Industrially Applicable System Regression Test Prioritization in Production Automation

Ulewicz, Sebastian; Vogel‐Heuser, Birgit

doi:10.1109/tase.2018.2810280

Cited by 24 publications

(11 citation statements)

References 18 publications

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“…A similar distinction could be found in another pair of metamodels: FM4IEC and a control flow analysis metamodel of PLC programs [63]. Both metamodels depict IEC 61131‐3 SFC in which the elements of steps and transitions compose the program.…”

Section: Analyses On Metamodel Inconsistenciesmentioning

confidence: 60%

Analysis of metamodels for model‐based production automation system engineering

Cha

Vogel‐Heuser

Fischer

2020

IET Collaborative Intelligent Manufacturing

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Section: Analyses On Metamodel Inconsistenciesmentioning

confidence: 60%

Analysis of metamodels for model‐based production automation system engineering

Cha

Vogel‐Heuser

Fischer

2020

IET Collaborative Intelligent Manufacturing

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“…Even if test management systems are considered, the time and effort required to extract the information should not be disregarded [63]. To cope with this, some authors update data asynchronously [16] and build specific tools to automate the extraction of information [58,109].…”

Section: Industry Studies In Regression Testingmentioning

confidence: 99%

A Taxonomy of Information Attributes for Test Case Prioritisation: Applicability, Machine Learning

Ramírez,

Feldt,

Romero

2022

Preprint

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Most software companies have extensive test suites and re-run parts of them continuously to ensure recent changes have no adverse effects. Since test suites are costly to execute, industry needs methods for test case prioritisation (TCP). Recently, TCP methods use machine learning (ML) to exploit the information known about the system under test (SUT) and its test cases. However, the value added by ML-based TCP methods should be critically assessed with respect to the cost of collecting the information. This paper analyses two decades of TCP research, and presents a taxonomy of 91 information attributes that have been used. The attributes are classified with respect to their information sources and the characteristics of their extraction process. Based on this taxonomy, TCP methods validated with industrial data and those applying ML are analysed in terms of information availability, attribute combination and definition of data features suitable for ML. Relying on a high number of information attributes, assuming easy access to SUT code and simplified testing environments are identified as factors that might hamper industrial applicability of ML-based TCP. The T PIA taxonomy provides a reference framework to unify terminology and evaluate alternatives considering the cost-benefit of the information attributes.CCS Concepts: • Software and its engineering → Software testing and debugging; • Computing methodologies → Machine learning.

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“…In paper [2] authors introduced evaluated by using the open source applications and results have been drawn to perform effective regression testing based on the test case prioritization. In paper [8] author proposed a novel approach which optimize the testing process after doing the modifications for the existing software. This process has some automatic nature of identifying and ordering the test cases for detection of the false with time bounds.…”

Section: Related Workmentioning

confidence: 99%

A Regression Test Based on the Test Case Prioritization Techniques by using the Nature of Bees

2019

IJITEE

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 Abstract: The software testing is a crucial role in the software development lifecycle. Testing can be done by the user who have full knowledge on the software, who has no knowledge and who has knowledge little bit on the software and the software testing can be tested in various level with various tests like unit, integrate, user, regression, acceptance etc.. The major and most important test is the regression testing. To perform the regression testing it takes more time. The current paper was focused on the regression testing to reduce the execution time and to improve the faults detection rate by considering the parameter of change coverage. The proposed system uses the test case prioritization techniques by using the nature of the bees. After performing the experimental study on an open source applications, the proposed system shows the efficiency and effectiveness in terms of the runtime and detecting faults when compared with the traditional system.

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Industrially Applicable System Regression Test Prioritization in Production Automation

Cited by 24 publications

References 18 publications

Analysis of metamodels for model‐based production automation system engineering

Analysis of metamodels for model‐based production automation system engineering

A Taxonomy of Information Attributes for Test Case Prioritisation: Applicability, Machine Learning

A Regression Test Based on the Test Case Prioritization Techniques by using the Nature of Bees

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