Investigating Different Metrics for Evaluation and Selection of Mutation Operators for Java

Mutation testing is a successful and powerful technique, specifically designed for injecting the artificial faults. Although it is effective at revealing the faults, test suite assessment and its reduction, however, suffer from the expense of executing a large number of mutants. The researchers have proposed different types of cost reduction techniques in the literature. These techniques highly depend on the inspection of mutation operators. Several metrics have been evolved for the same. The selective mutation technique is most frequently used by the researchers. In this paper, the authors investigate different metrics for evaluating the traditional mutation operators for Java. Results on 13 Java programs indicate how grouping few operators can impact the effectiveness of an adequate and minimal test suite, and how this could provide several cost benefits.

The mechanism of selective kinesin inhibition by kinesin binding protein

Subcellular compartmentalisation is necessary for eukaryotic cell function. Spatial and temporal regulation of kinesin activity is essential for building these local environments via control of intracellular cargo distribution. Kinesin binding protein (KBP) interacts with a subset of kinesins via their motor domains, inhibits their microtubule (MT) attachment and blocks their cellular function. However, its mechanisms of inhibition and selectivity have been unclear. Here we use cryo-electron microscopy to reveal the structure of KBP and of a KBP-kinesin motor domain complex. KBP is a TPR-containing, crescent-shaped right-handed α-solenoid that sequesters the tubulin-binding surface of the kinesin motor domain, structurally distorting the motor domain and sterically blocking MT attachment. KBP uses its α-solenoid concave face and edge loops to bind the kinesin motor domain and selective mutation of this extended binding surface disrupts KBP inhibition of kinesin transport in cells. The KBP-interacting surface of the motor domain contains motifs exclusively conserved in KBP-interacting kinesins, providing a basis for kinesin selectivity.

Selecting fault revealing mutants

Mutant selection refers to the problem of choosing, among a large number of mutants, the (few) ones that should be used by the testers. In view of this, we investigate the problem of selecting the fault revealing mutants, i.e., the mutants that are killable and lead to test cases that uncover unknown program faults. We formulate two variants of this problem: the fault revealing mutant selection and the fault revealing mutant prioritization. We argue and show that these problems can be tackled through a set of ‘static’ program features and propose a machine learning approach, named FaRM, that learns to select and rank killable and fault revealing mutants. Experimental results involving 1,692 real faults show the practical benefits of our approach in both examined problems. Our results show that FaRM achieves a good trade-off between application cost and effectiveness (measured in terms of faults revealed). We also show that FaRM outperforms all the existing mutant selection methods, i.e., the random mutant sampling, the selective mutation and defect prediction (mutating the code areas pointed by defect prediction). In particular, our results show that with respect to mutant selection, our approach reveals 23% to 34% more faults than any of the baseline methods, while, with respect to mutant prioritization, it achieves higher average percentage of revealed faults with a median difference between 4% and 9% (from the random mutant orderings).

Structural and Functional analysis of the GABARAP Interaction Motif (GIM)

Through the canonical LC3 interaction motif (LIR), [W/F/Y]-X1-X2-[I/L/V], protein complexes are recruited to autophagosomes to perform their functions as either autophagy adaptors or receptors. How these adaptors/receptors selectively interact with either LC3 or GABARAP families remains unclear. Herein, we determine the range of selectivity of 30 known core LIR motifs towards LC3s and GABARAPs. From these, we define a GABARAP Interaction Motif (GIM) sequence (W/F-V-X2-V) that the adaptor protein PLEKHM1 tightly conforms to. Using biophysical and structural approaches, we show that the PLEKHM1-LIR is indeed eleven-fold more specific for GABARAP than LC3B. Selective mutation of the X1 and X2 positions either completely abolished the interaction with all LC3 and GABARAPs or increased PLEKHM1-GIM selectivity 20-fold towards LC3B. Finally, we show that conversion of the canonical p62/SQSTM1-LIR into our newly defined GIM, by introducing two valine residues, enhances p62/SQSTM1 interaction with endogenous GABARAP over LC3B. The identification of a GABARAP-specific interaction motif will aid the identification and characterization of the continually expanding array of autophagy receptor and adaptor proteins and their in vivo functions.