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  • An Empirical Investigation on the Challenges of Creating Custom Static Analysis Rules for Defect Localization
    arXiv.cs.SE Pub Date : 2020-11-25
    Diogo Silveira Mendonça; Marcos Kalinowski

    Background: Custom static analysis rules, i.e., rules specific for one or more applications, already were successfully used to perform corrective and preventive software maintenance. Their usage can reduce costs of verification and improve the reliability and security of applications. Pattern-Driven Maintenance (PDM) is a method designed to support the creation of those rules during software maintenance

    更新日期:2020-11-27
  • Nudge: Accelerating Overdue Pull Requests Towards Completion
    arXiv.cs.SE Pub Date : 2020-11-25
    Chandra Maddila; Sai Surya Upadrasta; Chetan Bansal; Nachiappan Nagappan; Georgios Gousios; Arie van Deursen

    Pull requests are a key part of the collaborative software development and code review process today. However, pull requests can also slow down the software development process when the reviewer(s) or the author do not actively engage with the pull request. In this work, we design an end-to-end service, Nudge, for accelerating overdue pull requests towards completion by reminding the author or the

    更新日期:2020-11-27
  • High-Level Description of Robot Architecture
    arXiv.cs.SE Pub Date : 2020-11-25
    Sabah Al-Fedaghi; Manar AlSaraf

    Architectural Description (AD) is the backbone that facilitates the implementation and validation of robotic systems. In general, current high-level ADs reflect great variation and lead to various difficulties, including mixing ADs with implementation issues. They lack the qualities of being systematic and coherent, as well as lacking technical-related forms (e.g., icons of faces, computer screens)

    更新日期:2020-11-27
  • Resonance: Replacing Software Constants with Context-Aware Models in Real-time Communication
    arXiv.cs.SE Pub Date : 2020-11-23
    Jayant Gupchup; Ashkan Aazami; Yaran Fan; Senja Filipi; Tom Finley; Scott Inglis; Marcus Asteborg; Luke Caroll; Rajan Chari; Markus Cozowicz; Vishak Gopal; Vinod Prakash; Sasikanth Bendapudi; Jack Gerrits; Eric Lau; Huazhou Liu; Marco Rossi; Dima Slobodianyk; Dmitri Birjukov; Matty Cooper; Nilesh Javar; Dmitriy Perednya; Sriram Srinivasan; John Langford; Ross Cutler; Johannes Gehrke

    Large software systems tune hundreds of 'constants' to optimize their runtime performance. These values are commonly derived through intuition, lab tests, or A/B tests. A 'one-size-fits-all' approach is often sub-optimal as the best value depends on runtime context. In this paper, we provide an experimental approach to replace constants with learned contextual functions for Skype - a widely used real-time

    更新日期:2020-11-27
  • Transforming Data Flow Diagrams for Privacy Compliance (Long Version)
    arXiv.cs.SE Pub Date : 2020-11-24
    Hanaa Alshareef; Sandro Stucki; Gerardo Schneider

    Recent regulations, such as the European General Data Protection Regulation (GDPR), put stringent constraints on the handling of personal data. Privacy, like security, is a non-functional property, yet most software design tools are focused on functional aspects, using for instance Data Flow Diagrams (DFDs). In previous work, a conceptual model was introduced where DFDs could be extended into so-called

    更新日期:2020-11-25
  • Code Search Intent Classification Using Weak Supervision
    arXiv.cs.SE Pub Date : 2020-11-24
    Nikitha Rao; Chetan Bansal; Joe Guan

    Developers use search for various tasks such as finding code, documentation, debugging information, etc. In particular, web search is heavily used by developers for finding code examples and snippets during the coding process. Recently, natural language based code search has been an active area of research. However, the lack of real-world large-scale datasets is a significant bottleneck. In this work

    更新日期:2020-11-25
  • A Family of Experiments on Test-Driven Development
    arXiv.cs.SE Pub Date : 2020-11-24
    Adrian Santos; Sira Vegas; Oscar Dieste; Fernando Uyaguari; Aysee Tosun; Davide Fucci; Burak Turhan; Giuseppe Scanniello; Simone Romano; Itir Karac; Marco Kuhrmann; Vladimir Mandic; Robert Ramac; Dietmar Pfahl; Christian Engblom; Jarno Kyykka; Kerli Rungi; Carolina Palomeque; Jaroslav Spisak; Markku Oivo; Natalia Juristo

