Search

Most of today's graph analytics systems model static graphs and do not support business use cases that require the ability to: (i) query the dynamic graph data for a time-evolving system, (ii) carry out investigations on its historical evolution, and (iii) audit past business decisions made with potentially stale or incorrect data. This position paper presents our vision for bi-temporal dynamic graph analytics, and sketches a design for a system that efficiently supports these requirements.

Function-as-a-Service (FaaS) has raised a growing interest in how to "tame" serverless to enable domain-specific use cases such as data-intensive applications and machine learning (ML), to name a few. Recently, several systems have been implemented for training ML models. Certainly, these research articles are significant steps in the correct direction. However, they do not completely answer the nagging question of when serverless ML training can be more cost-effective compared to traditional "serverful" computing. To help in this task, we propose MLLess, a FaaS-based ML training prototype built atop IBM Cloud Functions. To boost cost-efficiency, MLLess implements two key optimizations: a significance filter and a scale-in auto-tuner, and leverages them to specialize model training to the FaaS model. Our results certify that MLLess can be 15X faster than serverful ML systems [24] at a lower cost for ML models (such as sparse logistic regression and matrix factorization) that exhibit fast convergence.

With this position paper, we want to draw the attention of the community toward theoretical work and practical opportunities that have been overlooked so far regarding concepts, principles, and design knowledge for the user experience of Augmented and Mixed Reality content, I/O devices, interactions, applications, and systems. Despite considerable innovations in commercial products and research prototypes enabling Augmented and Mixed Reality worlds, how to design great user experiences in such worlds has been overall neglected at core, while the information and knowledge currently available to practitioners cover usability aspects mostly. Therefore, we advocate for theoretical foundations of the user experience in Augmented and Mixed Reality and propose several directions for more scientific research in this regard.

Logic Programming (LP) is considered to be relatively simple for non-programmers, and allows the developer to focus on developing facts and rules of a logical derivation, and not on algorithms. Secure multiparty computation (MPC) is a methodology that allows several parties to process private data collaboratively without revealing the data to any party. In this paper, we bring together the notions of MPC and LP, allowing users to write privacy-preserving applications in logic programming language.

Past research recognized that paper has many advantages over digital devices, such as affordability, tangibility, and flexibility. Paper, however, also lacks many of the functionalities available in digital technologies, such as access to online resources and the ability to display interactive content. Prior research therefore identified opportunities for fusing the two mediums into a combined interface. This work presents a literature review on this form of innovation - technologies that bridge the paper-digital gap. First, we synthesize an understanding of paper and its relationship with digital devices through the lens of past works. Then, we outline the state-of-the-art for paper-digital interfaces and highlight possible use cases and implementation approaches. Last, we discuss design considerations and future work for developing paper-digital interfaces. Our work may be beneficial for HCI researchers interested in the development of hybrid paper-digital interfaces, and more broadly in embedding digital functionalities in everyday objects.

“zones of flow (iii)’’ is a photo-sensitive installation that investigates the fluid and changing connections between people, sea and land. It addresses the instantaneous but sometimes asynchronous connectivity between things as they move, are placed or displaced in their environments. The artwork brings origami structures, electronics and audiovisual media together to create an immersive cogitative environment. A video projection depicting water surfaces is mapped onto a 2.5m paper-boat. Underneath, arrays of light sensors receive waves of information and send signals to small paper-boats scattered across the floor. As the flotilla of small paper-boats is activated it becomes a changing water surface where non-linear patterns emerge over time.

Automatically detecting the positions of key-points (e.g., facial key-points or finger key-points) in an image is an essential problem in many applications, such as driver's gaze detection and drowsiness detection in automated driving systems. With the recent advances of Deep Neural Networks (DNNs), Key-Points detection DNNs (KP-DNNs) have been increasingly employed for that purpose. Nevertheless, KP-DNN testing and validation have remained a challenging problem because KP-DNNs predict many independent key-points at the same time -- where each individual key-point may be critical in the targeted application -- and images can vary a great deal according to many factors. In this paper, we present an approach to automatically generate test data for KP-DNNs using many-objective search. In our experiments, focused on facial key-points detection DNNs developed for an industrial automotive application, we show that our approach can generate test suites to severely mispredict, on average, more than 93% of all key-points. In comparison, random search-based test data generation can only severely mispredict 41% of them. Many of these mispredictions, however, are not avoidable and should not therefore be considered failures. We also empirically compare state-of-the-art, many-objective search algorithms and their variants, tailored for test suite generation. Furthermore, we investigate and demonstrate how to learn specific conditions, based on image characteristics (e.g., head posture and skin color), that lead to severe mispredictions. Such conditions serve as a basis for risk analysis or DNN retraining., to appear in ISSTA 2021

The current paper provides preliminary statements of the panelists ahead of a panel discussion at the ACM SPAA 2021 conference on the topic: algorithm-friendly architecture versus architecture-friendly algorithms.

