Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact Analysis of Cross-Project Bugs on Software Ecosystems

Software projects are increasingly forming social-technical ecosystems within which individual projects rely on the infrastructures or functional components provided by other projects, leading to complex inter-dependencies. Through inter-project dependencies, a bug in an upstream project may have profound impact on a large number of downstream projects, resulting in cross-project bugs. This emerging type of bugs has brought new challenges in bug fixing due to their unclear influence on downstream projects. In this paper, we present an approach to estimating the impact of a cross-project bug within its ecosystem by identifying the affected downstream modules (classes/methods). Note that a downstream project that uses a buggy upstream function may not be affected as the usage does not satisfy the failure inducing preconditions. For a reported bug with the known root cause function and failure inducing preconditions, we first collect the candidate downstream modules that call the upstream function through an ecosystem-wide dependence analysis. Then, the paths to the call sites of the buggy upstream function are encoded as symbolic constraints. Solving the constraints, together with the failure inducing preconditions, identifies the affected downstream modules. Our evaluation of 31 existing upstream bugs on the scientific Python ecosystem containing 121 versions of 22 popular projects (with a total of 16 millions LOC) shows that the approach is highly effective: from the 25490 candidate downstream modules that invoke the buggy upstream functions, it identifies 1132 modules where the upstream bugs can be triggered, pruning 95.6% of the candidates. The technique has no false negatives and an average false positive rate of 7.9%. Only 49 downstream modules (out of the 1132 we found) were reported before to be affected.
Distance-Dependent Barcodes for Context-Aware Mobile Applications

This article introduces the novel concept of distance-dependent barcodes, which provide users with different data based on their scanning distance. These barcodes employ color blending as the key technique to achieve distance-dependence. A simple yet robust encoding scheme is devised accordingly to distinguish between near and far users. Through several experimental results, the proposed technique is shown to be effective (in terms of clear separation between near and far scanners), reliable (as to successful scans), and practical (it can be used in off-the-shelf smartphones). A few representative use cases are then presented to establish distance-dependent barcodes as an enabling technology for context-aware mobile applications. They include casual interactions with public displays, where the role of users is determined based on their distance from a screen, and augmented reality in retail, where distance-dependent barcodes provide information on available goods with different granularities. Finally, distance-dependent barcodes are shown to be user-friendly and effective through a user study.
Metagenome-Assembled Genome Sequences from an Anoxygenic Photosynthetic Consortium Involved in Sulfur Cycling

We sequenced the metagenome of an anoxygenic photosynthetic consortium originating from pond water and reconstructed four metagenome-assembled genomes. These genomes include Desulfocapsa, Paludibacter, Lamprocystis, and Rhodocyclaceae representatives and indicate the presence of genes for dissimilatory sulfate reduction and oxidation of reduced sulfur compounds. ABSTRACT We sequenced the metagenome of an anoxygenic photosynthetic consortium originating from pond water and reconstructed four metagenome-assembled genomes. These genomes include Desulfocapsa, Paludibacter, Lamprocystis, and Rhodocyclaceae representatives and indicate the presence of genes for dissimilatory sulfate reduction and oxidation of reduced sulfur compounds.
Rapid determination of n-6 and n-3 fatty acid ratios in cereal grains and forages by 1H NMR spectroscopy

Abstract: Herein we describe a new method to rapidly determine the n-6/n-3 fatty acid ratios in cereal grains and forages (hydroponically-grown cereal sprouts and haylage) using 1H nuclear magnetic resonance (NMR) spectroscopy. This NMR method was found to be consistent with more established but time-consuming gas chromatographic methods (R = 0.994).
Low-Overhead Deadlock Prediction

