ControVol: A framework for controlled schema evolution in NoSQL application development

Scherzinger, Stefanie; Cerqueus, Thomas; Almeida, Eduardo Cunha de

doi:10.1109/icde.2015.7113402

Cited by 20 publications

(12 citation statements)

References 5 publications

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“…5. An earlier version of ControVol has been demoed at ICDE'15 [5]. As a new feature since that first prototype, our poster presentation at WWW will show how ControVol detects a new class of problems caused by re-introducing class member attributes that have been removed from the source code in earlier releases, but that may still be resident in legacy data.…”

Section: Contributions and Outlinementioning

confidence: 96%

ControVol

Cerqueus

Almeida

Scherzinger

2015

Proceedings of the 24th International Conference on World Wide Web

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In building software-as-a-service applications, a flexible development environment is key to shipping early and often. Therefore, schema-flexible data stores are becoming more and more popular. They can store data with heterogeneous structure, allowing for new releases to be pushed frequently, without having to migrate legacy data first. However, the current application code must continue to work with any legacy data that has already been persisted in production. To let legacy data structurally "catch up" with the latest application code, developers commonly employ object mapper libraries with life-cycle annotations. Yet when used without caution, they can cause runtime errors and even data loss. We present ControVol, an IDE plugin that detects evolutionary changes to the application code that are incompatible with legacy data. ControVol warns developers already at development time, and even suggests automatic fixes for lazily migrating legacy data when it is loaded into the application. Thus, ControVol ensures that the structure of legacy data can catch up with the structure expected by the latest software release.

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Section: Contributions and Outlinementioning

confidence: 96%

ControVol

Cerqueus

Almeida

Scherzinger

2015

Proceedings of the 24th International Conference on World Wide Web

Self Cite

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“…Currently, there exists a number of approaches dealing with single-model systems or systems with closely related models, namely aggregate-oriented NoSQL databases [23,27]. There also exists a nontrivial set of approaches focusing primarily on the evolution management of XML documents, as well as comprehensive analyses of changes of real-world database schemas over time.…”

Section: Evolution Management In Multi-model Environmentmentioning

confidence: 99%

Unified Management of Multi-model Data

Holubová

Svoboda

2019

Conceptual Modeling

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The variety of data is one of the most challenging issues for research and practice in data management. The so-called multi-model data are naturally organized in different and mutually interlinked data formats and logical models, including structured, semi-structured, and unstructured. In this vision paper, we discuss the so far neglected, but for correct and efficient management of multi-model data critical issues and challenges: conceptual modeling of multi-model data, inference of multimodel schemas, unified and conceptual querying, evolution management, and, last but not least, autonomous multi-model data management.

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“…We briefly highlight the core features of ControVol, and refer to [16] and [17] for details on the workflow as experienced by developers. Our ControVol prototype currently supports Java development against Google Cloud Datastore [1], using the Objectify object mapper library.…”

Section: The Controvol Frameworkmentioning

confidence: 99%

“…• We have implemented our type checking rules within the ControVol Eclipse plugin. This plugin has been demoed in the past [16], [17], yet the theory on ControVol, in particular the type checking rules, are presented in this paper for the first time. In contrast, the demo papers focus (a) Before renaming.…”

Section: Introductionmentioning

confidence: 99%

Safely Managing Data Variety in Big Data Software Development

Cerqueus¹,

Almeida²,

Scherzinger³

2015

2015 IEEE/ACM 1st International Workshop on Big Data Software Engineering

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We consider the task of building Big Data software systems, offered as software-as-a-service. These applications are commonly backed by NoSQL data stores that address the proverbial Vs of Big Data processing: NoSQL data stores can handle large volumes of data and many systems do not enforce a global schema, to account for structural variety in data. Thus, software engineers can design the data model on the go, a flexibility that is particularly crucial in agile software development. However, NoSQL data stores commonly do not yet account for the veracity of changes when it comes to changes in the structure of persisted data. Yet this is an inevitable consequence of agile software development. In most NoSQL-based application stacks, schema evolution is completely handled within the application code, usually involving object mapper libraries. Yet simple code refactorings, such as renaming a class attribute at the source code level, can cause data loss or runtime errors once the application has been deployed to production. We address this pain point by contributing type checking rules that we have implemented within an IDE plugin. Our plugin ControVol statically type checks the object mapper class declarations against the code release history. ControVol is thus capable of detecting common yet risky cases of mismatched data and schema, and can even suggest automatic fixes. 2015 IEEE/ACM 1st International Workshop on Big Data Software Engineering 978-1-4673-7025-7/15 $31.00

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ControVol: A framework for controlled schema evolution in NoSQL application development

Cited by 20 publications

References 5 publications

ControVol

ControVol

Unified Management of Multi-model Data

Safely Managing Data Variety in Big Data Software Development

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