Fostering data literacy has largely been the domain of formal educational systems and export-oriented tools. Informal educational approaches, such as games or family activities, may overcome barriers to engaging with data by fostering data literacy through casual engagement. This work in progress explores how informal learning through creation and play with interactive data representations (physicalizations) can foster increased literacy and engagement with data. We outline a series of DIY paper charts using AR markers and everyday materials to help children interact and explore data through the creative process of making.

FT-Matrix is a typical vector-SIMD architecture that refines the cooperation between scalar and vector units. This approach is widely used in digital signal processing, high-performance computing, and artificial intelligence, among other fields. FT-Matrix currently adopts C vector extension as the main programming model, improving the utilization efficiency of SIMD by providing explicit vector extension API. Moreover, it is difficult to efficiently transplant parallel programs (OpenCL, CUDA) adopted by users. This paper proposes an automatic mapping and code optimization method for OpenCL kernels on FT-Matrix architecture. The proposed approach solves these challenges by means of work item coalescing, slicing and rotation, and instruction-level code optimization. Preliminary results show that our method can achieve high performance and good hardware utilization for OpenCL kernels, as well as decreasing the programming difficulty on FT-Matrix.

This is like an abstract to a paper, but it is more abstract. In fact, it is the introduction to something which is a not paper. The global Covid-19 pandemic of 2020 represented an inflection point for our post-post-modern world, a moment where our old normal was dramatically arrested. We are now in a state of comprehensive flux as ‘new normals’ emerge, begin to solidify, and may evolve into an—as yet undetermined—futures. This not paper is a facet and exploration of that flux as it relates to publication and conference culture, video conferencing systems, and how we both conduct, and share, research. You should read the whole of this abstract, but then you should take a step inside the not paper, it lives on the web over here https://designresearch.works/thisisnotapaper/

Writing research papers can be extremely challenging for new academic authors or entire scientific communities, with their own review and style guidelines like CHI. The impact of everything that we do as researchers is based on how we communicate it. Writing for CHI is a core skill to learn because it is hard to turn a research project into a successful CHI publication. This online edition of the successful CHI paper writing course offers hands-on advice and more in-depth tutorials on how to write papers with clarity, substance, and style. It is structured into four online units with a focus on writing CHI papers.

Despite the central importance of research papers to scientific progress, they can be difficult to read. Comprehension is often stymied when the information needed to understand a passage resides somewhere else: in another section, or in another paper. In this work, we envision how interfaces can bring definitions of technical terms and symbols to readers when and where they need them most. We introduce ScholarPhi, an augmented reading interface with four novel features: (1) tooltips that surface position-sensitive definitions from elsewhere in a paper, (2) a filter over the paper that "declutters" it to reveal how the term or symbol is used across the paper, (3) automatic equation diagrams that expose multiple definitions in parallel, and (4) an automatically generated glossary of important terms and symbols. A usability study showed that the tool helps researchers of all experience levels read papers. Furthermore, researchers were eager to have ScholarPhi's definitions available to support their everyday reading., 18 pages, 17 figures, 2 tables. To appear at the 2021 ACM CHI Conference on Human Factors in Computing Systems. For associated video, see https://youtu.be/yYcQf-Yq8B0. v2 changes: expanded discussion of design process and implementation; improved figure design. v3 changes: fixed typo in cell of Table 2; updated HEDDEx and Schwarz-Hearst accuracy in Section 5.3

Using machine learning (ML) services, both service customers and providers need to monitor complex contractual constraints of ML service that are strongly related to ML models and data. Therefore, establishing and monitoring comprehensive ML contracts are crucial in ML serving. This paper demonstrates a set of features and utilities of the QoA4ML framework for ML contracts.

