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Related Concept Videos

Translation01:31

Translation

14.9K
Translation is the process of synthesizing proteins from the genetic information carried by messenger RNA (mRNA). Following transcription, it constitutes the final step in the expression of genes. This process is carried out by ribosomes, complexes of protein and specialized RNA molecules. Ribosomes, transfer RNA (tRNA), and other proteins produce a chain of amino acids—the polypeptide—as the end product of translation.
Translation Produces the Building Blocks of Life
Proteins are...
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Improving Translational Accuracy02:07

Improving Translational Accuracy

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Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
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Leaky Scanning02:28

Leaky Scanning

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During most eukaryotic translation processes, the small 40S ribosome subunit scans an mRNA from its 5' end until it encounters the first start AUG codon. The large 60S ribosomal subunit then joins the smaller one to initiate protein synthesis. The location of the translation initiation is largely determined by the nucleotides near the start codon as there may be multiple translation initiation sites present on the mRNA.  Marilyn Kozak discovered that the sequence RCCAUGG (where R...
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Initiation of Translation02:33

Initiation of Translation

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Initiating translation is complex because it involves multiple molecules. Initiator tRNA, ribosomal subunits, and eukaryotic initiation factors (eIFs) are all required to assemble on the initiation codon of mRNA. This process consists of several steps that are mediated by different eIFs.
First, the initiator tRNA must be selected from the pool of elongator tRNAs by eukaryotic initiation factor 2 (eIF2). The initiator tRNA (Met-tRNAi) has conserved sequence elements including modified bases at...
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Mutations01:35

Mutations

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Mutations are changes in the sequence of DNA. These changes can occur spontaneously or they can be induced by exposure to environmental factors. Mutations can be characterized in a number of different ways: whether and how they alter the amino acid sequence of the protein, whether they occur over a small or large area of DNA, and whether they occur in somatic cells or germline cells.
Chromosomal Alterations Are Large-Scale Mutations
While point mutations are changes in a single nucleotide in...
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Termination of Translation01:44

Termination of Translation

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Analysis of Translation Initiation During Stress Conditions by Polysome Profiling
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Mutation analysis for evaluating code translation.

Giovani Guizzo1, Jie M Zhang2, Federica Sarro1

  • 1University College London, England, UK.

Empirical Software Engineering
|December 11, 2023
PubMed
Summary
This summary is machine-generated.

Mutation-based Translation Analysis (MBTA) assesses code translation by comparing program mutants to their translated versions. This method reveals significant translation bugs missed by traditional evaluations, indicating current translators have low trustworthiness.

Keywords:
Code translationMutation testingSource to source translation

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Area of Science:

  • Software Engineering
  • Programming Language Translation
  • Software Testing

Background:

  • Current code translation evaluation methods like BLEU scores lack semantic consideration, while test execution results suffer from insufficient data.
  • Assessing the semantic correctness of source-to-source code translation remains a significant challenge in software engineering.

Purpose of the Study:

  • To introduce Mutation-based Code Translation Analysis (MBTA) and Mutation-based Translation Score (MTS) for a more robust evaluation of code translators.
  • To assess the effectiveness and trustworthiness of existing code translation tools using the proposed MBTA framework.

Main Methods:

  • Developed MBTA, applying mutation analysis to compare program mutants against their translated counterparts, not the original program.
  • Introduced MTS, a metric to quantify translator trustworthiness based on the number of killed mutants.
  • Conducted a case study using 612 Java-Python pairs and 75,082 mutants on TransCoder and j2py.

Main Results:

  • MBTA revealed that TransCoder and j2py incorrectly translate over two-thirds of mutants (70.44% and 70.64%, respectively).
  • The MTS metric identified translation bugs missed by conventional evaluation methods.
  • The study demonstrates the feasibility and effectiveness of MBTA in uncovering subtle translation errors.

Conclusions:

  • Existing source-to-source code translators exhibit significant semantic inaccuracies.
  • MBTA provides a novel and effective approach for assessing code translation quality and trustworthiness.
  • The proposed MTS metric offers deeper insights into translator performance beyond syntactic or basic semantic checks.