Miracle-dz/UniFAR-FTUs huggingface dataset:
How to mitigate the incident? an effective troubleshooting guide recommendation technique for online service systems

In recent years, more and more traditional shrink-wrapped software is provided as 7x24 online services. Incidents (events that lead to service disruptions or outages) could affect service availability and cause great financial loss. Therefore, mitigating the incidents is important and time critical. In practice, a document describing a mitigation process, called a troubleshooting guide (TSG), is usually used to reduce the Time To Mitigate (TTM). To investigate the usage of TSGs in real-world online services, we conduct the first empirical study on 18 real-world, large-scale online service systems in Microsoft. We analyze the distribution and characteristics of TSGs among all incident records in the past two years. According to our study, 27.2% incidents have TSG records and 36.2% of them occurred at least twice. Besides, on average developers spend around 36.3% of the entire mitigation time on locating the desired TSGs. Our study shows that incidents could occur repeatedly and TSGs could be reused to facilitate incident mitigation. Motivated by our empirical study, we propose an automated TSG recommendation approach, DeepRmd, by leveraging the textual similarity between incident description and its corresponding TSG using deep learning techniques. We evaluate the effectiveness of DeepRmd on 18 online service systems. The results show that DeepRmd can recommend the correct TSG as the Top 1 returned result for 80.3% incidents, which significantly outperforms two baseline approaches.
Enhancing developer interactions with programming screencasts through accurate code extraction

Programming screencasts have become a pervasive resource on the Internet, which is favoured by many developers for learning new programming skills. For developers, the source code in screencasts is valuable and important. However, the streaming nature of screencasts limits the choice that they have for interacting with the code. Many studies apply the Optical Character Recognition (OCR) technique to convert screen images into text, which can be easily searched and indexed. However, we observe that the noise in the screen images significantly affects the quality of OCRed code. In this paper, we develop a tool named psc2code, which has two components, denoising code extraction from screencasts and enhancing programming video interaction. Experiment results on 1142 programming screencasts from YouTube show psc2code can effectively identify frames containing valid code region with a F1-score of 0.88 and improve the quality of OCRed code by fixing 46% of the errors. We also conduct a user study to evaluate the applicability of psc2code in enhancing video interaction, which shows it helps participants learn the knowledge in tutorials more efficiently.
UIED: a hybrid tool for GUI element detection

Graphical User Interface (GUI) elements detection is critical for many GUI automation and GUI testing tasks. Acquiring the accurate positions and classes of GUI elements is also the very first step to conduct GUI reverse engineering or perform GUI testing. In this paper, we implement a User Iterface Element Detection (UIED), a toolkit designed to provide user with a simple and easy-to-use platform to achieve accurate GUI element detection. UIED integrates multiple detection methods including old-fashioned computer vision (CV) approaches and deep learning models to handle diverse and complicated GUI images. Besides, it equips with a novel customized GUI element detection methods to produce state-of-the-art detection results. Our tool enables the user to change and edit the detection result in an interactive dashboard. Finally, it exports the detected UI elements in the GUI image to design files that can be further edited in popular UI design tools such as Sketch and Photoshop. UIED is evaluated to be capable of accurate detection and useful for downstream works. Tool URL: http://uied.online Github Link: https://github.com/MulongXie/UIED
Past-sensitive pointer analysis for symbolic execution

We propose a novel fine-grained integration of pointer analysis with dynamic analysis, including dynamic symbolic execution. This is achieved via past-sensitive pointer analysis, an on-demand pointer analysis instantiated with an abstraction of the dynamic state on which it is invoked. We evaluate our technique in three application scenarios: chopped symbolic execution, symbolic pointer resolution, and write integrity testing. Our preliminary results show that the approach can have a significant impact in these scenarios, by effectively improving the precision of standard pointer analysis with only a modest performance overhead.
Identifying linked incidents in large-scale online service systems

In large-scale online service systems, incidents occur frequently due to a variety of causes, from updates of software and hardware to changes in operation environment. These incidents could significantly degrade system’s availability and customers’ satisfaction. Some incidents are linked because they are duplicate or inter-related. The linked incidents can greatly help on-call engineers find mitigation solutions and identify the root causes. In this work, we investigate the incidents and their links in a representative real-world incident management (IcM) system. Based on the identified indicators of linked incidents, we further propose LiDAR (Linked Incident identification with DAta-driven Representation), a deep learning based approach to incident linking. More specifically, we incorporate the textual description of incidents and structural information extracted from historical linked incidents to identify possible links among a large number of incidents. To show the effectiveness of our method, we apply our method to a real-world IcM system and find that our method outperforms other state-of-the-art methods.
Interval counterexamples for loop invariant learning

