SEKE 2012 Proceedings - Knowledge Systems Institute

Spacemaker: Practical Formal Synthesis of Tradeoff
Spaces for Object-Relational Mapping
Hamid Bagheri
University of Virginia,
151 Engineer’s Way,
Charlottesville, VA 22903 USA
hb2j@virginia.edu
Kevin Sullivan
University of Virginia,
151 Engineer’s Way,
Charlottesville, VA 22903 USA
sullivan@virginia.edu
Sang H. Son
University of Virginia,
151 Engineer’s Way,
Charlottesville, VA 22903 USA
son@virginia.edu
Abstract—Developing mixed object-relational (OR) mappings
that achieve desirable quality attribute tradeoffs for objectoriented
applications is difficult, tedious, costly, and error-prone.
We contribute a practical, automated technique for exhaustive,
formal synthesis of large spaces of such mappings, and the
clustering of individual mappings in these spaces into multidimensional
quality equivalence classes. This technique can help
engineers to design effective persistence layers for object-oriented
applications. Our approach is to use a formal language to
describe both a space of mappings and multiple quality attribute
valuation functions on points in such a space. We use a constraint
solver to exhaustively enumerate points in this space and their
valuations. We then cluster the results into quality attribute
equivalence classes. This work promises to reduce the cost and
time required to develop mixed OR mappings, ensure their formal
correctness, and help engineers to understand and make tradeoffs
quantitatively. We conducted application-oriented experiments to
test feasibility and scalability of our approach. In one experiment
we synthesized an OR mapping tradeoff space for a real e-
commerce application, synthesizing and classifying hundreds of
thousands of mappings in just a few minutes.
Index Terms—Design; Database; Object-relational mapping;
Design space exploration; Alloy Language.
I. INTRODUCTION
Object-oriented applications often need to use relational
databases for persistent storage. Transformations between
instance models in these two paradigms encounter the socalled
impedance mismatch problem [9]. Object-relational
mapping (ORM) systems are now widely used to bridge the
gap between object-oriented application models and relational
database management systems (DBMS), based on applicationspecific
definitions on how object models are to be mapped to
database structures.
The problem we address is that today one has to choose between
automatic generation of mappings using pure mapping
strategies [3], [9], or the manual design of mixed mappings,
in which different mapping strategies are applied to individual
classes rather than to entire inheritance hierarchies. Producing
pure mappings automatically is easy, but it often leads to
sub-optimal results. Developing mixed mappings by hand can
achieve much higher quality, but it is hard and error-prone.
Among other things, it requires a thorough understanding
of both object and relational paradigms, of large spaces of
possible mappings, and of the tradeoffs involved in making
choices in these spaces.
To address this problem, we present an approach that
provides both the quality benefits of mixed mappings and
the productivity benefits of automated synthesis. We present a
practical formal automated technique, implemented in a prototype
tool that we call Spacemaker, for exhaustive synthesis
of mixed OR mappings and their classification into quality
attribute equivalence classes. We take as inputs a formal object
model and optional class-specific mapping strategies for those
classes that the user wants mapped in a specific manner.
We then use an automated constraint solver to exhaustively
generate the space of mappings subject to the given constraints,
along with multiple quality attribute measures for
each mapping. Next we cluster mappings into quality attribute
equivalence classes and present candidates from each class to
the engineer along with the measures of its quality attributes.
The engineer can then select a mapping to satisfy tradeoff
preferences. Our prototype tool uses Alloy as a specification
language [10], and the Alloy analyzer as a constraint solver.
In more detail, we claim four main contributions: (1) We
present what is to our knowledge the first formalization of
fine-grained and mixed ORM strategies by means of mapping
functions; (2) we contribute a fully automated approach for
formally precise synthesis of mapping tradeoff spaces, based
on this formalization; (3) we present an experimental demonstration
of technical feasibility and scalability to practically
meaningful applications; and (4) we develop the Spacemaker
tool [1], which we make available to the research and education
community. Data from our experiments support the
claim that our technique can reduce the time to develop highquality
OR mappings, ensure their correctness, and enable
engineers to make tradeoffs based on automatically computed
quality attributes for a full range of possible mappings rather
than on intuition or hard-to-acquire expertise in OR mapping
strategies.
The rest of this paper is organized as follows. Section II
presents our approach. Section III reports and discusses data
from the experimental testing of our approach. Section IV
surveys the related work. Section V concludes the paper with
an outline of our future work.
II. APPROACH
We present our approach in three parts. We first formalize
application of object-relational mapping strategies. We then
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