Synchronization of Queries and Views Upon Schema Evolutions

Caruccio, Loredana; Polese, Giuseppe; Tortora, Genoveffa

doi:10.1145/2903726

Cited by 23 publications

(3 citation statements)

References 103 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Schema evolution. There is a body of literature on automating the schema refactoring process, including the rewrite of SQL queries and updates [8,14,15,19,43,50]. Among these works, the most related one is the Prism project and its successor Prism++ [14,15].…”

Section: Related Workmentioning

confidence: 99%

Synthesizing database programs for schema refactoring

Wang

Dong

Shah

et al. 2019

Proceedings of the 40th ACM SIGPLAN Conference on Programming Language Design and Implementation

View full text Add to dashboard Cite

Many programs that interact with a database need to undergo schema refactoring several times during their life cycle. Since this process typically requires making significant changes to the program's implementation, schema refactoring is often non-trivial and error-prone. Motivated by this problem, we propose a new technique for automatically synthesizing a new version of a database program given its original version and the source and target schemas. Our method does not require manual user guidance and ensures that the synthesized program is equivalent to the original one. Furthermore, our method is quite efficient and can synthesize new versions of database programs (containing up to 263 functions) that are extracted from real-world web applications with an average synthesis time of 69.4 seconds.CCS Concepts • Software and its engineering → Programming by example; Automatic programming; • Information systems → Database utilities and tools.

show abstract

Section: Related Workmentioning

confidence: 99%

Synthesizing database programs for schema refactoring

Wang

Dong

Shah

et al. 2019

Proceedings of the 40th ACM SIGPLAN Conference on Programming Language Design and Implementation

View full text Add to dashboard Cite

show abstract

“…In the database community, schema evolution refers to the problem of evolving database schemas to adapt to requirement changes. Schema evolution also typically requires data migration and synchronization of legacy transactions, and many papers from the database community address the problem of facilitating schema evolution [Caruccio et al 2016;Curino et al 2013;Fagin et al 2011;Rahm and Bernstein 2006;Visser 2008]. For example, the Prism and Prism++ projects [Curino et al 2013] investigate techniques for automatically evolving transactions using a given set of SQL-based schema modification operators.…”

Section: Related Workmentioning

confidence: 99%

Verifying equivalence of database-driven applications

Wang

Dillig

Lahiri

et al. 2017

Proc. ACM Program. Lang.

View full text Add to dashboard Cite

This paper addresses the problem of verifying equivalence between a pair of programs that operate over databases with different schemas. This problem is particularly important in the context of web applications, which typically undergo database refactoring either for performance or maintainability reasons. While web applications should have the same externally observable behavior before and after schema migration, there are no existing tools for proving equivalence of such programs. This paper takes a first step towards solving this problem by formalizing the equivalence and refinement checking problems for database-driven applications. We also propose a proof methodology based on the notion of bisimulation invariants over relational algebra with updates and describe a technique for synthesizing such bisimulation invariants. We have implemented the proposed technique in a tool called Mediator for verifying equivalence between database-driven applications written in our intermediate language and evaluate our tool on 21 benchmarks extracted from textbooks and real-world web applications. Our results show that the proposed methodology can successfully verify 20 of these benchmarks.

show abstract

“…For example, many alternative strategies exist to map associations and inheritance to database tables [3,4], each with their own benefits and drawbacks. The simple act of querying also presents the possibility of in-termixing database query languages within the application language, which leads to database vendor or technology lock-in, and development maintainability issues when the database schema evolves [6]. To address these issues, object-relational mapping (ORM) frameworks have been created and are used extensively in practice [4].…”

Section: Introductionmentioning

confidence: 99%

Object to NoSQL Database Mappers (ONDM): A systematic survey and comparison of frameworks

Reniers

Landuyt

Rafique

et al. 2019

Information Systems

View full text Add to dashboard Cite

Context: Software applications frequently interact with database systems to persist and retrieve objects. Objectmapping frameworks address (i) the bi-directional conversion of data between object and target database and (ii) provide a programmatic interface for querying and storing data. The rise of NoSQL databases poses challenges beyond object-relational mapping (ORM) frameworks to abstract from various data models and non-standardized API's, but also take into account the different database capabilities (e.g. unsupported query operators, data ordering). Objective: A systematic survey study of existing Object-NoSQL data mapping (ONDM) frameworks. Specific focus is given to the level of abstraction of data and operations to multiple database technologies, as a means to limit vendor and technology lock-in and an enabler for multi-store and polyglot architectures. Additional attention is paid to mapping strategies that are specific to NoSQL databases (e.g. object embedding, schema flexibility). Method: A systematic search methodology identifies all relevant mapping frameworks (in total 342 frameworks). Subsequently, a subset of ONDM frameworks is selected and systematically compared in terms of criteria of: database support, interface and query functionality, architecture and software coupling. Secondly, we provide an in-depth comparison of object-oriented mapping strategies for classes, inheritance, relationships, and attribute types to NoSQL data models. Results: ONDM frameworks are most prevalent in Java, Ruby, Python, and overall 54 frameworks support multiple NoSQL databases. Interfaces are frequently standardized and commonly feature a uniform query language and even native DB query mapping. However, database portability may be hindered due to non-uniform abstractions. As for mapping strategies, current frameworks do not fully exploit NoSQL modeling potential, such as (i) the embedding of relationship data within referring objects' records, (ii) mapping at the individual object-level vs. class-level, and lacking (iii) collection normalization despite being supported for associations or when using relational databases. Conclusion: The study consolidates knowledge on available ONDM frameworks, and applied object-document, object-graph, and object-column mapping patterns. The study can guide practitioners in framework selection, and pinpoints areas of future development and research in this domain, most notably towards improved support for flexible, NoSQL-aware mapping strategies.

show abstract

Synchronization of Queries and Views Upon Schema Evolutions

Cited by 23 publications

References 103 publications

Synthesizing database programs for schema refactoring

Synthesizing database programs for schema refactoring

Verifying equivalence of database-driven applications

Object to NoSQL Database Mappers (ONDM): A systematic survey and comparison of frameworks

Contact Info

Product

Resources

About