Search-Based Testing of Relational Schema Integrity Constraints Across Multiple Database Management Systems

Kapfhammer, Gregory M.; McMinn, Phil; Wright, Chris J.

doi:10.1109/icst.2013.47

Cited by 32 publications

(54 citation statements)

References 14 publications

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“…The Alternating Variable Method (AVM) [9], [15], [16] is a local search technique that has been used to successfully generate test data for programs [17], [18] and has been applied to the automated generation of data for the INSERT statements used when testing relational database schemas [7], [10]. The AVM works to optimize a vector of test values according to a fitness function.…”

Section: B Search-based Test Data Generationmentioning

confidence: 99%

“…Based on the Alternating Variable Method (AVM) [9], this state-of-the-art method for generating schema tests is a searchbased one that receives guidance from a fitness function [7], [10]. Yet, the generation of schema tests with search can be slow, particularly when it must locate columns that need to have identical values and then adjust those values until they are the same.…”

Section: Introductionmentioning

confidence: 99%

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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)

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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.

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Section: B Search-based Test Data Generationmentioning

confidence: 99%

Section: Introductionmentioning

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)

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View full text Add to dashboard Cite

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“…The AVM has also found application to additional problems, including decision ordering for software product lines [22], balancing workload in requirements assignment [21], solving reliability-redundancy-allocation problems [20], as well as test case selection [19] and test suite prioritization [2]. Since Korel's original work, the AVM has been extended and improved for problems in SBSE: now it can handle more variable types, including fixed-point numbers [7] and strings [9,18], and can leverage new strategies proven to speed up the search for certain common types of objective function landscape [10,11].…”

Section: Introductionmentioning

confidence: 99%

“…Exploratory moves correspond to the smallest possible increments and decrements of the variable (i.e., ±10 −p ). Strings may also now be handled by the approach [9,18]. A string variable is essentially 1: while true do ⊲ {IPS}…”

Section: Introductionmentioning

confidence: 99%

“…In 2007, Harman and McMinn [7] reported its effectiveness and efficiency for a series of C programs, and combined it with a GA to provide a "best of" Memetic Algorithm approach [8]. It has since been implemented into tools to generate test data for C programs (e.g., IGUANA [17] and AUSTIN [14,15]); generate Java test suites with EvoSuite [3,4]; create relational database data with the SchemaAnalyst tool [9,18]; and combined with dynamic symbolic execution in Microsoft's Pex tool [16]. The AVM has also found application to additional problems, including decision ordering for software product lines [22], balancing workload in requirements assignment [21], solving reliability-redundancy-allocation problems [20], as well as test case selection [19] and test suite prioritization [2].…”

Section: Introductionmentioning

confidence: 99%

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AVMf: An Open-Source Framework and Implementation of the Alternating Variable Method

McMinn

Kapfhammer

2016

Search Based Software Engineering

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Abstract. The Alternating Variable Method (AVM) has been shown to be a fast and effective local search technique for search-based software engineering. Recent improvements to the AVM have generalized the representations it can optimize and have provably reduced its running time. However, until now, there has been no general, publicly-available implementation of the AVM incorporating all of these developments. We introduce AVMf , an object-oriented Java framework that provides such an implementation. AVMf is available from http://avmframework.org for configuration and use in a wide variety of projects.

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A systematic literature review of how mutation testing supports quality assurance processes

Zhu

Panichella

Zaidman

2018

Software Testing Verif & Rel

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Mutation testing has been very actively investigated by researchers since the 1970s, and remarkable advances have been achieved in its concepts, theory, technology, and empirical evidence.While the most influential realisations have been summarised by existing literature reviews, we lack insight into how mutation testing is actually applied. Our goal is to identify and classify the main applications of mutation testing and analyse the level of replicability of empirical studies related to mutation testing. To this aim, this paper provides a systematic literature review on the application perspective of mutation testing based on a collection of 191 papers published between 1981 and 2015. In particular, we analysed in which quality assurance processes mutation testing is used, which mutation tools and which mutation operators are employed. Additionally, we also investigated how the inherent core problems of mutation testing, ie, the equivalent mutant problem and the high computational cost, are addressed during the actual usage. The results show that most studies use mutation testing as an assessment tool targeting unit tests, and many of the supporting techniques for making mutation testing applicable in practice are still underdeveloped.Based on our observations, we made 9 recommendations for future work, including an important suggestion on how to report mutation testing in testing experiments in an appropriate manner. KEYWORDSapplication, mutation testing, systematic literature review 1 INTRODUCTION Mutation testing is defined by Jia and Harman [1] as a fault-based testing technique, which provides a testing criterion called the mutation adequacy score. This score can be used to measure the effectiveness of a test set in terms of its ability to detect faults [1]. The principle of mutation testing is to introduce syntactic changes into the original program to generate faulty versions (called mutants) according to well-defined rules (mutation operators) [2]. Mutation testing originated in the 1970s with works from Lipton [3], DeMillo et al. [4], and Hamlet [5] and has been a very active research field over the last few decades. The activeness of the field is in part evidenced by the extensive survey of more than 390 papers on mutation testing that Jia and Harman published in 2011 [1]. Jia and Harman's survey highlights the research achievements that have been made over the years, including the development of tools for a variety of languages and empirical studies performed [1]. Additionally, they highlight some of the actual and inherent problems of mutation testing, among others: (1) the high computational cost caused by generating and executing the numerous mutants and (2) the tremendous time-consuming human investigation required by the test oracle problem and equivalent mutant detection.While existing surveys (eg [1,2,6]) provide us with a great overview of the most influential realisations in research, we lack insight into how mutation testing is actually applied. Specifically, we are interested in analysing ...

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Search-Based Testing of Relational Schema Integrity Constraints Across Multiple Database Management Systems

Cited by 32 publications

References 14 publications

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

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

AVMf: An Open-Source Framework and Implementation of the Alternating Variable Method

A systematic literature review of how mutation testing supports quality assurance processes

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