Loop invariant generation has long been a challenging problem. Black-box learning has recently emerged as a promising method for inferring loop invariants. However, the performance depends heavily on the quality of collected examples. In many cases, only after tens or even hundreds of constraint queries, can a feasible invariant be successfully inferred. To reduce the gigantic number of constraint queries and improve the performance of black-box learning, we introduce interval counterexamples into the learning framework. Each interval counterexample represents a set of counterexamples from constraint solvers. We propose three different generalization techniques to compute interval counterexamples. The existing decision tree algorithm is also improved to adapt interval counterexamples. We evaluate our techniques and report over 40% improvement on learning rounds and verification time over the state-of-the-art approach.
All your app links are belong to us: understanding the threats of instant apps based attacks

Android deep link is a URL that takes users to a specific page of a mobile app, enabling seamless user experience from a webpage to an app. Android app link, a new type of deep link introduced in Android 6.0, is claimed to offer more benefits, such as supporting instant apps and providing more secure verification to protect against hijacking attacks that previous deep links can not. However, we find that the app link is not as secure as claimed, because the verification process can be bypassed by exploiting instant apps. In this paper, we explore the weakness of the existing app link mechanism and propose three feasible hijacking attacks. Our findings show that even popular apps are subject to these attacks, such as Twitter, Whatsapp, Facebook Message. Our observation is confirmed by Google. To measure the severity of these vulnerabilities, we develop an automatic tool to detect vulnerable apps, and perform a large-scale empirical study on 400,000 Android apps. Experiment results suggest that app link hijacking vulnerabilities are prevalent in the ecosystem. Specifically, 27.1% apps are vulnerable to link hijacking with smart text selection (STS); 30.0% apps are vulnerable to link hijacking without STS, and all instant apps are vulnerable to instant app attack. We provide an in-depth understanding of the mechanisms behind these types of attacks. Furthermore, we propose the corresponding detection and defense methods that can successfully prevent the proposed hijackings for all the evaluated apps, thus raising the bar against the attacks on Android app links. Our insights and findings demonstrate the urgency to identify and prevent app link hijacking attacks.
Thinking aloud about confusing code: a qualitative investigation of program comprehension and atoms of confusion

Atoms of confusion are small patterns of code that have been empirically validated to be difficult to hand-evaluate by programmers. Previous research focused on defining and quantifying this phenomenon, but not on explaining or critiquing it. In this work, we address core omissions to the body of work on atoms of confusion, focusing on the ‘how’ and ‘why’ of programmer misunderstanding. We performed a think-aloud study in which we observed programmers, both professionals and students, as they hand-evaluated confusing code. We performed a qualitative analysis of the data and found several surprising results, which explain previous results, outline avenues of further research, and suggest improvements of the research methodology. A notable observation is that correct hand-evaluations do not imply understanding, and incorrect evaluations not misunderstanding. We believe this and other observations may be used to improve future studies and models of program comprehension. We argue that thinking of confusion as an atomic construct may pose challenges to formulating new candidates for atoms of confusion. Ultimately, we question whether hand-evaluation correctness is, itself, a sufficient instrument to study program comprehension.
JITO: a tool for just-in-time defect identification and localization

In software development and maintenance, defect localization is necessary for software quality assurance. Current defect localization techniques mainly rely on defect symptoms (e.g., bug reports or program spectrum) when the defect has been exposed. One challenge task is: can we locate buggy program prior to the appearance of the defect symptom. Such kind of localization is conducted at an early stage (e.g., when buggy program elements are being checked-in) which can be an early step of continuous quality control. In this paper, we propose a Just-In-Time defect identification and lOcalization tool, named JITO, which can help developers to locate defective lines at check-in time. In summary, JITO contains two phases: (i) identify if a new change is buggy and (ii) locate suspicious buggy code lines in the identified buggy changes. We implement JITO as a plugin in an integrated development environment (i.e., Intellij IDEA). When developers using our plugin, JITO loads the local Git repository to build the JIT defect identification model and localization model based on historical changes. After submitting a new change to the local repository, developers apply JITO to identify whether it is a buggy change. If a buggy change is identified, JITO leverages JIT defect localization model to locate its suspicious buggy lines and highlight them in Intellij IDEA. Experimental results show that JITO outperforms two baselines (i.e., random guess and a static bug finder (i.e., PMD)) by a substantial margin in terms of four ranking measures. Demo URL: https://youtu.be/tvnYs62FkEQ Plugin download: https://git.io/Jf5r1
Two centuries for an almost complete community turnover from native to non‐native species in a riverine ecosystem

