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6. Evaluation: The OMOP as a Unifying Substrate
1 ImmutableDomain = Domain (
2
3 raiseImmutabilityError = (
4 ImmutabilityError signal : ’ Modification of object denied .’ )
5
6 write : val toField : idx of: obj = unenforced (
7 self raiseImmutabilityError . )
8
9 primat : idx put : aVal on: anObj = unenforced (
10 self raiseImmutabilityError . )
11
12 priminstVarAt : idx put : aVal on: anObj = unenforced (
13 self raiseImmutabilityError . )
14
15 " ... and all other mutating operations "
16 )
Listing 6.3: Definition of a Domain for Immutable Objects
6.2.2. Software Transactional Memory
Introduction Software Transactional Memory (STM) (cf. Sec. 2.4.3) promises
a solution to the engineering problems of threads and locks. This programming
model enables a programmer to reason about all code as if it were executed
in some sequential order. The runtime tries however to execute threads
in parallel while giving the strong correctness guarantees implied by ensuring
sequential semantics. While common consensus [Cascaval et al., 2008] seems
to be that the performance overhead of STM systems is too high for many
practical applications, the idea continues to be appealing. 4 Thus, it is used as
one of the case studies.
This evaluation uses LRSTM (Lukas Renggli’s STM), which is based on
the implementation described by Renggli and Nierstrasz [2007] (cf. Sec. 7.1.3).
The ad hoc version of LRSTM is a port of the original implementation to the
current version of Squeak and Pharo. It uses the original approach, i. e., it
uses abstract syntax tree (AST) transformation to add the tracking of state
access and to adapt the use of primitives to enable full state access tracking.
The implementation details are discussed below.
4 The performance of an STM depends also on the programming language it is applied to.
Languages such as Haskell and Clojure restrict mutation and thereby experience lower
overhead from an STM than imperative languages with unrestricted mutation, where the
STM needs to track all state access.
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