    Context: Test-driven development (TDD) is an agile software development approach that has been widely claimed to improve software quality. However, the extent to which TDD improves quality appears to be largely dependent upon the characteristics of the study in which it is evaluated (e.g., the research method, participant type, programming environment, etc.). The particularities of each study make

    更新日期:2020-11-25
  • Provably-Robust Runtime Monitoring of Neuron Activation Patterns
    arXiv.cs.SE Pub Date : 2020-11-24
    Chih-Hong Cheng

    For deep neural networks (DNNs) to be used in safety-critical autonomous driving tasks, it is desirable to monitor in operation time if the input for the DNN is similar to the data used in DNN training. While recent results in monitoring DNN activation patterns provide a sound guarantee due to building an abstraction out of the training data set, reducing false positives due to slight input perturbation

    更新日期:2020-11-25
  • CAT: Change-focused Android GUI Testing
    arXiv.cs.SE Pub Date : 2020-11-23
    Chao Peng; Ajitha Rajan

    Android Apps are frequently updated, every couple of weeks, to keep up with changing user, hardware and business demands. Correctness of App updates is checked through extensive testing. Recent research has proposed tools for automated GUI event generation in Android Apps. These techniques, however, are not efficient at checking App updates as the generated GUI events do not prioritise updates, and

    更新日期:2020-11-25
  • Modeling Functional Similarity in Source Code with Graph-Based Siamese Networks
    arXiv.cs.SE Pub Date : 2020-11-23
    Nikita Mehrotra; Navdha Agarwal; Piyush Gupta; Saket Anand; David Lo; Rahul Purandare

    Code clones are duplicate code fragments that share (nearly) similar syntax or semantics. Code clone detection plays an important role in software maintenance, code refactoring, and reuse. A substantial amount of research has been conducted in the past to detect clones. A majority of these approaches use lexical and syntactic information to detect clones. However, only a few of them target semantic

    更新日期:2020-11-25
  • Modular Moose: A new generation software reverse engineering environment
    arXiv.cs.SE Pub Date : 2020-11-22
    Nicolas Anquetil; Anne Etien; Mahugnon H. Houekpetodji; Benoit Verhaeghe; Stéphane Ducasse; Clotilde Toullec; Fatiha Djareddir; Jerôme Sudich; Mustapha Derras

    Advanced reverse engineering tools are required to cope with the complexity of software systems and the specific requirements of numerous different tasks (re-architecturing, migration, evolution). Consequently, reverse engineering tools should adapt to a wide range of situations. Yet, because they require a large infrastructure investment, being able to reuse these tools is key. Moose is a reverse

    更新日期:2020-11-25
  • Dynamic Data Consistency Tests Using a CRUD Matrix as an Underlying Model
    arXiv.cs.SE Pub Date : 2020-11-21
    Miroslav Bures; Vaclav Rechtberger

    In testing of software and Internet of Things (IoT) systems, one of necessary type of tests has to verify the consistency of data that are processed and stored in the system. The Data Cycle Test technique can effectively do such tests. The goal of this technique is to verify that the system processes data entities in a system under test in a correct way and that they remain in a consistent state after

    更新日期:2020-11-25
  • Quality and Reliability Metrics for IoT Systems: A Consolidated View
    arXiv.cs.SE Pub Date : 2020-11-21
    Matej Klima; Vaclav Rechtberger; Miroslav Bures; Xavier Bellekens; Hanan Hindy; Bestoun S. Ahmed

    Quality and reliability metrics play an important role in the evaluation of the state of a system during the development and testing phases, and serve as tools to optimize the testing process or to define the exit or acceptance criteria of the system. This study provides a consolidated view on the available quality and reliability metrics applicable to Internet of Things (IoT) systems, as no comprehensive

    更新日期:2020-11-25
  • An Empirical Study on Failed Error Propagation in Java Programs with Real Faults
    arXiv.cs.SE Pub Date : 2020-11-21
    Gunel Jahangirova; David Clark; Mark Harman; Paolo Tonella

    During testing, developers can place oracles externally or internally with respect to a method. Given a faulty execution state, i.e., one that differs from the expected one, an oracle might be unable to expose the fault if it is placed at a program point with no access to the incorrect program state or where the program state is no longer corrupted. In such a case, the oracle is subject to failed error

    更新日期:2020-11-25
  • Revisiting Binary Code Similarity Analysis using Interpretable Feature Engineering and Lessons Learned
    arXiv.cs.SE Pub Date : 2020-11-21
    Dongkwan Kim; Eunsoo Kim; Sang Kil Cha; Sooel Son; Yongdae Kim

