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  • Patch Quality and Diversity of Invariant-Guided Search-Based Program Repair
    arXiv.cs.SE Pub Date : 2020-03-25
    Zhen Yu Ding

    Most automatic program repair techniques rely on test cases to specify correct program behavior. Due to test cases' frequently incomplete coverage of desired behavior, however, patches often overfit and fail to generalize to broader requirements. Moreover, in the absence of perfectly correct outputs, methods to ensure higher patch quality, such as merging together several patches or a human evaluating

    更新日期:2020-03-28
  • On-the-Fly Adaptation of Source Code Models using Meta-Learning
    arXiv.cs.SE Pub Date : 2020-03-26
    Disha Shrivastava; Hugo Larochelle; Daniel Tarlow

    The ability to adapt to unseen, local contexts is an important challenge that successful models of source code must overcome. One of the most popular approaches for the adaptation of such models is dynamic evaluation. With dynamic evaluation, when running a model on an unseen file, the model is updated immediately after having observed each token in that file. In this work, we propose instead to frame

    更新日期:2020-03-28
  • Empirical Study of Restarted and Flaky Builds on Travis CI
    arXiv.cs.SE Pub Date : 2020-03-26
    Thomas Durieux; Claire Le Goues; Michael Hilton; Rui Abreu

    Continuous Integration (CI) is a development practice where developers frequently integrate code into a common codebase. After the code is integrated, the CI server runs a test suite and other tools to produce a set of reports (e.g., output of linters and tests). If the result of a CI test run is unexpected, developers have the option to manually restart the build, re-running the same test suite on

    更新日期:2020-03-28
  • Applying the Isabelle Insider Framework to Airplane Security
    arXiv.cs.SE Pub Date : 2020-03-26
    Florian Kammüller; Manfred Kerber

    Avionics is one of the fields in which verification methods have been pioneered and brought a new level of reliability to systems used in safety critical environments. Tragedies, like the 2015 insider attack on a German airplane, in which all 150 people on board died, show that safety and security crucially depend not only on the well functioning of systems but also on the way how humans interact with

    更新日期:2020-03-28
  • Modern RESTful API DLs and frameworks for RESTful web services API schema modeling, documenting, visualizing
    arXiv.cs.SE Pub Date : 2018-11-12
    Kyrylo Malakhov; Oleksandr Kurgaev; Vitalii Velychko

    The given paper presents an overview of modern RESTful API description languages (belongs to interface description languages set) - OpenAPI, RAML, WADL, Slate - designed to provide a structured description of a RESTful web APIs (that is useful both to a human and for automated machine processing), with related RESTful web API modeling frameworks. We propose an example of the schema model of web API

    更新日期:2020-03-28
  • Whence to Learn? Transferring Knowledge in Configurable Systems using BEETLE
    arXiv.cs.SE Pub Date : 2019-11-01
    Rahul Krishna; Vivek Nair; Pooyan Jamshidi; Tim Menzies

    As software systems grow in complexity and the space of possible configurations increases exponentially, finding the near-optimal configuration of a software system becomes challenging. Recent approaches address this challenge by learning performance models based on a sample set of configurations. However, collecting enough sample configurations can be very expensive since each such sample requires

    更新日期:2020-03-28
  • Quality Assurance of Heterogeneous Applications: The SODALITE Approach
    arXiv.cs.SE Pub Date : 2020-03-25
    Indika Kumara; Giovanni Quattrocchi; Damian Tamburri; Willem-Jan Van Den Heuvel

    A key focus of the SODALITE project is to assure the quality and performance of the deployments of applications over heterogeneous Cloud and HPC environments. It offers a set of tools to detect and correct errors, smells, and bugs in the deployment models and their provisioning workflows, and a framework to monitor and refactor deployment model instances at runtime. This paper presents objectives,

    更新日期:2020-03-26
  • Causality-Guided Adaptive Interventional Debugging
    arXiv.cs.SE Pub Date : 2020-03-21
    Anna Fariha; Suman Nath; Alexandra Meliou