Paper-based digital microfluidic biochips (P-DMFBs) have recently attracted great attention for its low-cost, in-place, and fast fabrication. This technology is essential for agile bio-assay development and deployment. P-DMFBs print electrodes and associate control lines on paper to control droplets and complete bio-assays. However, P-DMFBs have following issues: 1) control line interference may cause unwanted droplet movements, 2) avoiding control interference degrades assay performance and routability, 3) single layer fabrication limits routability, and 4) expensive ink cost limits low-cost benefits of P-DMFBs. To solve above issues, this work proposes an interference-free design methodology to design P-DMFBs with fast assay speed, better routability, and compact printing area. The contributions are as follows: First, we categorize control interference into soft and hard. Second, we identify only soft interference happens and propose to remove soft control interference constraints. Third, we propose an interference-free design methodology. Finally, we propose a cost-efficient ILP-based fluidic design module. Experimental results show proposed method outperforms prior work [14] across all bio-assay benchmarks. Compared to previous work, our cost-optimized designs use only 47%~78% area, gain 3.6%~16.2% more routing resources, and achieve 0.97x~1.5x shorter assay completion time. Our performance-optimized designs can accelerate assay speed by 1.05x~1.65x using 81%~96% printed area.

Paper-based digital microfluidic biochips (P-DMFBs) have emerged as a safe, low-cost, and fast-responsive platform for biochemical assays. In P-DMFB, droplet manipulations are executed by the electrowetting technology. In order to enable the electrowetting technology, pattern arrays of electrodes and control lines are coated on paper with a hydrophobic Teflon film and dielectric parylene-C film. Different from traditional DMFBs, the manufacturing of P-DMFBs is efficient and inexpensive since the electrodes and control lines are printed on photo paper with an inkjet printer. Active paper-based hybridized chip (APHC) is a type of P-DMFBs that has open and closed part. APHC enjoys more convenience than common P-DMFBs since it has no need to fabricate and maintain the micro gap between glass and paper chip, which requires highly delicate treatments. However, the pattern rails of electrodes in APHCs are denser than traditional P-DMFBs, which makes existing electrode routing algorithm fail in APHCs. To deal with the challenge in electrode routing of APHCs, this paper proposes a multi-commodity network flow-based routing algorithm, which simultaneously maximizes the routability and minimizes the total wire length of control lines. The multi-commodity flow model can utilize the pin-sharing between electrodes, which can improve routability and reduce the detour of routing lines. Moreover, the activation sequences of electrodes are considered, which guarantees that the bioassay will not be interfered with after pin-sharing. The proposed method achieves a 100% successful routing rate on real-life APHCs while other electrode routing method cannot solve the electrode routing of APHCs successfully.

We explored the paper augmentation technique where a tablet computer is placed under the paper to modify its content appearance and create the illusion of a static object appearing perceptually dynamic. Our approach is based on the Deformation Lamps (DL) technique commonly used with front projection. However, we applied it to rear projection, which removes the need for a fixed hardware setup or handling and wearing dedicated hardware. The key challenge was to ensure the appropriate mixing of light reflecting from the paper (to see what is printed on the paper) and the light passing though the paper (to see what the tablet screen is projecting) since (i) a tablet screen is a relatively weak light source when being used in rear projection and (ii) commonly, paper has high opacity so the content from one side is not visible on the other side. In order to achieve the appropriate mixing of light, we reduced the opacity of the paper by perforating it (thus allowing more light to pass through), and modified the algorithm for generating dynamic luminance animation by adding gamma and brightness correction. The outcomes provide a guide on how to modify the paper and the algorithm in order to achieve the DL effect with rear projection using a tablet computer.

Head-worn displays (HWDs) are an efficient and cost-effective means to guide users in order picking, a task that requires users to alternate their attention between the physical environment and the HWD's virtual image. After training 12 participants to expertise in picking, we compare three significantly different HWDs: Magic Leap One, Microsoft Hololens, and Google Glass Explorer Edition against paper pick lists (the industry standard). We find that previous findings on HWD benefits during such tasks are not reflected in all HWDs, suggesting that hardware design significantly influences efficacy. Based on experimental results and observations, we highlight challenges such as head weight, mounting, display clarity, field of view (FOV), and display position and discuss their possible effects on user comfort, user preference, task speed, and task accuracy.

Deploying context management systems at a global scale comes with a number of challenges and requirements. We argue that the hypermedia model and the agent-oriented paradigm help achieve the vision of Context-as-a-Service. We categorize challenges according to context processing concerns and use a scenario to exemplify how the proposed architectural principles help overcome the challenges.