    Binary code similarity analysis (BCSA) is widely used for diverse security applications such as plagiarism detection, software license violation detection, and vulnerability discovery. Despite the surging research interest in BCSA, it is significantly challenging to perform new research in this field for several reasons. First, most existing approaches focus only on the end results, namely, increasing

    更新日期:2020-11-25
  • Experiences from Large-Scale Model Checking: Verification of a Vehicle Control System
    arXiv.cs.SE Pub Date : 2020-11-20
    Jonas Fritzsch; Tobias Schmid; Stefan Wagner

    In the age of autonomously driving vehicles, functionality and complexity of embedded systems are increasing tremendously. Safety aspects become more important and require such systems to operate with the highest possible level of fault tolerance. Simulation and systematic testing techniques have reached their limits in this regard. Here, formal verification as a long established technique can be an

    更新日期:2020-11-23
  • Hyperparameter Optimization for AST Differencing
    arXiv.cs.SE Pub Date : 2020-11-20
    Matias Martinez; Jean-Rémy Falleri; Martin Monperrus

    Computing the differences between two versions of the same program is an essential task for software development and software evolution research. AST differencing is the most advanced way of doing so, and an active research area. Yet, AST differencing still relies on default configurations or manual tweaking. In this paper we present a novel approach named DAT for hyperparameter optimization of AST

    更新日期:2020-11-23
  • ReAssert: Deep Learning for Assert Generation
    arXiv.cs.SE Pub Date : 2020-11-19
    Robert White; Jens Krinke

    The automated generation of test code can reduce the time and effort required to build software while increasing its correctness and robustness. In this paper, we present RE-ASSERT, an approach for the automated generation of JUnit test asserts which produces more accurate asserts than previous work with fewer constraints. This is achieved by targeting projects individually, using precise code-to-test

    更新日期:2020-11-21
  • NeVer 2.0: Learning, Verification and Repair of Deep Neural Networks
    arXiv.cs.SE Pub Date : 2020-11-18
    Dario Guidotti; Luca Pulina; Armando Tacchella

    In this work, we present an early prototype of NeVer 2.0, a new system for automated synthesis and analysis of deep neural networks.NeVer 2.0borrows its design philosophy from NeVer, the first package that integrated learning, automated verification and repair of (shallow) neural networks in a single tool. The goal of NeVer 2.0 is to provide a similar integration for deep networks by leveraging a selection

    更新日期:2020-11-21
  • DeepRepair: Style-Guided Repairing for DNNs in the Real-world Operational Environment
    arXiv.cs.SE Pub Date : 2020-11-19
    Bing Yu; Hua Qi; Qing Guo; Felix Juefei-Xu; Xiaofei Xie; Lei Ma; Jianjun Zhao

    Deep neural networks (DNNs) are being widely applied for various real-world applications across domains due to their high performance (e.g., high accuracy on image classification). Nevertheless, a well-trained DNN after deployment could oftentimes raise errors during practical use in the operational environment due to the mismatching between distributions of the training dataset and the potential unknown

    更新日期:2020-11-21
  • What is a Process Model Composed of? A Systematic Literature Review of Meta-Models in BPM
    arXiv.cs.SE Pub Date : 2020-11-18
    Greta Adamo; Chiara Ghidini; Chiara Di Francescomarino

    Business process modelling languages typically enable the representation of business process models by employing (graphical) symbols. These symbols can vary depending upon the verbosity of the language, the modelling paradigm, the focus of the language, and so on. To make explicit the different constructs and rules employed by a specific language, as well as bridge the gap across different languages

    更新日期:2020-11-19
  • Ginkgo -- A Math Library designed for Platform Portability
    arXiv.cs.SE Pub Date : 2020-11-17
    Terry Cojean; Yu-Hsiang "Mike" Tsai; Hartwig Anzt

    The first associations to software sustainability might be the existence of a continuous integration (CI) framework; the existence of a testing framework composed of unit tests, integration tests, and end-to-end tests; and also the existence of software documentation. However, when asking what is a common deathblow for a scientific software product, it is often the lack of platform and performance

    更新日期:2020-11-19
  • Towards evaluating and eliciting high-quality documentation for intelligent systems
    arXiv.cs.SE Pub Date : 2020-11-17
    David Piorkowski; Daniel González; John Richards; Stephanie Houde