    Runtime nondeterminism is a fact of life in modern database applications. Previous research has shown that nondeterminism can cause applications to intermittently crash, become unresponsive, or experience data corruption. We propose Adaptive Interventional Debugging (AID) for debugging such intermittent failures. AID combines existing statistical debugging, causal analysis, fault injection, and group

    更新日期:2020-03-24
  • Software Effort Estimation from Use Case Diagrams Using Nonlinear Regression Analysis
    arXiv.cs.SE Pub Date : 2020-03-22
    Ali Bou Nassif; Manar AbuTaleb; Luiz Fernando Capretz

    Software effort estimation in the early stages of the software life cycle is one of the most essential and daunting tasks for project managers. In this research, a new model based on non-linear regression analysis is proposed to predict software effort from use case diagrams. It is concluded that, where software size is classified from small to very large, one linear or non-linear equation for effort

    更新日期:2020-03-24
  • Annotation-Based Static Analysis for Personal Data Protection
    arXiv.cs.SE Pub Date : 2020-03-22
    Kalle Hjerppe; Jukka Ruohonen; Ville Leppänen

    This paper elaborates the use of static source code analysis in the context of data protection. The topic is important for software engineering in order for software developers to improve the protection of personal data during software development. To this end, the paper proposes a design of annotating classes and functions that process personal data. The design serves two primary purposes: on one

    更新日期:2020-03-24
  • Rapid Reviews in Software Engineering
    arXiv.cs.SE Pub Date : 2020-03-22
    Bruno Cartaxo; Gustavo Pinto; Sergio Soares

    Integrating research evidence into practice is one of the main goals of Evidence-Based Software Engineering (EBSE). Secondary studies, one of the main EBSE products, are intended to summarize the best research evidence and make them easily consumable by practitioners. However, recent studies show that some secondary studies lack connections with software engineering practice. In this chapter, we present

    更新日期:2020-03-24
  • Fairway: SE Principles for Building Fairer Software
    arXiv.cs.SE Pub Date : 2020-03-23
    Joymallya Chakraborty; Suvodeep Majumdar; Zhe Wu; Tim Menziess

    Machine learning software is increasingly being used to make decisions that affect people's lives. But sometimes, the core part of this software (the learned model), behaves in a biased manner that gives undue advantages to a specific group of people (where those groups are determined by sex, race, etc.). This "algorithmic discrimination" in the AI software systems has become a matter of serious concern

    更新日期:2020-03-24
  • Building Very Small Test Suites (with Snap)
    arXiv.cs.SE Pub Date : 2019-05-14
    Jianfeng Chen; Xipeng Shen; Tim Menzies

    When test suites can be reduced in size by several orders of magnitude, then developers spend far less time in (a) analyzing what should be the required output; and (b) debugging failed tests. Also, such very small tests suites run faster (and so cost much less in cloud compute time). SNAP is a test suite generator that combines the Z3 theorem prover with a generation tactic that assumes code has much

    更新日期:2020-03-24
  • The Three Pillars of Machine Programming
    arXiv.cs.SE Pub Date : 2018-03-20
    Justin Gottschlich; Armando Solar-Lezama; Nesime Tatbul; Michael Carbin; Martin Rinard; Regina Barzilay; Saman Amarasinghe; Joshua B Tenenbaum; Tim Mattson

    In this position paper, we describe our vision of the future of machine programming through a categorical examination of three pillars of research. Those pillars are: (i) intention, (ii) invention, and(iii) adaptation. Intention emphasizes advancements in the human-to-computer and computer-to-machine-learning interfaces. Invention emphasizes the creation or refinement of algorithms or core hardware

    更新日期:2020-03-24
  • Vulnerabilities of Connectionist AI Applications: Evaluation and Defence
    arXiv.cs.SE Pub Date : 2020-03-18
    Christian Berghoff; Matthias Neu; Arndt von Twickel

    This article deals with the IT security of connectionist artificial intelligence (AI) applications, focusing on threats to integrity, one of the three IT security goals. Such threats are for instance most relevant in prominent AI computer vision applications. In order to present a holistic view on the IT security goal integrity, many additional aspects such as interpretability, robustness and documentation

