Automated Defect Prevention

Huizinga, Dorota; Kolawa, Adam

doi:10.1002/9780470165171

Cited by 46 publications

(5 citation statements)

References 24 publications

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“…to enable communication between autonomous intelligent agents). Some of these tasks can also be evaluated quantitatively: while consistency of a conceptual model is a binary quality that relies on a consistency proof, incorrect consequences can be estimated using predefined tests that aim to make inferences of a certain kind [ 104 ]. A formal specification of the meaning of a term using an ontology can be accompanied by a meta-theoretical analysis and a completeness proof for the ontology [ 105 ].…”

Section: Evaluation Of Research Results In Biomedical Ontologymentioning

confidence: 99%

Evaluation of research in biomedical ontologies

Hoehndorf¹,

Dumontier²,

Gkoutos

2012

Briefings in Bioinformatics

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Ontologies are now pervasive in biomedicine, where they serve as a means to standardize terminology, to enable access to domain knowledge, to verify data consistency and to facilitate integrative analyses over heterogeneous biomedical data. For this purpose, research on biomedical ontologies applies theories and methods from diverse disciplines such as information management, knowledge representation, cognitive science, linguistics and philosophy. Depending on the desired applications in which ontologies are being applied, the evaluation of research in biomedical ontologies must follow different strategies. Here, we provide a classification of research problems in which ontologies are being applied, focusing on the use of ontologies in basic and translational research, and we demonstrate how research results in biomedical ontologies can be evaluated. The evaluation strategies depend on the desired application and measure the success of using an ontology for a particular biomedical problem. For many applications, the success can be quantified, thereby facilitating the objective evaluation and comparison of research in biomedical ontology. The objective, quantifiable comparison of research results based on scientific applications opens up the possibility for systematically improving the utility of ontologies in biomedical research.

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Section: Evaluation Of Research Results In Biomedical Ontologymentioning

confidence: 99%

Evaluation of research in biomedical ontologies

Hoehndorf¹,

Dumontier²,

Gkoutos

2012

Briefings in Bioinformatics

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“…Testing methods play a crucial part in widening the scope of the test and in determination of strategies used in the test result analysis [5]. Several test methods are available to determine various qualitative aspects of the software application.…”

Section: Methodsmentioning

confidence: 99%

“…All of the listed issues are easily eliminated by the implementation of automated testing methods. Automated testing is a process using software separate from the software under test to control test execution and compare actual results with expected results [5].…”

Section: Introductionmentioning

confidence: 99%

Research of intelligent methods of software testing

Kazimov

Bayramova

Malikova

2021

SRIT

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This article presents the examination of several techniques and tools used in the automated software testing process. Considering the ever-growing importance of software testing, several possible implications of implementation of artificial intelligence into this area are also discussed. The main objective of this study is to examine the field of test automation by categorising related test activities, to which artificial intelligence tools can be applied for increased efficiency, and evaluate the impact of the application. The main software testing methods are white-box, black-box, and grey-box methods; an effort has been made to determine a connection between the given testing methods and artificial intelligence methods. A brief summary of several artificial intelligence engine tools used to automate testing was also provided. Lastly, the possible future benefits from usage of AI in software testing was investigated.

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“…Fault prevention is made possible by giving programmers real‐time guidance during programming and enabling the automatic generation of code for fragments of the specification. This is supported by the automation and incremental implementation principles for fault prevention as illustrated in Huizinga and Kolawa [65]. Automation for routine task is suggested as one of the best software engineering practices for scientific software development in [51] and mentioned frequently as one of the fault mitigation strategies related to processes by professional developers [12].…”

Section: Related Workmentioning

confidence: 99%

Requirements‐related fault prevention during the transformation from formal specifications to programs

Liu

2023

IET Software

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Software faults are costly to find and remove from programs. It is better to avoid inserting the faults in the first place. The authors identify requirements‐related faults that can arise during the transformation of formal specifications into programs, analyse each to discover its causes, and propose corresponding fault prevention methods. The approach works by analysing a specification, decomposing it into specification fragments with different levels like components, determining the correct implementation order among the components, and enabling automated code generation for the components and other low‐level specification fragments. The approach seeks to reduce the faults in programs significantly by guiding programmers to work effectively and productively. The authors evaluate the approach's performance experimentally and compare it to the performance of a fault‐prevention method with industry applications.

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Automated Defect Prevention

Cited by 46 publications

References 24 publications

Evaluation of research in biomedical ontologies

Evaluation of research in biomedical ontologies

Research of intelligent methods of software testing

Requirements‐related fault prevention during the transformation from formal specifications to programs

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