Comprehensive Review on the State-of- the-arts and Solutions to the Test Redundancy Reduction Problem with Taxonomy Article Swipe
Mizanur Rahman
,
Kamal Z. Zamli
,
Md. Abdul Kader
,
Roslina Mohd Sidek
,
Fakhrud Din
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.37934/araset.34.3.6287
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.37934/araset.34.3.6287
The process of software testing is of utmost importance and requires a major allocation of resources. It has a substantial influence on the quality and dependability of software products. Nevertheless, as the quantity of test cases escalates, the feasibility of executing all of them diminishes, and the accompanying expenses related to preparation, execution time, and upkeep grow excessively exorbitant. The objective of Test Redundancy Reduction (TRR) is to mitigate this issue by determining a minimal subset of the test suite that satisfies all the requirements of the primary test suite while lowering the number of test cases. In order to attain this objective, multiple methodologies have been suggested, encompassing heuristics, meta-heuristics, exact algorithms, hybrid approaches, and machine-learning techniques. This work provides a thorough examination of prior research on TRR, addressing deficiencies and making a valuable contribution to the current scholarly understanding. The literature study encompasses a comprehensive examination of the complete chronology of TRR, incorporating all pertinent scholarly articles and practitioner-authored research papers published in English. This study aims to provide managers with valuable insights into the strengths and shortcomings of different TRR methodologies, enabling them to make well-informed decisions regarding the most appropriate approach for their specific needs. The primary objective of this study is to offer a comprehensive analysis of Test Result Reduction (TRR) and its consequential impact on mitigating expenses related to software testing. This study makes a valuable contribution to extant literature by elucidating the present state-of-the-art and delineating potential avenues for future research.
Related Topics
Concepts
Heuristics
Dependability
Redundancy (engineering)
Computer science
Suite
Risk analysis (engineering)
Test suite
Test (biology)
Software
Data science
Management science
Test case
Operations research
Reliability engineering
Software engineering
Engineering
Machine learning
Business
Archaeology
Paleontology
History
Programming language
Biology
Regression analysis
Operating system
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.37934/araset.34.3.6287
- https://semarakilmu.com.my/journals/index.php/applied_sciences_eng_tech/article/download/2933/3137
- OA Status
- hybrid
- Cited By
- 5
- References
- 57
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4389954687
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4389954687Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.37934/araset.34.3.6287Digital Object Identifier
- Title
-
Comprehensive Review on the State-of- the-arts and Solutions to the Test Redundancy Reduction Problem with TaxonomyWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-12-16Full publication date if available
- Authors
-
Mizanur Rahman, Kamal Z. Zamli, Md. Abdul Kader, Roslina Mohd Sidek, Fakhrud DinList of authors in order
- Landing page
-
https://doi.org/10.37934/araset.34.3.6287Publisher landing page
- PDF URL
-
https://semarakilmu.com.my/journals/index.php/applied_sciences_eng_tech/article/download/2933/3137Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
hybridOpen access status per OpenAlex
- OA URL
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https://semarakilmu.com.my/journals/index.php/applied_sciences_eng_tech/article/download/2933/3137Direct OA link when available
- Concepts
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Heuristics, Dependability, Redundancy (engineering), Computer science, Suite, Risk analysis (engineering), Test suite, Test (biology), Software, Data science, Management science, Test case, Operations research, Reliability engineering, Software engineering, Engineering, Machine learning, Business, Archaeology, Paleontology, History, Programming language, Biology, Regression analysis, Operating systemTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
5Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 3, 2024: 2Per-year citation counts (last 5 years)
- References (count)
-
57Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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