    A vital component of trust and transparency in intelligent systems built on machine learning and artificial intelligence is the development of clear, understandable documentation. However, such systems are notorious for their complexity and opaqueness making quality documentation a non-trivial task. Furthermore, little is known about what makes such documentation "good." In this paper, we propose and

    更新日期:2020-11-18
  • One Stop Career Centre for People with Disabilities
    arXiv.cs.SE Pub Date : 2020-11-17
    Salhazan Nasution; Mohd Hanafi Mohd Yasin; Noraidah Sahari

    Career is a journey of life that made the field of profession or employment options as a way to live. Careers are basis to generate income to sustain the needs of everyday life. Disabled people also need a job and benefit from the job same as a normal person. However, the attitudes of some prejudice community against the disabled people to find a job. The purpose of this paper is to discuss about website

    更新日期:2020-11-18
  • Continuous Open Source License Compliance
    arXiv.cs.SE Pub Date : 2020-11-17
    Simon PhippsUP, Inria, DGD-I; Stefano ZacchiroliUP, Inria, DGD-I

    In this article we consider the role of policy and process in open source usage and propose in-workflow automation as the best path to promoting compliance.

    更新日期:2020-11-18
  • Gender Differences in Public Code Contributions: a 50-year Perspective
    arXiv.cs.SE Pub Date : 2020-11-17
    Stefano ZacchiroliUP, Inria, DGD-I

    Gender imbalance in information technology in general, and Free/Open Source Software specifically, is a well-known problem in the field. Still, little is known yet about the large-scale extent and long-term trends that underpin the phenomenon. We contribute to fill this gap by conducting a longitudinal study of the population of contributors to publicly available software source code. We analyze 1

    更新日期:2020-11-18
  • Automatically Repairing Programs Using Both Tests and Bug Reports
    arXiv.cs.SE Pub Date : 2020-11-16
    Manish Motwani; Yuriy Brun

    The success of automated program repair (APR) depends significantly on its ability to localize the defects it is repairing. For fault localization (FL), APR tools typically use either spectrum-based (SBFL) techniques that use test executions or information-retrieval-based (IRFL) techniques that use bug reports. These two approaches often complement each other, patching different defects. No existing

    更新日期:2020-11-18
  • Feasibility Study on CCTV-aware Routing and Navigation for Privacy, Anonymity, and Safety. Jyvaskyla -- Case-study of the First City to Benefit from CCTV-aware Technology. (Preprint)
    arXiv.cs.SE Pub Date : 2020-11-17
    Tuomo Lahtinen; Lauri Sintonen; Hannu Turtiainen; Andrei Costin

    In order to withstand the ever-increasing invasion of privacy by CCTV cameras and technologies, on par CCTV-aware solutions must exist that provide privacy, safety, and cybersecurity features. We argue that a first important step towards such CCTV-aware solutions must be a mapping system that provides both privacy and safety routing and navigation options. To the best of our knowledge, there are no

    更新日期:2020-11-18
  • ACCORDANT: A Domain Specific Model and DevOpsApproach for Big Data Analytics Architectures
    arXiv.cs.SE Pub Date : 2020-11-16
    Camilo Castellanos; Carlos A. Varela; Dario Correal

    Big data analytics (BDA) applications use machine learning algorithms to extract valuable insights from large, fast, and heterogeneous data sources. New software engineering challenges for BDA applications include ensuring performance levels of data-driven algorithms even in the presence of large data volume, velocity, and variety (3Vs). BDA software complexity frequently leads to delayed deployments

    更新日期:2020-11-18
  • Preventing Repeated Real World AI Failures by Cataloging Incidents: The AI Incident Database
    arXiv.cs.SE Pub Date : 2020-11-17
    Sean McGregor

    Mature industrial sectors (e.g., aviation) collect their real world failures in incident databases to inform safety improvements. Intelligent systems currently cause real world harms without a collective memory of their failings. As a result, companies repeatedly make the same mistakes in the design, development, and deployment of intelligent systems. A collection of intelligent system failures experienced

    更新日期:2020-11-18
  • GPURepair: Automated Repair of GPU Kernels
    arXiv.cs.SE Pub Date : 2020-11-17
    Saurabh Joshi; Gautam Muduganti

    This paper presents a tool for repairing errors in GPU kernels written in CUDA or OpenCL due to data races and barrier divergence. Our novel extension to prior work can also remove barriers that are deemed unnecessary for correctness. We implement these ideas in our tool called GPURepair, which uses GPUVerify as the verification oracle for GPU kernels. We also extend GPUVerify to support CUDA Cooperative