To support the replication of "Instance of Interest Detection", which was presented at MM'19, this companion paper provides the details of the artifacts. Instance of Interest Detection (IOID) aims to provide instance-level user interest modeling for image semantic description. In this paper, we explain the file structure of the source code and publish the details of our IOID dataset, which can be used to retrain the model with custom parameters. We also provide a program for component analysis to help other researchers to do experiments with alternative models that are not included in our experiments. Moreover, we provide a demo program for using our model easily.

This companion paper supports the experimental replication of paper "Outfit Compatibility Prediction and Diagnosis with Multi-Layered Comparison Network", which is presented at ACM Multimedia 2019. We provide the software package for replicating the implementation of Multi-Layered Comparison Network (MCN), as well as the Polyvore-T dataset and baseline methods compared in the original paper. This paper contains the guides to reproduce the experiment results including outfit compatibility prediction, outfit diagnosis and automatic outfit revision.

Biological systems exhibit extraordinary levels of diversity. Embodied behaviours are the emergent property of many loosely-coupled parallel processes, from the microscopic level, e.g. materials, to more abstracted levels, e.g. organs and limbs. We summarise our investigations into using a synthetic methodology, i.e. an understanding-by-building approach, for designing the complex interactions of falling paper shapes. By studying how simple systems such as a falling paper shape behave, we can analyse the specific characteristics of the interaction between morphology and the environment, and how this leads to programmable non-trivial behaviours. We present current results and discuss the implications on the future of design in robotics.

This pictorial presents a design investigation at the intersection of paper and computer vision for tangible interfaces. Through this exploration, we uncovered various characteristics of paper that connect tangible interactions with concealing and revealing printed fiducial markers for detection-particularly through the affordances of paper craft and fiber. We illustrate a variety of paper structures that construct and deconstruct fiducial markers. We also demonstrate how these structures enable untethered functional physical inputs, such as push buttons and sliders. We showcase four proposals that extend these material insights into tangible interface applications, including interactive data physicalizations and functional paper prototypes. Furthermore, we continue the legacy of pictorials by exposing fabrication drawings for others to engage with this work at a more practical level.

Children and young people make extensive and varied use of digital and online technologies, yet issues about how their personal data may be collected and used by online platforms are rarely discussed. Additionally, despite calls to increase awareness, schools often do not cover these topics, instead focusing on online safety issues, such as being approached by strangers, cyberbullying or access to inappropriate content. This paper presents the results of one of the activities run as part of eleven workshops with 13-18 year olds, using co-designed activities to encourage critical thinking. Sets of 'data cards' were used to stimulate discussion about sharing and selling of personal data by online technology companies. Results highlight the desire and need for increased awareness about the potential uses of personal data amongst this age group, and the paper makes recommendations for embedding this into school curriculums as well as incorporating it into interaction design, to allow young people to make informed decisions about their online lives.

Nowadays, recommendation systems play an indispensable role in many fields, including e-commerce, finance, economy, and gaming. There is emerging research on publication venue recommendation systems to support researchers when submitting their scientific work. Several publishers such as IEEE, Springer, and Elsevier have implemented their submission recommendation systems only to help researchers choose appropriate conferences or journals for submission. In this work, we present a demo framework to construct an effective recommendation system for paper submission. With the input data (the title, the abstract, and the list of possible keywords) of a given manuscript, the system recommends the list of top relevant journals or conferences to authors. By using state-of-the-art techniques in natural language understanding, we combine the features extracted with other useful handcrafted features. We utilize deep learning models to build an efficient recommendation engine for the proposed system. Finally, we present the User Interface (UI) and the architecture of our paper submission recommendation system for later usage by researchers.

Storytelling is an important means for children to build literacy while sharing beliefs, values, and cultural norms. Our work investigates how augmented reality (AR) can fit into creative storytelling practices. We introduce Living Paper, a system for authoring AR narratives that span both digital and tangible media. Our augmented storybook prototype integrates animated AR characters from hand drawings with programmable LED lights that shine through the pages. Living Paper combines the flexibility of digital objects with the tangibility of physical cues to enable the creation of immersive and shareable stories.

Writing research papers can be extremely challenging specifically for scientific communities with their own review and style guidelines like CHI. The impact of everything that we do as researchers is based on how we communicate it. That is why writing for CHI is a core skill to learn because it is hard to turn a research project into a successful CHI publication. This fourth edition of the successful CHI paper writing course offers hands-on advice and more in-depth tutorials on how to write papers with clarity, substance, and style. It is structured into three 80-minute units with a focus on writing CHI papers.

