ScalaSTM provides very strong guarantees (strong atomicity and isolation), but only for accesses to Ref and the provided transactional collections. This is different from STMs that retrofit transactional behavior onto all variables of an existing language.

Write skew

Write skew occurs when a transaction’s reads are validated at a different point in time from where its writes are applied. MVCC (multi-version concurrency control) algorithms allows write skew, because it performs reads against a snapshot taken at the beginning of a transaction while using locks to atomically apply the writes at the end.

One of the nice features of true atomicity is that it allows local correctness reasoning for each transaction. A system that tolerates write skews allows a greater fraction of transactions to commit, which is a good thing, but it makes correctness a global property. Some pluggable ScalaSTM implementations may allow relaxed consistency to be selectively enabled, but write skew is not allowed by default.

Strong atomicity

At its most basic, a software transactional memory is a way of isolating a group of memory accesses and verifying that those accesses are equivalent to some serial execution. The STM barriers that perform the transactional reads and writes include code that blocks or rolls back any accesses that violate atomicity or isolation. If non-transactional code bypasses the barriers and accesses an STM-managed memory location directly, however, the barriers can no longer detect all violations.

There are three potential responses to the weak isolation between direct memory accesses and concurrent transactions:

Scala favors safety and compile-time checking of program correctness, so the authors are of the opinion that it is only natural to employ types to avoid the problems of weak isolation. A deep extension to Scala’s type system to directly encode transactionality would be possible, but we can get type checking for much less effort by using the reference-based approach. ScalaSTM provides strong atomicity by encapsulating all transactionally-managed memory locations inside references.


A subtle issue with STM is that, unless special care is taken, only committed transactions are guaranteed to be consistent. Speculative transactions may observe an inconsistent state and only subsequently detect that they should roll back. These ‘zombies’ can produce surprising behavior by taking impossible branches or performing transactional accesses to the wrong object. This problem is greatly magnified in a reference based STM, because the STM cannot provide a sandbox that isolates all actions taken by the zombie. The read of a single impossible value may produce an infinite loop, so a transparent STM must either prevent inconsistent reads or instrument back edges to periodically revalidate the transaction. Only the first option is available to an STM implemented as a library.

The TL2 7 and LSA 8 algorithms use a global time-stamp to efficiently validate a transaction after each read, guaranteeing consistency for all intermediate states. This correctness property is formalized as opacity 9.

The reference implementation included with ScalaSTM is based on SwissTM 10, which adds eager detection of write-write conflicts to TL2’s validation algorithm. Additional implementations should also guarantee opacity, unless it is explicitly disabled using TxnExecutor.withHint or TxnExecutor.withConfig.

Irrevocable actions

One of the side effects of ScalaSTM’s alternate syntax for transactional barriers is that it avoids creating the impression that the STM can magically parallelize all existing sequential code, or that atomic blocks are always a better replacement for locks. This avoids scalability problems stemming from incidental dependencies, and avoids the semantic problems of irrevocable actions.

The semantic problems with hiding rollback and retry come from actions that the STM cannot isolate or undo, such as I/O or calls to external libraries. ScalaSTM does not try to automatically handle irrevocable actions. Instead, it allows the user to register handlers to perform manual cleanup or two-phase commit. Handler registration is accomplished via methods of object Txn.

  1. F. T. Schneider, V. Menon, T. Shpeisman, and A.-R. Adl-Tabatabai. Dynamic Optimization for Efficient Strong Atomicity. In OOPSLA ‘08: Proceedings of the 23rd ACM SIGPLAN conference on Object-Oriented Programming Systems, Languages, and Applications, New York, NY, USA, October 2008. ACM. 

  2. N. G. Bronson, C. Kozyrakis, and K. Olukotun. Feedback-Directed Barrier Optimization in a Strongly Isolated STM. In POPL ‘09: Proceedings of the 36th Annual ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages, pages 213–225, New York, NY, USA, 2009. ACM. 

  3. V. Menon, S. Balensieger, T. Shpeisman, A.-R. Adl-Tabatabai, R. L. Hudson, B. Saha, and A. Welc. Practical Weak-Atomicity Semantics for Java STM. In SPAA ‘08: Proceedings of the 20th ACM Symposium on Parallel Algorithms and Architectures, 2008. 

  4. K. F. Moore and D. Grossman. High-Level Small-Step Operational Semantics for transactions. In POPL ‘08: Proceedings of the 35th Annual ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages, pages 51–62, New York, NY, USA, 2008. ACM. 

  5. T. Harris, S. Marlow, S. Peyton-Jones, and M. Herlihy. Composable Memory Transactions. In PPoPP ‘05: Proceedings of the tenth ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, pages 48–60, New York, NY, USA, 2005. ACM. 

  6. R. Hickey. The Clojure Programming Language. In Proceedings of the 2008 Symposium on Dynamic Languages. ACM New York, NY, USA, 2008. 

  7. D. Dice, O. Shalev, and N. Shavit. Transactional Locking II. In DISC ‘06: Proceedings of the 20th International Symposium on Distributed Computing, March 2006. 

  8. T. Riegel, P. Felber, and C. Fetzer. A Lazy Snapshot Algorithm with Eager Validation. In Disc ‘06: Proceedings of the 20th International Symposium on Distributed Computing, pages 284–298, 2006. 

  9. R. Guerraoui and M. Kapalka. On the Correctness of Transactional Memory. In PPoPP ‘08: Proceedings of the 13th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, pages 175–184, New York, NY, USA, 2008. ACM. 

  10. A. Dragojevic, R. Guerraoui, and M. Kapalka. Stretching Transactional Memory. In PLDI ‘09: Proceedings of the 2009 ACM SIGPLAN Conference on Programming Language Design and Implementation, pages 155–165, New York, NY, USA, 2009. ACM.