    更新日期:2020-11-18
  • Please Turn Your Cameras On: Remote Onboarding of Software Developers during a Pandemic
    arXiv.cs.SE Pub Date : 2020-11-16
    Paige Rodeghero; Thomas Zimmermann; Brian Houck; Denae Ford

    The COVID-19 pandemic has impacted the way that software development teams onboard new hires. Previously, most software developers worked in physical offices and new hires onboarded to their teams in the physical office, following a standard onboarding process. However, when companies transitioned employees to work from home due to the pandemic, there was little time to no time to develop new onboarding

    更新日期:2020-11-17
  • Neural Software Analysis
    arXiv.cs.SE Pub Date : 2020-11-16
    Michael Pradel; Satish Chandra

    Many software development problems can be addressed by program analysis tools, which traditionally are based on precise, logical reasoning and heuristics to ensure that the tools are practical. Recent work has shown tremendous success through an alternative way of creating developer tools, which we call neural software analysis. The key idea is to train a neural machine learning model on numerous code

    更新日期:2020-11-17
  • Determining the Intrinsic Structure of Public Software Development History
    arXiv.cs.SE Pub Date : 2020-11-16
    Antoine PietriDGD-I; Guillaume RousseauUP, DGD-I; Stefano ZacchiroliUP, DGD-I

    Background. Collaborative software development has produced a wealth of version control system (VCS) data that can now be analyzed in full. Little is known about the intrinsic structure of the entire corpus of publicly available VCS as an interconnected graph. Understanding its structure is needed to determine the best approach to analyze it in full and to avoid methodological pitfalls when doing so

    更新日期:2020-11-17
  • Environment Modeling for Adaptive Systems: A Systematic Literature Review
    arXiv.cs.SE Pub Date : 2020-11-16
    Fabian Kneer; Erik Kamsties; Klaus Schmid

    [Context & Motivation] Adaptive systems are an important research area. The dominant reason for adaptivity in systems are changes in the environment. Thus, it is an important question how to model the environment and how to determine the necessary information on this environment in the requirements engineering phase. [Question/ Problem] There is so far relatively little explicit study of the notion

    更新日期:2020-11-17
  • Dependency Solving Is Still Hard, but We Are Getting Better at It
    arXiv.cs.SE Pub Date : 2020-11-16
    Pietro AbateUP, Inria, DGD-I; Roberto Di CosmoUP, Inria, DGD-I; Georgios GousiosTU Delft; Stefano ZacchiroliUP, Inria, DGD-I

    Dependency solving is a hard (NP-complete) problem in all non-trivial component models due to either mutually incompatible versions of the same packages or explicitly declared package conflicts. As such, software upgrade planning needs to rely on highly specialized dependency solvers, lest falling into pitfalls such as incompleteness-a combination of package versions that satisfy dependency constraints

    更新日期:2020-11-17
  • Secure Vehicle Communications Using Proof-of-Nonce Blockchain
    arXiv.cs.SE Pub Date : 2020-11-16
    N. Y. Ahn; D. H. Lee

    This paper presents an autonomous driving that achieves physical layer security. Proposed vehicle communication is implemented based on Proof-of-Nonce (PoN) blockchain algorithm. PoN blockchain algorithm is a consensus algorithm that can be implemented in light weight. We propose a more secure vehicle communication scheme while achieving physical layer security by defecting PoN algorithm and secrecy

    更新日期:2020-11-17
  • The Software Heritage Graph Dataset: Large-scale Analysis of Public Software Development History
    arXiv.cs.SE Pub Date : 2020-11-16
    Antoine PietriDGD-I; Diomidis SpinellisAUEB; Stefano ZacchiroliUP, DGD-I

    Software Heritage is the largest existing public archive of software source code and accompanying development history. It spans more than five billion unique source code files and one billion unique commits , coming from more than 80 million software projects. These software artifacts were retrieved from major collaborative development platforms (e.g., GitHub, GitLab) and package repositories (e.g

    更新日期:2020-11-17
  • Forking Without Clicking: on How to Identify Software Repository Forks
    arXiv.cs.SE Pub Date : 2020-11-16
    Antoine PietriDGD-I; Guillaume RousseauUP, DGD-I; Stefano ZacchiroliUP, DGD-I