    更新日期:2020-03-20
  • Self-Supervised Log Parsing
    arXiv.cs.SE Pub Date : 2020-03-17
    Sasho Nedelkoski; Jasmin Bogatinovski; Alexander Acker; Jorge Cardoso; Odej Kao

    Logs are extensively used during the development and maintenance of software systems. They collect runtime events and allow tracking of code execution, which enables a variety of critical tasks such as troubleshooting and fault detection. However, large-scale software systems generate massive volumes of semi-structured log records, posing a major challenge for automated analysis. Parsing semi-structured

    更新日期:2020-03-19
  • Big Code != Big Vocabulary: Open-Vocabulary Models for Source Code
    arXiv.cs.SE Pub Date : 2020-03-17
    Rafael-Michael Karampatsis; Hlib Babii; Romain Robbes; Charles Sutton; Andrea Janes

    Statistical language modeling techniques have successfully been applied to large source code corpora, yielding a variety of new software development tools, such as tools for code suggestion, improving readability, and API migration. A major issue with these techniques is that code introduces new vocabulary at a far higher rate than natural language, as new identifier names proliferate. Both large vocabularies

    更新日期:2020-03-19
  • Learning Nonlinear Loop Invariants with Gated Continuous Logic Networks
    arXiv.cs.SE Pub Date : 2020-03-17
    Jianan Yao; Gabriel Ryan; Justin Wong; Suman Jana; Ronghui Gu

    In many cases, verifying real-world programs requires inferring loop invariants with nonlinear constraints. This is especially true in programs that perform many numerical operations, such as control systems for avionics or industrial plants. Recently, data-driven methods for loop invariant inference have gained popularity, especially on linear loop invariants. However, applying data-driven inference

    更新日期:2020-03-19
  • An Exploratory Study of Bot Commits
    arXiv.cs.SE Pub Date : 2020-03-17
    Tapajit Dey; Bogdan Vasilescu; Audris Mockus

    Background: Bots help automate many of the tasks performed by software developers and are widely used to commit code in various social coding platforms. At present, it is not clear what types of activities these bots perform and understanding it may help design better bots, and find application areas which might benefit from bot adoption. Aim: We aim to categorize the Bot Commits by the type of change

    更新日期:2020-03-19
  • An Exploratory Study to Find Motives Behind Cross-platform Forks from Software Heritage Dataset
    arXiv.cs.SE Pub Date : 2020-03-17
    Avijit Bhattacharjee; Sristy Sumana Nath; Shurui Zhou; Debasish Chakroborti; Banani Roy; Chanchal K. Roy; Kevin Schneider

    The fork-based development mechanism provides the flexibility and the unified processes for software teams to collaborate easily in a distributed setting without too much coordination overhead.Currently, multiple social coding platforms support fork-based development, such as GitHub, GitLab, and Bitbucket. Although these different platforms virtually share the same features, they have different emphasis

    更新日期:2020-03-19
  • Improving the Robustness to Data Inconsistency between Training and Testing for Code Completion by Hierarchical Language Model
    arXiv.cs.SE Pub Date : 2020-03-18
    Yixiao Yang

    In the field of software engineering, applying language models to the token sequence of source code is the state-of-art approach to build a code recommendation system. The syntax tree of source code has hierarchical structures. Ignoring the characteristics of tree structures decreases the model performance. Current LSTM model handles sequential data. The performance of LSTM model will decrease sharply

    更新日期:2020-03-19
  • Automated synthesis of local time requirement for service composition
    arXiv.cs.SE Pub Date : 2020-03-18
    Étienne André; Tian Huat Tan; Manman Chen; Shuang Liu; Jun Sun; Yang Liu; Jin Song Dong

    Service composition aims at achieving a business goal by composing existing service-based applications or components. The response time of a service is crucial especially in time critical business environments, which is often stated as a clause in service level agreements between service providers and service users. To meet the guaranteed response time requirement of a composite service, it is important

