Are Smell-Based Metrics Actually Useful in Effort-Aware Structural Change-Proneness Prediction? An Empirical Study

Bad code smells (also named as code smells) are symptoms of poor design choices in implementation. Existing studies empirically confirmed that the presence of code smells increases the likelihood of subsequent changes (i.e., change-proness). However, to the best of our knowledge, no prior studies have leveraged smell-based metrics to predict particular change type (i.e., structural changes). Moreover, when evaluating the effectiveness of smell-based metrics in structural change-proneness prediction, none of existing studies take into account of the effort inspecting those change-prone source code. In this paper, we consider five smell-based metrics for effort-aware structural change-proneness prediction and compare these metrics with a baseline of well-known CK metrics in predicting particular categories of change types. Specifically, we first employ univariate logistic regression to analyze the correlation between each smellbased metric and structural change-proneness. Then, we build multivariate prediction models to examine the effectiveness of smell-based metrics in effort-aware structural change-proneness prediction when used alone and used together with the baseline metrics, respectively. Our experiments are conducted on six Java open-source projects with up to 60 versions and results indicate that: (1) all smell-based metrics are significantly related to structural change-proneness, except metric ANS in hive and SCM in camel after removing confounding effect of file size; (2) in most cases, smell-based metrics outperform the baseline metrics in predicting structural change-proneness; and (3) when used together with the baseline metrics, the smell-based metrics are more effective to predict change-prone files with being aware of inspection effort

Overcoming Catastrophic Forgetting in Graph Neural Networks

Catastrophic forgetting refers to the tendency that a neural network "forgets" the previous learned knowledge upon learning new tasks. Prior methods have been focused on overcoming this problem on convolutional neural networks (CNNs), where the input samples like images lie in a grid domain, but have largely overlooked graph neural networks (GNNs) that handle non-grid data. In this paper, we propose a novel scheme dedicated to overcoming catastrophic forgetting problem and hence strengthen continual learning in GNNs. At the heart of our approach is a generic module, termed as topology-aware weight preserving~(TWP), applicable to arbitrary form of GNNs in a plug-and-play fashion. Unlike the main stream of CNN-based continual learning methods that rely on solely slowing down the updates of parameters important to the downstream task, TWP explicitly explores the local structures of the input graph, and attempts to stabilize the parameters playing pivotal roles in the topological aggregation. We evaluate TWP on different GNN backbones over several datasets, and demonstrate that it yields performances superior to the state of the art. Code is publicly available at \url{https://github.com/hhliu79/TWP}.Comment: Accepted by AAAI 202

Cryptographic Enforcement of Attribute-based Authentication

Doktorgradsavhandling,This dissertation investigates on the cryptographic enforcement about attributebased authentication (ABA) schemes. ABA is an approach to authenticate users via attributes, which are properties of users to be authenticated, environment conditions such as time and locations. By using attributes in place of users’ identity information, ABA can provide anonymous authentication, or more specifically, ABA enables to keep users anonymous from their authenticators. In addition, the property of least information leakage provides better protection for users’ privacy compared with public key based authentication approaches. These properties make it possible to apply ABA schemes in privacy preserving scenarios, for instance, cloud-based applications. The most important security requirements of ABA schemes consist of anonymity, traceability, unforgeability, unlinkability and collision resistance. In this dissertation, we combine these security requirements with other properties such as hierarchy to divide ABA schemes into different categories, based on which we use examples to demonstrate how to construct these schemes cryptographically. The main contributions of this dissertation include the following aspects: We categorize ABA schemes into different types and describe their structures as well as workflows, such that readers can gain a big picture and a clear view of different ABA schemes and their relations. This categorization serves as a guideline how to design and construct ABA schemes. We provide two examples to demonstrate how to construct ciphertext-policy attribute-based authentication (CP-ABA) schemes via two different approaches. Different from key-policy attribute-based authentication (KP-ABA) schemes, attribute keys generated in CP-ABA schemes are comparatively independent of relations among attributes. Thus compared with KP-ABA, CP-ABA extends the flexibility and usage scope of ABA schemes. We extend the core ABA schemes to hierarchical ABA (HABA) schemes by adding the property of hierarchy. Then we propose two different types of hierarchical structures, i.e., user related hierarchical ABA (U-HABA) and attribute related hierarchical ABA (A-HABA). According to these two hierarchical structures, an example is provided for each type to show how to use cryptographic primitives to build HABA schemes. All ABA schemes discussed above and proposed in this dissertation can be implemented to assist users to achieve anonymous authentication from their authenticators. Therefore, these schemes can offer more opportunities to protect users’ privacy, for example, in attribute-based access control (ABAC) and cloud-based services