Non‐native species introductions affect freshwater communities by changing community compositions, functional roles, trait occurrences and ecological niche spaces. Reconstructing such changes over long periods is difficult due to limited data availability. We collected information spanning 215 years on fish and selected macroinvertebrate groups (Mollusca and Crustacea) in the inner‐Florentine stretch of the Arno River (Italy) and associated water grid, to investigate temporal changes. We identified an almost complete turnover from native to non‐native fish (1800: 92% native; 2015: 94% non‐native species) and macroinvertebrate species (1800: 100% native; 2015: 70% non‐native species). Non‐native fish species were observed ~50 years earlier compared to macroinvertebrate species, indicating phased invasion processes. In contrast, α‐diversity of both communities increased significantly following a linear pattern. Separate analyses of changes in α‐diversities for native and non‐native species of both fish and macroinvertebrates were nonlinear. Functional richness and divergence of fish and macroinvertebrate communities decreased non‐significantly, as the loss of native species was compensated by non‐native species. Introductions of non‐native fish and macroinvertebrate species occurred outside the niche space of native species. Native and non‐native fish species exhibited greater overlap in niche space over time (62%–68%) and non‐native species eventually replaced native species. Native and non‐native macroinvertebrate niches overlapped to a lesser extent (15%–30%), with non‐natives occupying mostly unoccupied niche space. These temporal changes in niche spaces of both biotic groups are a direct response to the observed changes in α‐diversity and species turnover. These changes are potentially driven by deteriorations in hydromorphology as indicated by alterations in trait modalities. Additionally, we identified that angling played a considerable role for fish introductions. Our results support previous findings that the community turnover from native to non‐native species can be facilitated by, for example, deteriorating environmental conditions and that variations in communities are multifaceted requiring more indicators than single metrics.
Phytomelatonin: An overview of the importance and mediating functions of melatonin against environmental stresses.

Recently, melatonin has gained significant importance in plant research. The presence of melatonin in the plant kingdom has been known since 1995. It is a molecule that is conserved in a wide array of evolutionary distant organisms. Its functions and characteristics have been found to be similar in both plants and animals. The review focuses on the role of melatonin pertaining to physiological functions in higher plants. Melatonin regulates physiological functions regarding auxin activity, root, shoot, and explant growth, activates germination of seeds, promotes rhizogenesis (growth of adventitious and lateral roots), and holds up impelled leaf senescence. Melatonin is a natural bio-stimulant that creates resistance in field crops against various abiotic stress, including heat, chemical pollutants, cold, drought, salinity, and harmful ultra-violet radiation. The full potential of melatonin in regulating physiological functions in higher plants still needs to be explored by further research. This article is protected by copyright. All rights reserved.
Evaluation of Internal and Superficial Self-Healing of Cracks in Concrete with Crystalline Admixtures

Reinforced concrete structures are prone to cracking. The development of cementitious matrices with the capacity for self-healing soon after these cracks appear represents savings with inspections and repairs of the structures. Self-healing can be stimulated with the use of crystalline admixtures. Such materials easily react with water and increase the density of C-S-H (hydrated-calcium-silicate), forming insoluble deposits blocking existing pores and cracks. In this research, self-healing in concrete cracks was evaluated using three different crystalline admixtures, submitted to two and six wetting–drying cycles. The efficiency of self-healing was evaluated by optical microscopy and using the chloride diffusion test, which allowed calculating the predicted useful life of the concretes. The results highlight two important findings: (i) in optical microscopy, crystalline admixtures were not efficient in promoting self-healing on the surface of cracks in any of the studied concretes; (ii) the passage of chlorides by diffusion was lower for concretes with crystalline admixtures compared to the reference, showing better internal healing of these materials and, consequently, greater prediction of the concrete’s useful life.
Ceramides in Metabolism: Key Lipotoxic Players.

The global prevalence of metabolic diseases such as type 2 diabetes mellitus, steatohepatitis, myocardial infarction, and stroke has increased dramatically over the past two decades. These obesity-fueled disorders result, in part, from the aberrant accumulation of harmful lipid metabolites in tissues not suited for lipid storage (e.g., the liver, vasculature, heart, and pancreatic beta-cells). Among the numerous lipid subtypes that accumulate, sphingolipids such as ceramides are particularly impactful, as they elicit the selective insulin resistance, dyslipidemia, and ultimately cell death that underlie nearly all metabolic disorders. This review summarizes recent findings on the regulatory pathways controlling ceramide production, the molecular mechanisms linking the lipids to these discrete pathogenic events, and exciting attempts to develop therapeutics to reduce ceramide levels to combat metabolic disease. Expected final online publication date for the Annual Review of Physiology, Volume 83 is February 10, 2021. Please see http://www.annualreviews. org/page/journal/pubdates for revised estimates.
Effects of α-tubulin acetylation on microtubule structure and stability