    更新日期:2020-03-19
  • Model-Based User Interface Design for Generating E-Forms in the Context of an E-Government Project
    arXiv.cs.SE Pub Date : 2020-03-18
    Bedir Tekinerdogan; Namik Aktekin

    We report on our experiences in an e-government project for supporting the automatic generation of E-forms for services provided by local governments. The approach requires the integration of both the model-based user interface design (MBUID) and software product line engineering approaches. During the domain engineering activity the commonality and variability of product services is modeled using

    更新日期:2020-03-19
  • A Dataset and an Approach for Identity Resolution of 38 Million Author IDs extracted from 2B Git Commits
    arXiv.cs.SE Pub Date : 2020-03-18
    Tanner Fry; Tapajit Dey; Andrey Karnauch; Audris Mockus

    The data collected from open source projects provide means to model large software ecosystems, but often suffer from data quality issues, specifically, multiple author identification strings in code commits might actually be associated with one developer. While many methods have been proposed for addressing this problem, they are either heuristics requiring manual tweaking, or require too much calculation

    更新日期:2020-03-19
  • Constraint Solving with Deep Learning for Symbolic Execution
    arXiv.cs.SE Pub Date : 2020-03-18
    Junye Wen; Mujahid Khan; Meiru Che; Yan Yan; Guowei Yang

    Symbolic execution is a powerful systematic software analysis technique, but suffers from the high cost of constraint solving, which is the key supporting technology that affects the effectiveness of symbolic execution. Techniques like Green and GreenTrie reuse constraint solutions to speed up constraint solving for symbolic execution; however, these reuse techniques require syntactic/semantic equivalence

    更新日期:2020-03-19
  • Towards a More Complete Object-Orientation in Design Grammars
    arXiv.cs.SE Pub Date : 2017-12-19
    Samuel Vogel; Peter Arnold

    The ongoing digital transformation in industry applies to all product life cycle's stages. The design decisions and dimensioning carried out in the early conceptual design stages determine a huge part of the product's life cycle costs (LCC). The automation of the conceptual design phase promises therefore huge gains in terms of LCC. Design grammars encode design processes in production systems made

    更新日期:2020-03-19
  • Arguing Practical Significance in Software Engineering Using Bayesian Data Analysis
    arXiv.cs.SE Pub Date : 2018-09-26
    Richard Torkar; Robert Feldt; Carlo A. Furia; Lucas Gren; Per Lenberg; Francisco Gomes de Oliveira Neto

    This paper provides a case for using Bayesian data analysis (BDA) to make more informed claims regarding practical significance of software engineering research. We show that using BDA, here combined with cumulative prospect theory (CPT), is appropriate when a researcher or practitioner wants to make more explicit connections between statistical findings and practical significance in empirical software

    更新日期:2020-03-19
  • MSRBot: Using Bots to Answer Questions from Software Repositories
    arXiv.cs.SE Pub Date : 2019-05-16
    Ahmad Abdellatif; Khaled Badran; Emad Shihab

    Software repositories contain a plethora of useful information that can be used to enhance software projects. Prior work has leveraged repository data to improve many aspects of the software development process, such as, help extract requirement decisions, identify potentially defective code and improve maintenance and evolution. However, in many cases, practitioners are not able to fully benefit from

    更新日期:2020-03-19
  • The OpenUAV Swarm Simulation Testbed: a Collaborative Design Studio for Field Robotics
    arXiv.cs.SE Pub Date : 2019-10-02
    Harish Anand; Zhiang Chen; Sarah Bearman; Prasad Antervedi; Devin Keating; Stephen A. Rees; Jnaneshwar Das

    In this paper, we describe our OpenUAV multi-robot design studio that enables simulations to run as browser accessible Lubuntu desktop containers. Our simulation testbed, based on ROS, Gazebo, and PX4 flight stack has been developed to facilitate collaborative mission planning, and serve as a sandbox for vision-based problems, collision avoidance, and multi-robot coordination for Unmanned Aircraft

    更新日期:2020-03-19
  • Lazy Product Discovery in Huge Configuration Spaces
    arXiv.cs.SE Pub Date : 2020-03-16
    Michael Lienhardt; Ferruccio Damiani; Einar Broch Johnsen; Jacopo Mauro