Multithreaded programs can have deadlocks, even after deployment, so users may want to run deadlock tools on deployed programs. However, current deadlock predictors such as MagicLock and UnDead have large overheads that make them impractical for end-user deployment and confine their use to development time. Such overhead stems from running an exponential-time algorithm on a large execution trace. In this paper, we present the first low-overhead deadlock predictor, called AirLock, that is fit for both in-house testing and deployed programs. AirLock maintains a small predictive lock reachability graph, searches the graph for cycles, and runs an exponential-time algorithm only for each cycle. This approach lets AirLock find the same deadlocks as MagicLock and UnDead but with much less overhead because the number of cycles is small in practice. Our experiments with real-world benchmarks show that the average time overhead of AirLock is 3.5%, which is three orders of magnitude less than that of MagicLock and UnDead. AirLock's low overhead makes it suitable for use with fuzz testers like AFL and on-the-fly after deployment.
GUI-focused Overviews of Mobile Development Videos

The need for mobile applications and mobile programming is increasing due to the continuous rise in the pervasiveness of mobile devices. Developers often refer to video programming tutorials to learn more about mobile programming topics. To find the right video to watch, developers typically skim over several videos, looking at their title, description, and video content in order to determine if they are relevant to their information needs. Unfortunately, the title and description do not always provide an accurate overview, and skimming over videos is time-consuming and can lead to missing important information. We propose a novel approach that locates and extracts the GUI screens showcased in a video tutorial, then selects and displays the most representative ones to provide a GUI-focused overview of the video. We believe this overview can be used by developers as an additional source of information for determining if a video contains the information they need. To evaluate our approach, we performed an empirical study on iOS and Android programming screencasts which investigates the accuracy of our automated GUI extraction. The results reveal that our approach can detect and extract GUI screens with an accuracy of 94%.
Scaling Open Source Communities: An Empirical Study of the Linux Kernel

Large-scale open source communities, such as the Linux kernel, have gone through decades of development, substantially growing in scale and complexity. In the traditional workflow, maintainers serve as “gatekeepers” for the subsystems that they maintain. As the number of patches and authors significantly increases, maintainers come under considerable pressure, which may hinder the operation and even the sustainability of the community. A few subsystems have begun to use new workflows to address these issues. However, it is unclear to what extent these new workflows are successful, or how to apply them. Therefore, we conduct an empirical study on the multiple-committer model (MCM) that has provoked extensive discussion in the Linux kernel community. We explore the effect of the model on the i915 subsystem with respect to four dimensions: pressure, latency, complexity, and quality assurance. We find that after this model was adopted, the burden of the i915 maintainers was significantly reduced. Also, the model scales well to allow more committers. After analyzing the online documents and interviewing the maintainers of i915, we propose that overloaded subsystems which have trustworthy candidate committers are suitable for adopting the model. We further suggest that the success of the model is closely related to a series of measures for risk mitigation–sufficient precommit testing, strict review process, and the use of tools to simplify work and reduce errors. We employ a network analysis approach to locate candidate committers for the target subsystems and validate this approach and contextual success factors through email interviews with their maintainers. To the best of our knowledge, this is the first study focusing on how to scale open source communities. We expect that our study will help the rapidly growing Linux kernel and other similar communities to adapt to changes and remain sustainable.
Augmenting Public Bookcases to Support Book Sharing

Public bookcases offer the opportunity to serendipitously discover books and to anonymously share books with others. The set of available books as well as the sharing patterns are highly dynamic, as anybody can freely take or donate books. This makes it difficult for users to see what is available or of interest to them. To support book sharing via public bookcases we developed a mobile AR application that highlights relevant books in the camera viewfinder and that facilitates searching for specific books. The application recognizes books via text and color features on the spine. In a lab study with 15 participants we evaluated our book recognition algorithm and found that it outperforms unaided visual search. We interviewed users of public bookcases and analyzed the bookcases’ setup and rate of change. A subsequent field evaluation of the AR application on nine public bookcases found a recognition accuracy of 80 % for 450 books under different conditions. The proposed approach provides the basis for effectively sharing books via public bookcases.
Increasing User Experience and Trust in Automated Vehicles via an Ambient Light Display