Significance Microtubules are polymers of αβ-tubulin that play important roles in the cell. Regulation of their dynamics is critical for function and includes the posttranslational modification of tubulin. While most of tubulin modifications reside in the flexible C-terminal tail of tubulin, acetylation of α-tubulin on K40 is localized to the inside of the microtubule, within the so-called αK40 loop. Using high-resolution cryo-EM maps of acetylated and deacetylated microtubules, in conjunction with molecular-dynamics methods, we found that acetylation restricts the range of motion of the αK40 loop. In the deacetylated state, the loop extends deeper into the microtubule lumen and samples a greater number of conformations that we propose increase its accessibility to the acetylase and likely influence lateral contacts. Acetylation of K40 in α-tubulin is the sole posttranslational modification to mark the luminal surface of microtubules. It is still controversial whether its relationship with microtubule stabilization is correlative or causative. We have obtained high-resolution cryo-electron microscopy (cryo-EM) reconstructions of pure samples of αTAT1-acetylated and SIRT2-deacetylated microtubules to visualize the structural consequences of this modification and reveal its potential for influencing the larger assembly properties of microtubules. We modeled the conformational ensembles of the unmodified and acetylated states by using the experimental cryo-EM density as a structural restraint in molecular dynamics simulations. We found that acetylation alters the conformational landscape of the flexible loop that contains αK40. Modification of αK40 reduces the disorder of the loop and restricts the states that it samples. We propose that the change in conformational sampling that we describe, at a location very close to the lateral contacts site, is likely to affect microtubule stability and function.
Team-based primary health care for non-communicable diseases: complexities in South India

Abstract Chronic non-communicable diseases (NCDs), such as diabetes and cardiovascular diseases, have reached epidemic proportions worldwide. Health systems, especially those in low- and middle-income countries, such as India, struggle to deliver quality chronic care. A reorganization of healthcare service delivery is needed to strengthen care for chronic conditions. In this study, we evaluated the implementation of a package of tailored interventions to reorganize care, which were identified following a detailed analysis of gaps in delivering quality NCD care at the primary care level in India. Interventions included a redesign of the workflow at primary care clinics, a redistribution of tasks, the introduction of patient information records and the involvement of community health workers in the follow-up of patients with NCDs. An experimental case study design was chosen to study the implementation of the quality improvement measures. Three public primary care facilities in rural South India were selected. Qualitative methods were used to gain an in-depth understanding of the implementation process and outcomes of implementation. Observations, field notes and semi-structured interviews with staff at these facilities (n = 15) were thematically analysed to identify contextual factors that influenced implementation. Only one of the primary health centres implemented all components of the intervention by the end of 9 months. The main barriers to implementation were hierarchical arrangements that inhibited team-based care, the amount of time required for counselling and staff transfers. Team cohesion, additional staff and staff motivation seem to have facilitated implementation. This quality improvement research highlights the importance of building relational leadership to enable team-based care at primary care clinics in India. Redesigned organization of care and task redistribution is important solutions to deliver quality chronic care. However, implementing these will require capacity building of local primary care teams.
Harnessing the health systems strengthening potential of quality improvement using realist evaluation: an example from southern Tanzania

Abstract Quality improvement (QI) is a problem-solving approach in which stakeholders identify context-specific problems and create and implement strategies to address these. It is an approach that is increasingly used to support health system strengthening, which is widely promoted in Sub-Saharan Africa. However, few QI initiatives are sustained and implementation is poorly understood. Here, we propose realist evaluation to fill this gap, sharing an example from southern Tanzania. We use realist evaluation to generate insights around the mechanisms driving QI implementation. These insights can be harnessed to maximize capacity strengthening in QI and to support its operationalization, thus contributing to health systems strengthening. Realist evaluation begins by establishing an initial programme theory, which is presented here. We generated this through an elicitation approach, in which multiple sources (theoretical literature, a document review and previous project reports) were collated and analysed retroductively to generate hypotheses about how the QI intervention is expected to produce specific outcomes linked to implementation. These were organized by health systems building blocks to show how each block may be strengthened through QI processes. Our initial programme theory draws from empowerment theory and emphasizes the self-reinforcing nature of QI: the more it is implemented, the more improvements result, further empowering people to use it. We identified that opportunities that support skill- and confidence-strengthening are essential to optimizing QI, and thus, to maximizing health systems strengthening through QI. Realist evaluation can be used to generate rich implementation data for QI, showcasing how it can be supported in ‘real-world’ conditions for health systems strengthening.