    Highly-configurable software systems can have thousands of interdependent configuration options across different subsystems. In the resulting configuration space, discovering a valid product configuration for some selected options can be complex and error prone. The configuration space can be organized using a feature model, fragmented into smaller interdependent feature models reflecting the configuration

    更新日期:2020-03-18
  • Formal Scenario-Based Testing of Autonomous Vehicles: From Simulation to the Real World
    arXiv.cs.SE Pub Date : 2020-03-17
    Daniel J. Fremont; Edward Kim; Yash Vardhan Pant; Sanjit A. Seshia; Atul Acharya; Xantha Bruso; Paul Wells; Steve Lemke; Qiang Yu; Shalin Mehta

    We present a new approach to automated scenario-based testing of the safety of autonomous vehicles, especially those using advanced artificial intelligence-based components, spanning both simulation-based evaluation as well as testing in the real world. Our approach is based on formal methods, combining formal specification of scenarios and safety properties, algorithmic test case generation using

    更新日期:2020-03-18
  • Pressio: Enabling projection-based model reduction for large-scale nonlinear dynamical systems
    arXiv.cs.SE Pub Date : 2020-03-17
    Francesco Rizzi; Patrick J. Blonigan; Kevin T. Carlberg

    This work introduces Pressio, an open-source project aimed at enabling leading-edge projection-based reduced order models (ROMs) for large-scale nonlinear dynamical systems in science and engineering. Pressio provides model-reduction methods that can reduce both the number of spatial and temporal degrees of freedom for any dynamical system expressible as a system of parameterized ordinary differential

    更新日期:2020-03-18
  • Architectural Software Patterns for the Development of IoT Smart Applications
    arXiv.cs.SE Pub Date : 2020-03-10
    Fabrizio Borelli; Gabriela Biondi; Flávio Horita; Carlos Kamienski

    Software developers usually start coding an application with no formal architecture in mind and relying on intuition and experience instead of on well-known design patters. A different approach is recommended for the development of IoT smart applications due to its high complexity that combines sensors, actuators, communication technologies, and big data analytics, as well as its distributed nature

    更新日期:2020-03-18
  • AskCI Server: Collaborative and version controlled knowledge base
    arXiv.cs.SE Pub Date : 2020-03-12
    Vanessa Sochat

    AskCI server is a collaborative, open source documentation server that uses GitHub for automation and version control of shared knowledge. A programmatic application programming interface, friendly user interface, and organization of concepts into questions makes it versatile as a support or collaborative knowledge base.

    更新日期:2020-03-16
  • On the Role of Software Architecture in DevOps Transformation: An Industrial Case Study
    arXiv.cs.SE Pub Date : 2020-03-13
    Mojtaba Shahin; M. Ali Babar

    Development and Operations (DevOps), a particular type of Continuous Software Engineering, has become a popular Software System Engineering paradigm. Software architecture is critical in succeeding with DevOps. However, there is little evidence-based knowledge of how software systems are architected in the industry to enable and support DevOps. Since architectural decisions, along with their rationales

    更新日期:2020-03-16
  • High Quality Software for Planetary Science from Space
    arXiv.cs.SE Pub Date : 2020-03-13
    Francesco Lazzarotto; Gabriele Cremonese; Alice Lucchetti; Cristina Re; Emanuele Simioni; Maurizio Pajola; Pamela Cambianca; Giovanni Munaretto

    Planetary science space missions need high quality software ed efficient algorithms in order to extract innovative scientific results from flight data. Reliable and efficient software technologies are increasingly vital to improve and prolong the exploiting of the results of a mission, to allow the application of established algorithms and technologies also to future space missions and for the scientific

    更新日期:2020-03-16
  • Software Engineering Meets Deep Learning: A Literature Review
    arXiv.cs.SE Pub Date : 2019-09-25
    Fabio Ferreira; Luciana Lourdes Silva; Marco Tulio Valente