    The notion of software ''fork'' has been shifting over time from the (negative) phenomenon of community disagreements that result in the creation of separate development lines and ultimately software products, to the (positive) practice of using distributed version control system (VCS) repositories to collaboratively improve a single product without stepping on each others toes. In both cases the VCS

    更新日期:2020-11-17
  • A Probability Distribution and Location-aware ResNet Approach for QoS Prediction
    arXiv.cs.SE Pub Date : 2020-11-16
    Wenyan Zhang; Ling Xu; Meng Yan; Ziliang Wang; Chunlei Fu

    In recent years, the number of online services has grown rapidly, invoke the required services through the cloud platform has become the primary trend. How to help users choose and recommend high-quality services among huge amounts of unused services has become a hot issue in research. Among the existing QoS prediction methods, the collaborative filtering(CF) method can only learn low-dimensional linear

    更新日期:2020-11-17
  • Classification of Reverse-Engineered Class Diagram and Forward-Engineered Class Diagram using Machine Learning
    arXiv.cs.SE Pub Date : 2020-11-14
    Kaushil Mangaroliya; Het Patel

    UML Class diagram is very important to visualize the whole software we are working on and helps understand the whole system in the easiest way possible by showing the system classes, its attributes, methods, and relations with other objects. In the real world, there are two types of Class diagram engineers work with namely 1) Forward Engineered Class Diagram (FwCD) which are hand-made as part of the

    更新日期:2020-11-17
  • Software Protection as a Risk Analysis Process
    arXiv.cs.SE Pub Date : 2020-11-14
    Daniele Canavese; Leonardo Regano; Cataldo Basile; Bart Coppens; Bjorn De Sutter

    The last years have seen an increase of Man-at-the-End (MATE) attacks against software applications, both in number and severity. However, MATE software protections are dominated by fuzzy concepts and techniques, and security-through-obscurity is omnipresent in this field. In this paper, we present a rationale for adopting and standardizing the protection of software as a risk management process according

    更新日期:2020-11-17
  • Initiatives and Challenges of Using Gamification in Software Engineering: A Systematic Mapping
    arXiv.cs.SE Pub Date : 2020-11-13
    Daniel Porto; Gabriela Jesus; Fabiano Ferrari; Sandra Fabbri

    Context: Gamification is an emerging subject that has been applied in different areas, bringing contributions to different types of activities. Objective: This paper aims to characterize how gamification has been adopted in non-educational contexts of software engineering (SE) activities. Method: We performed a Systematic Mapping of the literature obtained from relevant databases of the area. The searches

    更新日期:2020-11-17
  • Large-Scale Manual Validation of Bug Fixing Commits: A Fine-grained Analysis of Tangling
    arXiv.cs.SE Pub Date : 2020-11-12
    Steffen Herbold; Alexander Trautsch; Benjamin Ledel; Alireza Aghamohammadi; Taher Ahmed Ghaleb; Kuljit Kaur Chahal; Tim Bossenmaier; Bhaveet Nagaria; Philip Makedonski; Matin Nili Ahmadabadi; Kristof Szabados; Helge Spieker; Matej Madeja; Nathaniel Hoy; Valentina Lenarduzzi; Shangwen Wang; Gema Rodríguez-Pérez; Ricardo Colomo-Palacios; Roberto Verdecchia; Paramvir Singh; Yihao Qin; Debasish Chakroborti;

    Context: Tangled commits are changes to software that address multiple concerns at once. For researchers interested in bugs, tangled commits mean that they actually study not only bugs, but also other concerns irrelevant for the study of bugs. Objective: We want to improve our understanding of the prevalence of tangling and the types of changes that are tangled within bug fixing commits. Methods: We

    更新日期:2020-11-13
  • Quality4.0 -- Transparent product quality supervision in the age of Industry 4.0
    arXiv.cs.SE Pub Date : 2020-11-12
    Jens Brandenburger; Christoph Schirm; Josef Melcher; Edgar Hancke; Marco Vannucci; Valentina Colla; Silvia Cateni; Rami Sellami; Sébastien Dupont; Annick Majchrowski; Asier Arteaga

    Progressive digitalization is changing the game of many industrial sectors. Focus-ing on product quality the main profitability driver of this so-called Industry 4.0 will be the horizontal integration of information over the complete supply chain. Therefore, the European RFCS project 'Quality4.0' aims in developing an adap-tive platform, which releases decisions on product quality and provides tailored

