
- Artificial Intelligence