    Deep learning (DL) is being used nowadays in many traditional software engineering (SE) problems and tasks, such as software documentation, defect prediction, and software testing. However, since the renaissance of DL techniques is still very recent, we lack works that summarize and condense the most recent and relevant research conducted in the intersection of DL and SE. Therefore, in this paper we

    更新日期:2020-03-16
  • A Simulation Study of Bandit Algorithms to Address External Validity of Software Fault Prediction
    arXiv.cs.SE Pub Date : 2020-03-11
    Teruki Hayakawa. Masateru Tsunoda; Koji Toda; Keitaro Nakasai; Kenichi Matsumoto

    Various software fault prediction models and techniques for building algorithms have been proposed. Many studies have compared and evaluated them to identify the most effective ones. However, in most cases, such models and techniques do not have the best performance on every dataset. This is because there is diversity of software development datasets, and therefore, there is a risk that the selected

    更新日期:2020-03-12
  • Towards CRISP-ML(Q): A Machine Learning Process Model with Quality Assurance Methodology
    arXiv.cs.SE Pub Date : 2020-03-11
    Stefan Studer; Thanh Binh Bui; Christian Drescher; Alexander Hanuschkin; Ludwig Winkler; Steven Peters; Klaus-Robert Mueller

    We propose a process model for the development of machine learning applications. It guides machine learning practitioners and project organizations from industry and academia with a checklist of tasks that spans the complete project life-cycle, ranging from the very first idea to the continuous maintenance of any machine learning application. With each task, we propose quality assurance methodology

    更新日期:2020-03-12
  • On Tracking Java Methods with Git Mechanisms
    arXiv.cs.SE Pub Date : 2020-03-11
    Yoshiki Higo; Shinpei Hayashi; Shinji Kusumoto

    Method-level historical information is useful in research on mining software repositories such as fault-prone module detection or evolutionary coupling identification. An existing technique named Historage converts a Git repository of a Java project to a finer-grained one. In a finer-grained repository, each Java method exists as a single file. Treating Java methods as files has an advantage, which

    更新日期:2020-03-12
  • On the Feasibility of Automated Issue Type Prediction
    arXiv.cs.SE Pub Date : 2020-03-11
    Steffen Herbold; Alexander Trautsch; Fabian Trautsch

    Context: Issue tracking systems are used to track and describe tasks in the development process, e.g., requested feature improvements or reported bugs. However, past research has shown that the reported issue types often do not match the description of the issue. Objective: We want to understand the overall maturity of the state of the art of issue type prediction with the goal to predict if issues

    更新日期:2020-03-12
  • A Methodology for Automating Assurance Case Generation
    arXiv.cs.SE Pub Date : 2020-03-11
    Shreyas Ramakrishna; Charles Hartsell; Abhishek Dubey; Partha Pal; Gabor Karsai

    Safety Case has become an integral component for safety-certification in various Cyber Physical System domains including automotive, aviation, medical devices, and military. The certification processes for these systems are stringent and require robust safety assurance arguments and substantial evidence backing. Despite the strict requirements, current practices still rely on manual methods that are

    更新日期:2020-03-12
  • Research Directions for Developing and Operating Artificial Intelligence Models in Trustworthy Autonomous Systems
    arXiv.cs.SE Pub Date : 2020-03-11
    Silverio Martínez-Fernández; Xavier Franch; Andreas Jedlitschka; Marc Oriol; Adam Trendowicz

    Context: Autonomous Systems (ASs) are becoming increasingly pervasive in today's society. One reason lies in the emergence of sophisticated Artificial Intelligence (AI) solutions that boost the ability of ASs to self-adapt in increasingly complex and dynamic environments. Companies dealing with AI models in ASs face several problems, such as users' lack of trust in adverse or unknown conditions, and

    更新日期:2020-03-12
  • DLBricks: Composable Benchmark Generation to Reduce Deep Learning Benchmarking Effort on CPUs (Extended)
    arXiv.cs.SE Pub Date : 2019-11-18
    Cheng Li; Abdul Dakkak; Jinjun Xiong; Wen-mei Hwu