Today’s developments in the automotive industry are moving towards automated driving. At the highest levels, the driver becomes the passenger, which presents a new challenge for human-computer interaction. People not only have to trust in the automated system but are also confronted with increased complexity, as it is often not clear what the automated vehicle is about to do. An ambient light display is one way to give the driver a clearer picture of the car’s intentions and to keep complexity low. We have examined the impact on trust and user experience in more detail using two concepts for an ambient light display. One design provides information about detected potential conflicts in the current trajectory. The other design also highlights the future trajectory. We implemented both concepts as virtual light bars at the bottom of the screens. We evaluated them in a fixed-base driving simulator with 18 participants against each other and a baseline condition without additional information. Our scenario is a fully automated journey (SAE Level 5) through a German town. Although the two concepts do not differ much from each other, only the display showing both information – possible conflicts and future driving route – provided a clear added value for the users.
Complete Genome Sequences of Four Extensively Drug-Resistant Acinetobacter baumannii Isolates from Thailand

Here, we report the complete genome sequences of four clinical isolates of extensively drug-resistant Acinetobacter baumannii (XDRAB), isolated in Thailand. These results revealed multiple antimicrobial-resistant genes, each involving two sequence type 16 (ST16) isolates, ST2, and a novel sequence type isolate, ST1479. ABSTRACT Here, we report the complete genome sequences of four clinical isolates of extensively drug-resistant Acinetobacter baumannii (XDRAB), isolated in Thailand. These results revealed multiple antimicrobial-resistant genes, each involving two sequence type 16 (ST16) isolates, ST2, and a novel sequence type isolate, ST1479.
Extracting Daytime-Dependent Alertness Patterns from Mobile Game Data

Cognitive performance fluctuates throughout the day partly due to our “inner clock”. Systems that are aware of these fluctuations can adapt to their users’ momentary capacity and adjust task difficulty accordingly. Here, we evaluate the use of performance measures obtained from mobile game data to estimate players’ varying alertness. We developed a smartphone game that emulates three validated tasks for cognitive performance and conducted an in-the-wild study over two weeks with 30 participants to collect performance measures and subjective ground truth on alertness levels. Our results show that players’ performance can be explained by a generative model which is based on two established alertness-modulating processes, namely the homeostatic process and circadian alertness fluctuations. Our method can be used to implicitly model players’ alertness levels as a basis for cognition-aware applications.
Formalization and analysis of quantitative attributes of distributed systems

While there is not much discussion on the importance of formally describing and analyzing quantitative requirements in the process of software construction; in the paradigm of API-based software systems, it could be vital. Quantitative attributes can be thought of as attributes determining the Quality of Service - QoS provided by a software component published as a service. In this sense, they play a determinant role in classifying software artifacts according to specific needs stated as requirements.In this work, we present a research program consisting of the development of formal languages and tools to characterize and analyze the Quality of Service attributes of software components in the context of distributed systems. More specifically, our main motivational scenario lays on the execution of a service-oriented architecture.
Evolutionary hot-spots in Software Systems

We propose a methodology to study and visualize the evolution of the modular structure of a network of functional dependencies in a software system. Our method identifies periods of significant refactoring activities, also known as the evolutionary hot spots in software systems. Our approach is based on clustering design structure matrices of functional dependencies and Kleinberg’s method of identifying evolutionary hot-spots in dynamic networks. As a case study, we characterize the evolution of the modular structure of Octave over its entire life cycle.
Playing With Your Project Data in Scrum Retrospectives

