IceDust: Incremental and eventual computation of derived values in persistent object graphs

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Derived values are values calculated from base values. They can be expressed in object-oriented languages by means of getters calculating the derived value, and in relational or logic databases by means of (materialized) views. However, switching to a different calculation strategy (for example caching) in object-oriented programming requires invasive code changes, and the databases limit expressiveness by disallowing recursive aggregation. In this paper, we present IceDust, a data modeling language for expressing derived attribute values without committing to a calculation strategy. IceDust provides three strategies for calculating derived values in persistent object graphs: Calculate-on-Read, Calculate-on-Write, and Calculate-Eventually. We have developed a path-based abstract interpretation that provides static dependency analysis to generate code for these strategies. Benchmarks show that different strategies perform better in different scenarios. In addition we have conducted a case study that suggests that derived value calculations of systems used in practice can be expressed in IceDust.

Original languageEnglish
Title of host publication30th European Conference on Object-Oriented Programming, ECOOP 2016
EditorsShriram Krishnamurthi, Benjamin S. Lerner
PublisherSchloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing
Number of pages26
ISBN (Electronic)978-3-95977-014-9
Publication statusPublished - 1 Jul 2016
EventECOOP 2016: 30th European Conference on Object-Oriented Programming - Rome, Italy
Duration: 18 Jul 201622 Jul 2016

Publication series

NameLeibniz International Proceedings in Informatics
ISSN (Print)1868-8969


ConferenceECOOP 2016


  • Data modeling
  • Domain specific language
  • Incremental computing


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