As Michael Polanyi claims, "we know more than we can tell." As such, much of the author's tacit knowledge remains beyond the reader's grasp. However, by engaging with the text through embodied action, readers can gain their own tacit knowledge which may approximate or even expand upon the author's knowledge through the reader's own situated analysis. I present a situated analysis of a CHI paper, "Design for Collaborative Survival," to propose an embodied method of reading through situated action that enables communication and expansion of the knowledge beyond the text. I responded to each of the concepts in that paper in an active way to better approach the authors' tacit knowledge by developing my own. Through this activity I intend to stimulate discussion on how authors and readers can benefit from similar methods that take reading beyond the text.

When sketching, we must choose between paper (expressive ease, ruler and eraser) and computational assistance (parametric support, a digital record). PHysically Assisted SKetching provides both, with a pen that displays force constraints with which the sketcher interacts as they draw on paper. Phasking provides passive, "bound" constraints (like a ruler); or actively "brings" the sketcher along a commanded path (e.g., a curve), which they can violate for creative variation. The sketcher modulates constraint strength (control sharing) by bearing down on the pen-tip. Phasking requires untethered, graded force-feedback, achieved by modifying a ballpoint drive that generates force through rolling surface contact. To understand phasking's viability, we implemented its interaction concepts, related them to sketching tasks and measured device performance. We assessed the experience of 10 sketchers, who could understand, use and delight in phasking, and who valued its control-sharing and digital twinning for productivity, creative control and learning to draw.

Cybersecurity is now more important than ever, and so is education in this field. However, the cybersecurity domain encompasses an extensive set of concepts, which can be taught in different ways and contexts. To understand the state of the art of cybersecurity education and related research, we examine papers from the ACM SIGCSE and ACM ITiCSE conferences. From 2010 to 2019, a total of 1,748 papers were published at these conferences, and 71 of them focus on cybersecurity education. The papers discuss courses, tools, exercises, and teaching approaches. For each paper, we map the covered topics, teaching context, evaluation methods, impact, and the community of authors. We discovered that the technical topic areas are evenly covered (the most prominent being secure programming, network security, and offensive security), and human aspects, such as privacy and social engineering, are present as well. The interventions described in SIGCSE and ITiCSE papers predominantly focus on tertiary education in the USA. The subsequent evaluation mostly consists of collecting students' subjective perceptions via questionnaires. However, less than a third of the papers provide supplementary materials for other educators, and none of the authors published their dataset. Our results provide orientation in the area, a synthesis of trends, and implications for further research. Therefore, they are relevant for instructors, researchers, and anyone new in the field of cybersecurity education. The information we collected and synthesized from individual papers are organized in a publicly available dataset., Comment: ACM SIGCSE 2020 conference, 7 pages, 3 figures, 1 table

Exams are an integral assessment component in CS1 courses. However, little research exists concerning the impact of the exam format on student performance. To address this deficit, we conducted a year-long study to investigate student performance across two test formats, paper and IDE, with the goal of identifying any differences attributable to the format. Data was collected from the second and third exams over the course of two semesters, with five sections per semester. Each exam, whether paper or IDE, was constructed from a common list of concepts to ensure comparability across formats and sections. To assess the impact of exam format, we considered three points of concern. The first factor, grade received, provides a direct indication of student performance. Next, we examined the type of error committed by students (either syntax or logic) to determine influence of exam format (e.g., Does an IDE reduce the occurrence of syntax errors?). Finally, we considered exam completion rates to address concerns such as if the additional feedback might be overwhelming students in an already stressful environment (exam-taking) leading to lower completion rates.

We present Self-powered Paper INterfaces (SPIN) combining folding paper creases with triboelectric nanogenerator (TENG). Embedding TENG into paper creases, we developed a design editor and set of fabrication techniques to create paper-based interfaces that power sensors and actuators. Our SPIN design editor enables users to design their own crease pattern by changing parameters, embed power generating modules into the design, estimate total power generation, and export the files. Then following the fabrication instructions, users can cut and crease materials, and assemble them to build their own interfaces. We employ repetitive push-and-pull based embodied interactions with the mechanism of paper creases and demonstrate four application examples that show new expressive possibilities applying different scales of embodied interactions.