Modern, agile software development methods rely on iterative work and improvement cycles to deliver their claimed benefits. In Scrum, the most popular agile method, process improvement is implemented through regular Retrospective meetings. In these meetings, team members reflect on the latest development iteration and decide on improvement actions. To identify potential issues, data on the completed iteration needs to be gathered. The Scrum method itself does not prescribe these steps in detail. However, Retrospective games, i.e. interactive group activities, have been proposed to encourage the sharing of experiences and problems. These activities mostly rely on the collected perceptions of team members. However, modern software development practices produce a large variety of digital project artifacts, e.g. commits in version control systems or test run results, which contain detailed information on performed teamwork. We propose taking advantage of this information in new, data-driven Retrospective activities, allowing teams to gain additional insights based on their own team-specific data.
MAGHair: A Wearable System to Create Unique Tactile Feedback by Stimulating Only the Body Hair

We present MAGHair, a novel wearable technique that provides subtle haptic sensation by stimulating the body hair without touching the skin. Our approach builds on previous research in magnetic hair stimulation and magnetic locomotion. We use magnetic cosmetics to augment the body hair, which can then be stimulated by a wearable apparatus that combines electromagnets and permanent magnets. We provide technical insights on the implementation of a fully functional wrist-worn form factor and early adaptations into other form factors. In addition, we provide a workflow for evaluating and characterizing the magnetic cosmetic recipes. Finally, we evaluate MAGHair, which demonstrated that users could detect the sensation of hair movement that they described as gentle and unique.
SMRL: A Metamorphic Security Testing Tool for Web Systems

We present a metamorphic testing tool that alleviates the oracle problem in security testing. The tool enables engineers to specify metamorphic relations that capture security properties of Web systems. It automatically tests Web systems to detect vulnerabilities based on those relations. We provide a domain-specific language accompanied by an Eclipse editor to facilitate the specification of metamorphic relations. The tool automatically collects the input data and transforms the metamorphic relations into executable Java code in order to automatically perform security testing based on the collected data. The tool has been successfully evaluated on a commercial system and a leading open source system (Jenkins). Demo video: https://youtu.be/9kx6u9LsGxs.
“I’d like an Explanation for That!”Exploring Reactions to Unexpected Autonomous Driving

Autonomous vehicles are complex systems that may behave in unexpected ways. From the drivers’ perspective, this can cause stress and lower trust and acceptance of autonomous driving. Prior work has shown that explanation of system behavior can mitigate these negative effects. Nevertheless, it remains unclear in which situations drivers actually need an explanation and what kind of interaction is relevant to them. Using thematic analysis of real-world experience reports, we first identified 17 situations in which a vehicle behaved unexpectedly. We then conducted a think-aloud study (N = 26) in a driving simulator to validate these situations and enrich them with qualitative insights about drivers’ need for explanation. We identified six categories to describe the main concerns and topics during unexpected driving behavior (emotion and evaluation, interpretation and reason, vehicle capability, interaction, future driving prediction and explanation request times). Based on these categories, we suggest design implications for autonomous vehicles, in particular related to collaboration insights, user mental models and explanation requests.
Refractive index sensor based on multimode interference in a twin-hole fiber

Abstract. We report a simple refractive index (RI) sensor based on a twin-hole fiber (THF). The THF is fused with the single-mode fiber to realize sensing by the multimode interference. The mode transmission characteristics in the THF are numerically investigated. In the sensing experiment, when the surrounding RI changes, the wavelength shift of the transmission spectrum shows approximate linearity in the low RI region and nonlinearity in the high RI region. When a THF with the length of 10 mm is used, the highest sensitivity can be up to 1351 nm / RIU in the RI range from 1.430 to 1.445. Moreover, the effect of the temperature on the transmission spectrum relative to the RI is much smaller when the external temperature changes from 30°C to 80°C.
Determining the Growth Limiting Conditions and Prevalence of Clostridium difficile in Foods

