JDAMA: Java database application mutation analyser

Zhou, Chixiang; Frankl, Phyllis G.

doi:10.1002/stvr.462

Cited by 16 publications

(11 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For instance, Chays et al [39] and Zhou et al [40] respectively created methods for automatically generating test cases and performing mutation analysis. It is also possible to use combinatorial data generators to test database applications, as was investigated by Li et al [41].…”

Section: Related Workmentioning

confidence: 99%

DOMINO: Fast and Effective Test Data Generation for Relational Database Schemas

Kapfhammer

McMinn

2018

2018 IEEE 11th International Conference on Software Testing, Verification and Validation (ICST)

View full text Add to dashboard Cite

Abstract-An organization's databases are often one of its most valuable assets. Data engineers commonly use a relational database because its schema ensures the validity and consistency of the stored data through the specification and enforcement of integrity constraints. To ensure their correct specification, industry advice recommends the testing of the integrity constraints in a relational schema. Since manual schema testing is laborintensive and error-prone, this paper presents DOMINO, a new automated technique that generates test data according to a coverage criterion for integrity constraint testing. In contrast to more generalized search-based approaches, which represent the current state of the art for this task, DOMINO uses tailored, domain-specific operators to efficiently generate test data for relational database schemas. In an empirical study incorporating 34 relational database schemas hosted by three different database management systems, the results show that DOMINO can not only generate test suites faster than the state-of-the-art search-based method but that its test suites can also detect more schema faults.

show abstract

Section: Related Workmentioning

confidence: 99%

DOMINO: Fast and Effective Test Data Generation for Relational Database Schemas

Kapfhammer

McMinn

2018

2018 IEEE 11th International Conference on Software Testing, Verification and Validation (ICST)

View full text Add to dashboard Cite

show abstract

“…In the fault-based category the existing works range from the development of sets of mutants for SQL queries [17], [18] or schemas [19], [20], [21] to the evaluation of the fault-detection effectiveness with tools [22], [23], [24], [25], fault-localization [26] and empirical studies [27]. Others are application specific, mainly with the goal of detecting SQL injection vulnerabilities [28], [29], [30] and preventing them [31].…”

Section: Test Coverage For Database Applicationsmentioning

confidence: 99%

Coverage-Aware Test Database Reduction

Tuya

Riva

Suárez-Cabal

et al. 2016

IIEEE Trans. Software Eng.

View full text Add to dashboard Cite

Abstract-Functional testing of applications that process the information stored in databases often requires a careful design of the test database. The larger the test database, the more difficult it is to develop and maintain tests as well as to load and reset the test data. This paper presents an approach to reduce a database with respect to a set of SQL queries and a coverage criterion. The reduction procedures search the rows in the initial database that contribute to the coverage in order to find a representative subset that satisfies the same coverage as the initial database. The approach is automated and efficiently executed against large databases and complex queries. The evaluation is carried out over two real life applications and a well-known database benchmark. The results show a very large degree of reduction as well as scalability in relation to the size of the initial database and the time needed to perform the reduction.

show abstract

“…Previously, we implemented a research infrastructure called JDAMA [1] to evaluate and assess quality assurance techniques (e.g., test generation, and test adequacy criteria) for database applications. In this paper, we concentrate on the evaluation of three test adequacy criteria: statement coverage, branch coverage, and command form coverage in the context of Java database applications.…”

Section: Introductionmentioning

confidence: 99%

Empirical Studies on Test Effectiveness for Database Applications

Zhou

Frankl

2012

2012 IEEE Fifth International Conference on Software Testing, Verification and Validation

Self Cite

View full text Add to dashboard Cite

This paper presents empirical studies of test effectiveness for Java database applications. We primarily address two research questions: (1) What is the relationship between test set size, coverage criteria, and test effectiveness for Java/JDBC programs? (2) Which adequacy criterion is more suitable for testing Java database applications, statement coverage, branch coverage, or command form coverage? We collected data sets by experimenting on several moderately complex open source database application programs, and performed a series of rigorous and comprehensive statistical analyses. The results show that linear models fit the relationship of size and coverage to effectiveness well and that coverage appears to have greater impact on effectiveness than size. However, surprisingly, command form coverage was not consistently more effective than statement or branch coverage.

show abstract

JDAMA: Java database application mutation analyser

Cited by 16 publications

References 30 publications

DOMINO: Fast and Effective Test Data Generation for Relational Database Schemas

DOMINO: Fast and Effective Test Data Generation for Relational Database Schemas

Coverage-Aware Test Database Reduction

Empirical Studies on Test Effectiveness for Database Applications

Contact Info

Product

Resources

About