Reporting usability defects-do reporters report what software developers need?

Reporting usability defects can be a challenging task, especially in convincing the software developers that the reported defect actually requires attention. Stronger evidence in the form of specific details is often needed. However, research to date in software defect reporting has not investigated the value of capturing different information based on defect type. We surveyed practitioners in both open source communities and industrial software organizations about their usability defect reporting practices to better understand information needs to address usability defect reporting issues. Our analysis of 147 responses show that reporters often provide observed result, expected result and steps to reproduce when describing usability defects, similar to the way other types of defects are reported. However, reporters rarely provide usability-related information. In fact, reporters ranked cause of the problem is the most difficult information to provide followed by usability principle, video recoding, UI event trace and title. Conversely, software developers consider cause of the problem as the most helpful information for them to fix usability defects. Our statistical analysis reveals a substantial gap between what reporters provide and what software developers need when fixing usability defects. We propose some remedies to resolve this gap.

Reporting usability defects: limitations of open source defect repositories and suggestions for improvement

Capturing good quality defect reports is critical for ensuring quick resolution of defects. While a range of studies into defect reporting exists, to date, very few focused on usability defect reporting issues can be found. To better understand issues specific to usability defect reporting, we carried out a survey of 56 contributors to the Mozilla and Google Chromium software projects spanning both usability defect reporters and developers. We discovered a range of limitations and key issues in current usability defect reporting tools and approaches identified as important by reporters and developers. In addition, we highlight opportunities to improve defect-reporting tools based on these open source communities' needs.

Quantum emission from defects in single-crystalline hexagonal boron nitride

Bulk hexagonal boron nitride (hBN) is a highly nonlinear natural hyperbolic material that attracts major attention in modern nanophotonics applications. However, studies of its optical properties in the visible part of the spectrum and quantum emitters hosted by bulk hBN have not been reported to date. In this work, we study the emission properties of hBN crystals in the red spectral range using sub-band-gap optical excitation. Quantum emission from defects is observed at room temperature and characterized in detail. Our results advance the use of hBN in quantum nanophotonics technologies and enhance our fundamental understanding of its optical properties.

Reduced glutathione biosynthesis in Drosophila melanogaster causes neuronal defects linked to copper deficiency.

Glutathione (GSH) is a tripeptide often considered to be the master antioxidant in cells. GSH plays an integral role in cellular redox regulation and is also known to have a role in mammalian copper homeostasis. In vitro evidence suggests that GSH is involved in copper uptake, sequestration and efflux. This study was undertaken to further investigate the roles that GSH plays in neuronal copper homeostasis in vivo, using the model organism Drosophila melanogaster. RNA interference-mediated knockdown of the Glutamate-cysteine ligase catalytic subunit gene (Gclc) that encodes the rate-limiting enzyme in GSH biosynthesis was utilised to genetically deplete GSH levels. When Gclc was knocked down in all neurons, this caused lethality, which was partially rescued by copper supplementation and was exacerbated by additional knockdown of the copper uptake transporter Ctr1A, or over-expression of the copper efflux transporter ATP7. Furthermore, when Gclc was knocked down in a subset of neuropeptide-producing cells, this resulted in adult progeny with unexpanded wings, a phenotype previously associated with copper dyshomeostasis. In these cells, Gclc suppression caused a decrease in axon branching, a phenotype further enhanced by ATP7 over-expression. Therefore, we conclude that GSH may play an important role in regulating neuronal copper levels and that reduction in GSH may lead to functional copper deficiency in neurons in vivo. We provide genetic evidence that glutathione (GSH) levels influence Cu content or distribution in vivo, in Drosophila neurons. GSH could be required for binding Cu imported by Ctr1A and distributing it to chaperones, such as Mtn, CCS and Atox1. Alternatively, GSH could modify the copper-binding and transport activities of Atox1 and the ATP7 efflux protein via glutathionylation of copper-binding cysteines.

Multilayer hybrid strategy for phishing email zero-day filtering

The cyber security threats from phishing emails have been growing buoyed by the capacity of their distributors to fine-tune their trickery and defeat previously known filtering techniques. The detection of novel phishing emails that had not appeared previously, also known as zero-day phishing emails, remains a particular challenge. This paper proposes a multilayer hybrid strategy (MHS) for zero-day filtering of phishing emails that appear during a separate time span by using training data collected previously during another time span. This strategy creates a large ensemble of classifiers and then applies a novel method for pruning the ensemble. The majority of known pruning algorithms belong to the following three categories: ranking based, clustering based, and optimization-based pruning. This paper introduces and investigates a multilayer hybrid pruning. Its application in MHS combines all three approaches in one scheme: ranking, clustering, and optimization. Furthermore, we carry out thorough empirical study of the performance of the MHS for the filtering of phishing emails. Our empirical study compares the performance of MHS strategy with other machine learning classifiers. The results of our empirical study demonstrate that MHS achieved the best outcomes and multilayer hybrid pruning performed better than other pruning techniques.