II ACKNOWLEDGEMENTS . III TABLE OF CONTENTS. IV LIST OF ABBREVIATIONS . VII LIST OF FIGURES . VIII LIST OF TABLES . IX CHAPTER 1: INTRODUCTION TO CLOSTRIDIUM DIFFICILE AND ITS ASSOCIATED DISEASE. 1 1.1 BACKGROUND AND PHYSICAL CHARACTERISTICS OF C. DIFFICILE . 1 1.2 C. DIFFICILE INFECTION . 2 1.2. 1 Acquisition . 2 1.2. 2 Infection and diagnosis. 3 1.2. 3 Incidence . 3 1.2. 4 Treatment . 4 1.3 VIRULENCE OF C. DIFFICILE. 4 1.3. 1 Large clostridial toxins. 4 1.3. 2 Pathogenicity locus . 5 1.3. 3 Binary toxin. 6 1.4 HYPERVIRULENT C. DIFFICILE AND COMMUNITY-ACQUIRED C. DIFFICILE INFECTION . 6 1.4. 1 Epidemic outbreak from strain NAP1/027 . 6 1.4. 2 Community-acquired C. difficile infection . 7 1.4. 3 Ribotype 078 and community-acquired C. difficile infection . 8 1.5 C. DIFFICILE IN ANIMALS . 9 1.5. 1 Prevalence . 9 1.5. 2 Hypervirulent strains . 10 1.6 C. DIFFICILE IN FOODS . 11 1.6. 1 North American meat products . 11 1.6. 2 European meat products . 14 1.6. 3 Other food products . 14 1.6. 4 Implications . 15 1.6. 5 Risk of foodborne transmission . 16 1.7 OBJECTIVES AND HYPOTHESES . 17 CHAPTER 2: DETERMINATION OF C. DIFFICILE GROWTH THRESHOLDS . 18 2.
The Effect of Social Capital on Tacit Knowledge-Sharing Intention: The Mediating Role of Employee Vigor

The role of social capital in predicting knowledge sharing has received considerable attention in research. However, very limited research has investigated the mechanisms mediating this relationship. To address this important gap in knowledge, the purpose of this study was to examine employee vigor as a psychological mechanism mediating the effect of social capital on tacit knowledge-sharing intention. Data collected from 209 employees in multiple industries in China were empirically tested by using structural equation modeling analysis. The results show that social capital positively affects emotional energy, which then positively influences the intention to share tacit knowledge. However, neither physical strength nor cognitive liveliness mediates the path through which social capital impacts tacit knowledge-sharing intention. Our research findings unpack the impact mechanism of social capital on tacit knowledge-sharing intention, and provide practical insights into how to use social capital to facilitate employees to share tacit knowledge in organizations.
Referenda as commitment devices – an experimental approach

This research note evaluates the claim that referenda can serve as useful commitment devices in international negotiations. More specifically, we relied on individual-level survey data to test the claim that governments can successfully “tie their hands” to policy choices by calling referenda on political issues. Our empirical analysis relied on original survey data collected in April 2019 in Belize. In so doing, we took advantage of an unusual political event. On 8 May (shortly after our survey), Belizean citizens participated in a countrywide plebiscite. During this vote, they decided to send their country’s territorial dispute with Guatemala for adjudication to the International Court of Justice. From a research perspective, this event allowed us to assess the effect of disregarded referendum results in a highly salient political environment. Our experimental analysis suggested that individuals do reprimand their governments for failing to implement a majority vote (a) even if this choice precipitates a person’s favored substantive outcome, and (b) irrespective of an individual’s preferred party.
Whole-Genome Sequencing of Multidrug-Resistant Campylobacter fetus subsp. fetus NWU_ED24, Isolated from a Bovine Sheath Wash Sample

Campylobacter fetus subsp. fetus is an opportunistic human pathogen that is frequently identified as a cause of intestinal infections as well as bloodstream infections. This bacterium is well known to cause spontaneous abortions in sheep and cows. The strain reported in this study was isolated from a preputial wash sample from a bull in South Africa. ABSTRACT Campylobacter fetus subsp. fetus is an opportunistic human pathogen that is frequently identified as a cause of intestinal infections as well as bloodstream infections. This bacterium is well known to cause spontaneous abortions in sheep and cows. The strain reported in this study was isolated from a preputial wash sample from a bull in South Africa.