    更新日期:2020-11-13
  • Software Framework for Testing of Automated Driving Systems in a Dynamic Traffic Environment
    arXiv.cs.SE Pub Date : 2020-11-09
    Demin Nalic; Aleksa Pandurevic; Arno Eichberger; Branko Rogic

    Virtual testing of automated driving systems (ADS) become essential part of testing procedures for all automation levels. As ADS from automation level 3 and up are very complex virtual testing for such systems is inevitable. The complexity for these levels lies in the modelling and calculation demand for the virtual environment which consists of roads, traffic, static and dynamic objects and the modelling

    更新日期:2020-11-12
  • Documentation Generation as Information Visualization
    arXiv.cs.SE Pub Date : 2020-11-11
    Will Crichton

    Automatic documentation generation tools, or auto docs, are widely used to visualize information about APIs. However, each auto doc tool comes with its own unique representation of API information. In this paper, I use an information visualization analysis of auto docs to generate potential design principles for improving their usability. Developers use auto docs as a reference by looking up relevant

    更新日期:2020-11-12
  • Leveraging the Defects Life Cycle to Label Affected Versions and Defective Classes
    arXiv.cs.SE Pub Date : 2020-11-11
    Bailey Vandehei; Daniel Alencar da Costa; Davide Falessi

    Two recent studies explicitly recommend labeling defective classes in releases using the affected versions (AV) available in issue trackers. The aim our study is threefold: 1) to measure the proportion of defects for which the realistic method is usable, 2) to propose a method for retrieving the AVs of a defect, thus making the realistic approach usable when AVs are unavailable, 3) to compare the accuracy

    更新日期:2020-11-12
  • Wayback Machine: Capturing the evolutionary behaviour of the bug dependency graph in open-source software systems
    arXiv.cs.SE Pub Date : 2020-11-10
    Hadi Jahanshahi; Mucahit Cevik; José Navas-Sú; Ayşe Başar; Antonio González-Torres

    The issue tracking system (ITS) is a rich data source for data-driven decision making. Different characteristics of bugs, such as severity, priority, and time to fix may be misleading. Similarly, these values may be subjective, e.g., severity and priority values are assigned based on the intuition of a user or a developer rather than a structured and well-defined procedure. Hence, we explore the dependency

    更新日期:2020-11-12
  • How do Practitioners Perceive the Relevance of Requirements Engineering Research?
    arXiv.cs.SE Pub Date : 2020-11-10
    Xavier Franch; Daniel Mendez; Andreas Vogelsang; Rogardt Heldal; Eric Knauss; Marc Oriol; Guilherme H. Travassos; Jeffrey C. Carver; Thomas Zimmermann

    The relevance of Requirements Engineering (RE) research to practitioners is vital for a long-term dissemination of research results to everyday practice. Some authors have speculated about a mismatch between research and practice in the RE discipline. However, there is not much evidence to support or refute this perception. This paper presents the results of a study aimed at gathering evidence from

    更新日期:2020-11-12
  • AndroEvolve: Automated Android API Update with Data Flow Analysis and Variable Denormalization
    arXiv.cs.SE Pub Date : 2020-11-10
    Stefanus A. Haryono; Ferdian Thung; David Lo; Lingxiao Jiang; Julia Lawall; Hong Jin Kang; Lucas Serrano; Gilles Muller

    The Android operating system is frequently updated, with each version bringing a new set of APIs. New versions may involve API deprecation; Android apps using deprecated APIs need to be updated to ensure the apps' compatibility withold and new versions of Android. Updating deprecated APIs is a time-consuming endeavor. Hence, automating the updates of Android APIs can be beneficial for developers. CocciEvolve

    更新日期:2020-11-12
  • Characterization and Automatic Update of Deprecated Machine-Learning API Usages
    arXiv.cs.SE Pub Date : 2020-11-10
    Stefanus Agus Haryono; Ferdian Thung; David Lo; Julia Lawall; Lingxiao Jiang

    Due to the rise of AI applications, machine learning libraries have become far more accessible, with Python being the most common programming language to write them. Machine learning libraries tend to be updated periodically, which may deprecate existing APIs, making it necessary for developers to update their usages. However, updating usages of deprecated APIs are typically not a priority for developers

    更新日期:2020-11-12
  • Assessing the Feasibility of Web-Request Prediction Models on Mobile Platforms
    arXiv.cs.SE Pub Date : 2020-11-10
    Yixue Zhao; Siwei Yin; Adriana Sejfia; Marcelo Schmitt Laser; Haoyu Wang; Nenad Medvidovic