With the spread of electronic devices such as smartphones and tablets, the transfer of electronic information such as images and videos has become commonplace. To exchange electronic information using e-mail or social network services a sender needs to know the recipient's contact information. However, if the recipient is a newly-encountered person or an ad hoc partner, a significant number of them are reluctant to exchange contact details. To address this issue, we propose an interaction method for transferring electronic information by tearing a sheet of paper. This is an approach that utilizes the fact that when a piece of paper is torn into two pieces, the features of the torn edges of the two pieces match.

Verification techniques have been applied to the design of secure protocols for decades. However, relatively few efforts have been made to ensure that verified designs are also implemented securely. Static code verification techniques offer one way to bridge the verification gap between design and implementation, but require substantial expertise and manual labor to realize in practice. In this short paper, we propose black-box runtime verification as an alternative approach to extend the security guarantees of protocol designs to their implementations. Instead of instrumenting the complete protocol implementation, our approach only requires instrumenting common cryptographic libraries and network interfaces with a runtime monitor that is automatically synthesized from the protocol specification. This lightweight technique allows the effort for instrumentation to be shared among different protocols and ensures security with presumably minimal performance overhead.

In this companion paper, firstly, we briefly summarize the contributions of our main manuscript: Selective Deep Convolutional Features for Image Retrieval, published in ACM MultiMedia 2017. In addition, we provide detail instructions together with pre-configured MATLAB scripts which allow experiments to be executed and to reproduce the results reported in our main manuscript effortlessly. The source code is available at https://github.com/hnanhtuan/selectiveConvFeatures_ACMMM_reproducibility.

While there are several frameworks for CNN inference on mobile GPUs, they do not achieve real-time processing for the most of the CNNs that aim at reasonable accuracy since they all employ kernel-by-kernel execution model and do not effectively support INT8 quantization yet. In this paper, we reveal that mobile GPUs suffer from large kernel launch overhead unlike server GPUs, and then propose an on-device deep learning inference framework that can achieve real-time inference of CNNs on mobile GPUs by removing kernel launch overhead and by effectively exploiting INT8 quantization. We have evaluated the proposed framework with a state-of-the-art CNN based face detector (RetinaFace), and observed up to 2.01X of speedup compared to ARM Compute Library (ACL) on a commodity smartphone.

International audience; Chameleon is a software that combines computer vision feature-matching algorithms with an open database format to allow the incorporation of dynamic HTML5 interactive content over any type of document (e.g. PDF files, Power-Point documents, etc.) without modifying existing applications or the source document. It thus allows the provision and viewing of an enhanced version of a research paper with embedded interactive demonstrations or videos. It can also be used to perform live demonstrations of interaction techniques while giving a presentation without having to switch tools.

Current research in HCI with immigrants predominantly focuses on their practical needs and little attention is given to their cultural identities. As such, we aim to understand how newcomers reflect their cultural values within domestic settings. We explore this by provoking memories immigrants associate with physical spaces inside their homes. Hence, we built "Our Home Sketcher": a paper-based home drafting tool that allows novice users to design their homes by sketching and implicitly expressing their space, light, and privacy preferences. The collected drawings are then fed into a computer algorithm that produces 3D models of the sketched houses. This process of design acts as an artifact-driven storytelling for heritage sharing and rapport building within migrant communities. We engage 13 Middle Eastern newcomers in Canada with the tool and use Halbwachs' [44] theory of collective memory to frame how home sketching provokes former experiences. Our findings show a strong longing for reclaiming the past, narrating space-related oral history, and designing beyond current limitations.

We describe gtutr, an interactive feedback system designed to assist students in developing context-free grammars and corresponding ANTLR parsers. It intelligently controls students' access to a large test suite for the target language. After each submission, gtutr analyzes any failing tests and uses the Needleman-Wunsch sequence alignment algorithm over the tests' rule traces to identify and eliminate similar failing tests. This reduces the redundancy in the feedback given to the students and prevents them from being overloaded. gtutr uses simple gamification to encourage independent problem solving by students: it gives as little information as possible, and students need to prompt the system for further details such as failing tests similar to or different from already seen tests, or even for hints about rules that are the most likely to contain faults. It tracks the students' information requests and uses this to attenuate marks following an instructor-set penalty schema. The system also visualizes test outcomes over multiple submissions, helping students to keep track of the effects of their changes as their grammar development progresses.

