Software quality assurance becomes especially critical if bioinformatics tools are to be used in audtranslational medical setting, such as analysis and interpretation of biological data. We mustudensure that only validated algorithms are used, and that they are implemented correctly in theudanalysis pipeline – and not disrupted by hardware or software failure. In this thesis, I reviewudcommon quality assurance practice and guidelines for bioinformatics software testing.udFurthermore, I present a novel cloud-based framework to enable automated testing of geneticudsequence alignment programs. This framework performs testing based on gold standardudsimulation data sets, and metamorphic testing. I demonstrate the effectiveness of this cloudbasedudframework using two widely used sequence alignment programs, BWA and Bowtie, andudsome fault-seeded ‘mutant’ versions of BWA and Bowtie. This preliminary study demonstratesudthat this type of cloud-based software testing framework is an effective and promising way toudimplement quality assurance in bioinformatics software that is used in genomic medicine.
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