    Prefetching web pages is a well-studied solution to reduce network latency by predicting users' future actions based on their past behaviors. However, such techniques are largely unexplored on mobile platforms. Today's privacy regulations make it infeasible to explore prefetching with the usual strategy of amassing large amounts of data over long periods and constructing conventional, "large" prediction

    更新日期:2020-11-12
  • SeqMobile: A Sequence Based Efficient Android Malware Detection System Using RNN on Mobile Devices
    arXiv.cs.SE Pub Date : 2020-11-10
    Ruitao Feng; Jing Qiang Lim; Sen Chen; Shang-Wei Lin; Yang Liu

    With the proliferation of Android malware, the demand for an effective and efficient malware detection system is on the rise. The existing device-end learning based solutions tend to extract limited syntax features (e.g., permissions and API calls) to meet a certain time constraint of mobile devices. However, syntax features lack the semantics which can represent the potential malicious behaviors and

    更新日期:2020-11-12
  • Scoring Popularity in GitHub
    arXiv.cs.SE Pub Date : 2020-11-10
    Abduljaleel Al-Rubaye; Gita Sukthankar

    Popularity and engagement are the currencies of social media platforms, serving as powerful reinforcement mechanisms to keep users online. Social coding platforms such as GitHub serve a dual purpose: they are practical tools that facilitate asynchronous, distributed collaborations between software developers while also supporting passive social media style interactions. There are several mechanisms

    更新日期:2020-11-12
  • First Infrastructure and Experimentation in Echo-debugging
    arXiv.cs.SE Pub Date : 2020-11-09
    Thomas DupriezCNRS, CRIStAL, RMOD; Steven CostiouCNRS, CRIStAL, RMOD; Stéphane DucasseCNRS, CRIStAL, RMOD

    As applications get developed, bugs inevitably get introduced. Often, it is unclear why a given code change introduced a given bug. To find this causal relation and more effectively debug, developers can leverage the existence of a previous version of the code, without the bug. But traditional debug-ging tools are not designed for this type of work, making this operation tedious. In this article, we

    更新日期:2020-11-12
  • Learning Autocompletion from Real-World Datasets
    arXiv.cs.SE Pub Date : 2020-11-09
    Gareth Ari Aye; Seohyun Kim; Hongyu Li

    Code completion is a popular software development tool integrated into all major IDEs. Many neural language models have achieved promising results in completion suggestion prediction on synthetic benchmarks. However, a recent study When Code Completion Fails: a Case Study on Real-World Completions demonstrates that these results may not translate to improvements in real-world performance. To combat

    更新日期:2020-11-12
  • Software engineering for artificial intelligence and machine learning software: A systematic literature review
    arXiv.cs.SE Pub Date : 2020-11-07
    Elizamary Nascimento; Anh Nguyen-Duc; Ingrid Sundbø; Tayana Conte

    Artificial Intelligence (AI) or Machine Learning (ML) systems have been widely adopted as value propositions by companies in all industries in order to create or extend the services and products they offer. However, developing AI/ML systems has presented several engineering problems that are different from those that arise in, non-AI/ML software development. This study aims to investigate how software

    更新日期:2020-11-12
  • Synthesising Privacy by Design Knowledge Towards Explainable Internet of Things Application Designing in Healthcare
    arXiv.cs.SE Pub Date : 2020-11-07
    Lamya Alkhariji; Nada Alhirabi; Mansour Naser Alraja; Mahmoud Barhamgi; Omer Rana; Charith Perera

    Privacy by Design (PbD) is the most common approach followed by software developers who aim to reduce risks within their application designs, yet it remains commonplace for developers to retain little conceptual understanding of what is meant by privacy. A vision is to develop an intelligent privacy assistant to whom developers can easily ask questions in order to learn how to incorporate different

    更新日期:2020-11-12
  • ControlFlag: A Self-supervised Idiosyncratic Pattern Detection System for Software Control Structures
    arXiv.cs.SE Pub Date : 2020-11-06
    Niranjan Hasabnis; Justin Gottschlich

    Software debugging has been shown to utilize upwards of 50% of developers' time. Machine programming, the field concerned with the automation of software (and hardware) development, has recently made progress in both research and production-quality automated debugging systems. In this paper, we present ControlFlag, a system that detects possible idiosyncratic violations in software control structures

    更新日期:2020-11-12
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