Recent efforts have sought to design new smart contract programming languages that make writing blockchain programs safer. But programs on the blockchain are beholden only to the safety properties enforced by the blockchain itself: even the strictest language-only properties can be rendered moot on a language-oblivious blockchain due to inter-contract interactions. Consequently, while safer languages are a necessity, fully realizing their benefits necessitates a language-aware redesign of the blockchain itself.To this end, we propose that the blockchain be viewed as a typechain: a chain of typed programs --- not arbitrary blocks --- that are included iff they typecheck against the existing chain. Reaching consensus, or blockchecking, validates typechecking in a byzantine fault-tolerant manner. Safety properties traditionally enforced by a runtime are instead enforced by a type system with the aim of statically capturing smart contract correctness.To provide a robust level of safety, we contend that a typechain must minimally guarantee (1) asset linearity and liveness, (2) physical resource availability, including CPU and memory, (3) exceptionless execution, or no early termination, (4) protocol conformance, or adherence to some state machine, and (5) inter-contract safety, including reentrancy safety. Despite their exacting nature, typechains are extensible, allowing for rich libraries that extend the set of verified properties. We expand on typechain properties and present examples of real-world bugs they prevent.

Types indexed with extra type-level information are a powerful tool for statically enforcing domain-specific security properties. In many cases, this extra information is runtime-irrelevant, and so it can be completely erased at compile-time without degrading the performance of the compiled code. In practice, however, the added bureaucracy often disrupts the development process, as programmers must completely adhere to new complex constraints in order to even compile their code.In this work we present WRIT, a plugin for the GHC Haskell compiler that relaxes the type checking process in the presence of runtime-irrelevant constraints. In particular, WRIT can automatically coerce between runtime equivalent types, allowing users to run programs even in the presence of some classes of type errors. This allows us to gradually secure our code while still being able to compile at each step, separating security concerns from functional correctness.Moreover, we present a novel way to specify which types should be considered equivalent for the purpose of allowing the program to run, how ambiguity at the type level should be resolved and which constraints can be safely ignored and turned into warnings.

Botnets continue to be a threat to organizations, thus various machine learning-based botnet detectors have been proposed. However, the capability of such systems in detecting new or unseen botnets is crucial to ensure its robustness against the rapid evolution of botnets. Moreover, it prolongs the effectiveness of the system in detecting bots, avoiding frequent and time-consuming classifier re-training. We present BOTection, a privacy-preserving bot detection system that models the bot network flow behavior as a Markov Chain. The Markov Chain state transitions capture the bots' network behavior using high-level flow features as states, producing content-agnostic and encryption resilient behavioral features. These features are used to train a classifier to first detect flows produced by bots, and then identify their bot families. We evaluate our system on a dataset of over 7M malicious flows from 12 botnet families, showing its capability of detecting bots' network traffic with 99.78% F-measure and classifying it to a malware family with a 99.09% F-measure. Notably, due to the modeling of general bot network behavior by the Markov Chains, BOTection can detect traffic belonging to unseen bot families with an F-measure of 93.03% making it robust against malware evolution.

Game map interfaces provide an alternative perspective on the worlds players inhabit.compared to navigation applications popular in day-to-day life, game maps have different affordances to match players' situated goals. To contextualize and understand these differences and how they developed, we present a historical chronicle of game map interfaces. Starting from how games came to involve maps, we trace how maps are first separate from the game, becoming more and more integrated into play until converging in smartphone-style interfaces. We synthesize several game history texts with critical engagement with 123 key games to develop this map-focused chronicle, from which we highlight trends and opportunities for future map designs. Our work contributes a record of trends in game map interfaces that can serve as a source of reference and inspiration to game designers, digital physical-world map designers, and game scholars.

With the trend of adopting FPGAs in data centers, various FPGA acceleration platforms have been developed in recent years. Each server could incorporate one or many of these FPGAs at different compute hierarchy levels to match its workload intensity. FPGAs could either be used as IO-attached accelerators or be closely integrated with CPU as on-chip co-processors. For a more data-centric approach, an FPGA could be moved closer to the data medium (RAM or disk) and serve as a near-memory or near-storage accelerator. In this work, we present a quantitative model and in-depth analysis of application characteristics to determine when an application is more suitable for each acceleration hierarchy. We analyze 18 benchmarks from six domains and create a preliminary guideline for both application and hardware developers.

Digital signal processors (DSPs) offer cutting-edge energy efficiency for embedded multimedia computations, but writing high-performance DSP code requires expert tuning. Programmers need to work at a low level of abstraction, manually tailoring vendor-specific instructions to enable vector and VLIW parallelism. Diospyros is a synthesizing compiler that searches for optimal data layouts to enable efficient vectorized code on DSPs. Preliminary results show that for small fixed-size matrix multiply and 2D convolution, Diospyros achieves a 6.4--7.6x speedup compared to vendor-provided optimized kernels, and a 6.5--31.3x speedup over loop-based kernels optimized with the vendor's included compiler.