The Mechanism of Na+/K+ Selectivity in Mammalian Voltage-Gated Sodium Channels Based on Molecular Dynamics Simulation

AbstractVoltage-gated sodium (Nav) channels and their Na+/K+ selectivity are of great importance in the mammalian neuronal signaling. According to mutational analysis, the Na+/K+ selectivity in mammalian Nav channels is mainly determined by the Lys and Asp/Glu residues located at the constriction site within the selectivity filter. Despite successful molecular dynamics simulations conducted on the prokaryotic Nav channels, the lack of Lys at the constriction site of prokaryotic Nav channels limits how much can be learned about the Na+/K+ selectivity in mammalian Nav channels. In this work, we modeled the mammalian Nav channel by mutating the key residues at the constriction site in a prokaryotic Nav channel (NavRh) to its mammalian counterpart. By simulating the mutant structure, we found that the Na+ preference in mammalian Nav channels is collaboratively achieved by the deselection from Lys and the selection from Asp/Glu within the constriction site

In vitro evaluation of a novel pH neutral calcium phosphosilicate bioactive glass that does not require preconditioning prior to use

It is well known that bioactive glasses can cause a significant increase in pH due to the rapid release of calcium and/or sodium ions. Consequently, preconditioning of the glass is usually required prior to surgery to negate the effect of this sudden release of ions. However, preconditioning for several days is far from ideal and also preconditioning is not practical for novel organic/inorganic sol-gel hybrids currently being developed since the organic phase will start to hydrolyze and dissolve. This study describes a bioactive glass that dissolves without causing a significant change in pH from physiologically optimal values and requires no preconditioning prior to use. The bioactivity of the pH neutral glass, hydroxyapatite formation, and cellular responses, are measured and compared directly with results from archetypal 45S5 and S70C30 bioactive glasses. A hydroxyapatite layer was found to rapidly form (within 1 day) on the surface of the pH neutral glass upon reacting with simulated body fluid. In addition, improved cell compatibility was observed compared with 45S5 and S70C30 glasses. Therefore, this pH neutral glass has significant potential for bone repair applications

Development of the Swimbladder Surfactant System and Biogenesis of Lysosome-Related Organelles Is Regulated by BLOS1 in Zebrafish

Hermansky-Pudlak syndrome (HPS) is a human autosomal recessive disorder that is characterized by oculocutaneous albinism and a deficiency of the platelet storage pool resulting from defective biogenesis of lysosome-related organelles (LROs). To date, 10 HPS genes have been identified, three of which belong to the octamer complex BLOC-1 (biogenesis of lysosome-related organelles complex 1). One subunit of the BLOC-1 complex, BLOS1, also participates in the BLOC-1-related complex (BORC). Due to lethality at the early embryo stage in BLOS1 knockout mice, the function of BLOS1 in the above two complexes and whether it has a novel function are unclear. Here, we generated three zebrafish mutant lines with a BLOC-1 deficiency, in which melanin and silver pigment formation was attenuated as a result of mutation of bloc1s1, bloc1s2, and dtnbp1a, suggesting that they function in the same complex. In addition, mutations of bloc1s1 and bloc1s2 caused an accumulation of clusters of lysosomal vesicles at the posterior part of the tectum, representing a BORC-specific function in zebrafish. Moreover, bloc1s1 is highly expressed in the swimbladder during postembryonic stages and is required for positively regulating the expression of the genes, which is known to govern surfactant production and lung development in mammals. Our study identified BLOS1 as a crucial regulator of the surfactant system. Thus, the zebrafish swimbladder might be an easy system to screen and study genetic modifiers that control surfactant production and homeostasis.</p

Flow Injection Chemiluminescent Immunoassay for Carcinoembryonic Antigen Using Boronic Immunoaffinity Column

A flow injection chemiluminescence immunoassay for rapid and sensitive detection of carcinoembryonic antigen (CEA) by using a phenylboronic acid-based immunoaffinity column as a glycoprotein collector was proposed in this paper. The column was prepared by coupling of 3-aminophenylboronic acid on the glass beads through a γ-glycidoxypropyltrimethoxysilane (GPMS) linkage. Based on an indirect competitive immunoreaction, the mixture of CEA sample and enzyme conjugated CEA antibody (HRP-anti-CEA) was incubated in advance, followed by direct injection to the column to capture free HRP-labeled CEA antibody in the column. The trapped HRP-labeled antibody was detected by flow inject chemiluminescence in the presence of luminol and hydrogen peroxide. The decreased chemiluminescent signal was proportional to the concentration of CEA in the range of 3.0–30.0 ng/mL with a correlation coefficient of 0.998. The column showed an acceptable reproducibility and stability and is potentially used for practical clinical detection of the serum CEA level