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You searched for subject:(Selective Mutation). Showing records 1 – 2 of 2 total matches.

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1. Gamini, Devi charan. Generate Test Selection Statistics With Automated Selective Mutation.

Degree: 2020, , Department of Computer Science

Context. Software systems are under constant updating for being faulty and to improve and introduce features. The Software testing is the most commonly used  method for validating the quality of software systems. Agile processes help to  automate testing process. A regression test is the main strategy used in testing. Regression testing is time consuming, but with increase in codebases is making it more time extensive and time consuming. Making regression testing time efficient for continuous integration is the new strategy.   Objectives. This thesis focuses on co-relating code packages to test packages by automating mutation to inject error into C code. Regression testing against mutated code establishes co-relations. Co-relation data of particular modified code packages can be used for test selections. This method is most effective than the traditional test selection method. For this thesis to reduce the mutation costs selective mutation method is selected. Demonstrating the proof of concept helps to prove proposed  hypothesis.   Methods. An experiment answers the research questions. Testing of hypothesis on open source C programs will evaluate efficiency. Using this correlation method testers can reduce the testing cycles regardless of test environments. Results. Experimenting with sample programs using automated selective mutation the efficiency to co-relate tests to code packages was 93.4%.   Results. After experimenting with sample programs using automated selective mutation the efficiency to co-relate tests to code packages was 93.4%.   Conclusions. This research concludes that the automated mutation to obtain test selection statistics can be adopted. Though it is difficult for mutants to fail every test case, supposing that this method works with 93.4% efficient test failure on an average, then this method can reduce the test suite size to 5% for the particular modified code package.

Subjects/Keywords: Regression testing; test case selection; mutation testing; selective mutation.; Computer Sciences; Datavetenskap (datalogi)

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Gamini, D. c. (2020). Generate Test Selection Statistics With Automated Selective Mutation. (Thesis). , Department of Computer Science. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:bth-19313

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Gamini, Devi charan. “Generate Test Selection Statistics With Automated Selective Mutation.” 2020. Thesis, , Department of Computer Science. Accessed May 06, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-19313.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Gamini, Devi charan. “Generate Test Selection Statistics With Automated Selective Mutation.” 2020. Web. 06 May 2021.

Vancouver:

Gamini Dc. Generate Test Selection Statistics With Automated Selective Mutation. [Internet] [Thesis]. , Department of Computer Science; 2020. [cited 2021 May 06]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:bth-19313.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Gamini Dc. Generate Test Selection Statistics With Automated Selective Mutation. [Thesis]. , Department of Computer Science; 2020. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:bth-19313

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Brno University of Technology

2. Procházka, Ondřej. Metody detekce selekce v DNA sekvencích: Methods to detect selection in DNA sequences.

Degree: 2019, Brno University of Technology

The topic of semestral thesis is methods to detect selection in DNA sequences. In the begining of the thesis we will describe molecular evolution. It will be written what made the evolution and how the evolution is shown. Moreover there are gen mutations and mechanisms of diffuse and fixation. It will be defined what pozitive, negative and neutral selection is. The thesis is focused on evolution distance of synonymous and nonsynonymous substitution. There will be described three methods – Nei-Gojobori, Li-Wu-Luo and Comeron. All these methods will be described with mathematic formulas. There will be statistic test to decide what kind of selection ti is – there will be used z-test. In the practical part, there will be information about developed software what counts selection pressure from sequences from databazes in format GenBank and it shows parts where selection is. The software will be used for two data sets with two different genetic codes. The result will be discussed. We will discuss results of all three methods of selection pressure and influence of input parametrs. Advisors/Committee Members: Škutková, Helena (advisor), Maděránková, Denisa (referee).

Subjects/Keywords: Mutace; přírodní výběr; selekce; selekční tlak; Ka/Ks poměr; Nei-Gojobori; Li-Wu-Luo; Comeron; synonymní substituce; nesynonymní substituce; Mutation; selection; natural selection; selective pressure; Ka/Ks ratio; Nei-Gojobori; Li-Wu-Luo; Comeron; synonymous substitution; nonsynonymous substitution

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Procházka, O. (2019). Metody detekce selekce v DNA sekvencích: Methods to detect selection in DNA sequences. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/59862

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Procházka, Ondřej. “Metody detekce selekce v DNA sekvencích: Methods to detect selection in DNA sequences.” 2019. Thesis, Brno University of Technology. Accessed May 06, 2021. http://hdl.handle.net/11012/59862.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Procházka, Ondřej. “Metody detekce selekce v DNA sekvencích: Methods to detect selection in DNA sequences.” 2019. Web. 06 May 2021.

Vancouver:

Procházka O. Metody detekce selekce v DNA sekvencích: Methods to detect selection in DNA sequences. [Internet] [Thesis]. Brno University of Technology; 2019. [cited 2021 May 06]. Available from: http://hdl.handle.net/11012/59862.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Procházka O. Metody detekce selekce v DNA sekvencích: Methods to detect selection in DNA sequences. [Thesis]. Brno University of Technology; 2019. Available from: http://hdl.handle.net/11012/59862

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

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