Developers of applications relying on cryptographic libraries can easily make mistakes in their use. Popular dynamic languages such as JavaScript make testing or verifying such applications particularly challenging. In this paper, we present our ongoing work toward a methodology for automatically checking security properties in JavaScript code. Our main idea is to attach security annotations to values that encode properties of interest. We illustrate our idea using examples and, as an initial step in our line of work, we present a formalization of security annotations in a statically typed lambda calculus. As next steps, we will translate our annotations to a dynamically typed formalization of JavaScript such as λJS and implement a runtime checked type extension using code instrumentation for full JavaScript.

Based on the concept of explanation sheets, we present an approach to make spreadsheets easier to understand and thus easier to use and maintain. We identify the notion of explanation soundness and show that explanation sheets which conform to simple rules of formula coverage provide sound explanations. We also present a practical evaluation of explanation sheets based on samples drawn from widely used spreadsheet corpora and based on a small user study.In addition to supporting spreadsheet understanding and maintenance, our work on explanation sheets has also uncovered several general principles of explanation languages that can help guide the design of explanations for other programming and domain-specific languages., This work is partially supported by the National Science Foundation under the grant CCF-1717300. Work financed by European Regional Development Fund through the Operational Programme for Competitiveness and Internationalization COMPETE 2020 Programme and by National Funds through the Portuguese funding agency FCT project POCI-01-0145-FEDER-016718 and NOVA LINCS UID/CEC/04516/2013, and by FLAD project 233/2014.

The recent Meltdown and Spectre attacks took the community by surprise. Rather than exploiting an incorrect implementation of the ISA, these attacks leverage the undocumented implementation-specific speculation behavior of high-performance microarchitectures to affect the extra-architectural state of the machine (e.g., caches).Inspired by these novel speculation-based attacks, we argue it is time to rethink the traditional ISA layers. Programmers and security professionals need a framework to reason about the effects of speculation and other microarchitectural performance optimizations. We propose judiciously extending the ISA to include the extra-architectural state so that an ISA implementation either completely squashes all system state changes caused by mis-speculated instructions or the potential changes are rigorously documented. We hope this new framework will give architects and security researchers tools to reduce the likelihood of future surprise vulnerabilities.

Keyphrases associated with research papers provide an effective way to find useful information in the large and growing scholarly digital collections. However, keyphrases are not always provided with the papers, but they need to be extracted from their content. In this paper, we explore keyphrase extraction formulated as sequence labeling and utilize the power of Conditional Random Fields in capturing label dependencies through a transition parameter matrix consisting of the transition probabilities from one label to the neighboring label. We aim at identifying the features that, by themselves or in combination with others, perform well in extracting the descriptive keyphrases for a paper. Specifically, we explore word embeddings as features along with traditional, document-specific features for keyphrase extraction. Our results on five datasets of research papers show that the word embeddings combined with document specific features achieve high performance and outperform strong baselines for this task.

Automatically matching reviewers to papers is a crucial step of the peer review process for venues receiving thousands of submissions. Unfortunately, common paper matching algorithms often construct matchings suffering from two critical problems: (1) the group of reviewers assigned to a paper do not collectively possess sufficient expertise, and (2) reviewer workloads are highly skewed. In this paper, we propose a novel local fairness formulation of paper matching that directly addresses both of these issues. Since optimizing our formulation is not always tractable, we introduce two new algorithms, FairIR and FairFlow, for computing fair matchings that approximately optimize the new formulation. FairIR solves a relaxation of the local fairness formulation and then employs a rounding technique to construct a valid matching that provably maximizes the objective and only compromises on fairness with respect to reviewer loads and papers by a small constant. In contrast, FairFlow is not provably guaranteed to produce fair matchings, however it can be 2x as efficient as FairIR and an order of magnitude faster than matching algorithms that directly optimize for fairness. Empirically, we demonstrate that both FairIR and FairFlow improve fairness over standard matching algorithms on real conference data. Moreover, in comparison to state-of-the-art matching algorithms that optimize for fairness only, FairIR achieves higher objective scores, FairFlow achieves competitive fairness, and both are capable of more evenly allocating reviewers., Appears at KDD 2019 Research Track, 20 pages