    The past few years have seen a surge of applying Deep Learning (DL) models for a wide array of tasks such as image classification, object detection, machine translation, etc. While DL models provide an opportunity to solve otherwise intractable tasks, their adoption relies on them being optimized to meet latency and resource requirements. Benchmarking is a key step in this process but has been hampered

    更新日期:2020-03-12
  • PUMiner: Mining Security Posts from Developer Question and Answer Websites with PU Learning
    arXiv.cs.SE Pub Date : 2020-03-08
    Triet H. M. Le; David Hin; Roland Croft; M. Ali Babar

    Security is an increasing concern in software development. Developer Question and Answer (Q&A) websites provide a large amount of security discussion. Existing studies have used human-defined rules to mine security discussions, but these works still miss many posts, which may lead to an incomplete analysis of the security practices reported on Q&A websites. Traditional supervised Machine Learning methods

    更新日期:2020-03-10
  • SpellBound: Defending Against Package Typosquatting
    arXiv.cs.SE Pub Date : 2020-03-06
    Matthew Taylor; Ruturaj K. Vaidya; Drew Davidson; Lorenzo De Carli; Vaibhav Rastogi

    Package managers for software repositories based on a single programming language are very common. Examples include npm (JavaScript), and PyPI (Python). These tools encourage code reuse, making it trivial for developers to import external packages. Unfortunately, repositories' size and the ease with which packages can be published facilitates the practice of typosquatting: the uploading of a package

    更新日期:2020-03-10
  • Continuous Experimentation for Automotive Software on the Example of a Heavy Commercial Vehicle in Daily Operation
    arXiv.cs.SE Pub Date : 2020-03-08
    Federico Giaimo; Christian Berger

    As the automotive industry focuses their efforts more and more towards the software end of the spectrum, techniques to deliver new software value at a fast pace are needed. Continuous Experimentation, a practice coming from the web-based systems world, is one of such techniques. It enables researchers and developers to use real-world data to verify their hypothesis and steer the software evolution

    更新日期:2020-03-10
  • Flexible numerical optimization with ensmallen
    arXiv.cs.SE Pub Date : 2020-03-09
    Ryan R. Curtin; Marcus Edel; Rahul Ganesh Prabhu; Suryoday Basak; Zhihao Lou; Conrad Sanderson

    This report provides an introduction to the ensmallen numerical optimization library, as well as a deep dive into the technical details of how it works. The library provides a fast and flexible C++ framework for mathematical optimization of arbitrary user-supplied functions. A large set of pre-built optimizers is provided, including many variants of Stochastic Gradient Descent and Quasi-Newton optimizers

    更新日期:2020-03-10
  • Continuous Experimentation and the Cyber-Physical Systems challenge. An overview in literature and the industrial perspective
    arXiv.cs.SE Pub Date : 2020-03-08
    Federico Giaimo; Hugo Andrade; Christian Berger

    Context: New software development patterns are emerging aiming at accelerating the process of delivering value. One is Continuous Experimentation, which allows to systematically deploy and run instrumented software variants during development phase in order to collect data from the field of application. While currently this practice is used on a daily basis on web-based systems, technical difficulties

    更新日期:2020-03-10
  • Software-testing education: A systematic literature mapping
    arXiv.cs.SE Pub Date : 2020-03-08
    Vahid Garousi; Austen Rainer; Per Lauvås jr; Andrea Arcuri

    Context: With the rising complexity and scale of software systems, there is an ever-increasing demand for sophisticated and cost-effective software testing. To meet such a demand, there is a need for a highly-skilled software testing work-force (test engineers) in the industry. To address that need, many university educators worldwide have included software-testing education in their software engineering

    更新日期:2020-03-10
  • The Cost and Benefits of Static Analysis During Development
    arXiv.cs.SE Pub Date : 2020-03-06
    William R. Nichols Jr

    Without quantitative data, deciding whether and how to use static analysis in a development workflow is a matter of expert opinion and guesswork rather than an engineering trade-off. Moreover, relevant data collected under real-world conditions is scarce. Important but unknown quantitative parameters include, but are not limited to, the effort to apply the techniques, the effectiveness of removing

    更新日期:2020-03-09
  • Detecting and Characterizing Bots that Commit Code
    arXiv.cs.SE Pub Date : 2020-03-02
    Tapajit Dey; Sara Mousavi; Eduardo Ponce; Tanner Fry; Bogdan Vasilescu; Anna Filippova; Audris Mockus

    Background: Some developer activity traditionally performed manually, such as making code commits, opening, managing, or closing issues is increasingly subject to automation in many OSS projects. Specifically, such activity is often performed by tools that react to events or run at specific times. We refer to such automation tools as bots and, in many software mining scenarios related to developer

    更新日期:2020-03-09
  • Automated Repair of Resource Leaks in Android Applications
    arXiv.cs.SE Pub Date : 2020-03-06
    Bhargav Nagaraja Bhatt; Carlo A. Furia

    Resource leaks -- a program does not release resources it previously acquired -- are a common kind of bug in Android applications. Even with the help of existing techniques to automatically detect leaks, writing a leak-free program remains tricky. One of the reasons is Android's event-driven programming model, which complicates the understanding of an application's overall control flow. In this paper

    更新日期:2020-03-09
  • Constructing Object Groups Corresponding to Concepts for Recovery of a Summarized Sequence Diagram
    arXiv.cs.SE Pub Date : 2020-03-06
    Kunihiro Noda; Takashi Kobayashi; Kiyoshi Agusa

    Comprehending the behavior of an object-oriented system solely from its source code is troublesome, owing to its dynamism. To aid comprehension, visualizing program behavior through reverse-engineered sequence diagrams from execution traces is a promising approach. However, because of the massiveness of traces, recovered diagrams tend to become very large, causing scalability issues. To address the

    更新日期:2020-03-09
  • TranS^3: A Transformer-based Framework for Unifying Code Summarization and Code Search
    arXiv.cs.SE Pub Date : 2020-03-06
    Wenhua Wang; Yuqun Zhang; Zhengran Zeng; Guandong Xu

    Code summarization and code search have been widely adopted in sofwaredevelopmentandmaintenance. However, fewstudieshave explored the efcacy of unifying them. In this paper, we propose TranS^3 , a transformer-based framework to integrate code summarization with code search. Specifcally, for code summarization,TranS^3 enables an actor-critic network, where in the actor network, we encode the collected

    更新日期:2020-03-09
  • Memory-Safety Challenge Considered Solved? An Empirical Study with All Rust CVEs
    arXiv.cs.SE Pub Date : 2020-03-06
    Hui Xu; Zhuangbin Chen; Mingshen Sun; Yangfan Zhou

    Rust is an emerging programing language that aims at preventing memory-safety bugs without sacrificing much efficiency. The property is very attractive to developers, and many projects start using the language. However, can Rust achieve the memory-safety promise? This paper studies the question by surveying the bug reports collected from two public datasets, Advisory-db and Trophy-cases, which contain

    更新日期:2020-03-09
  • TypeWriter: Neural Type Prediction with Search-based Validation
    arXiv.cs.SE Pub Date : 2019-12-08
    Michael Pradel; Georgios Gousios; Jason Liu; Satish Chandra

    Maintaining large code bases written in dynamically typed languages, such as JavaScript or Python, can be challenging due to the absence of type annotations: simple data compatibility errors proliferate, IDE support is limited, and APIs are hard to comprehend. Recent work attempts to address those issues through either static type inference or probabilistic type prediction. Unfortunately, static type

    更新日期:2020-03-09
  • Some Aspects of a Software Reliability Problem
    arXiv.cs.SE Pub Date : 2020-03-05
    Anton Petrov; Elena Popova; Alexander Petrov

    Obviously, the dynamism of software reliability research has speeded up significantly in the last period, and we can state the fact that its intensity is approaching, and in some cases is ahead of the information systems hardware reliability research intensity. Reliability of software is much more important than its other characteristics, such as runtime, and although the absolute reliability of modern

    更新日期:2020-03-06
  • Microservice Decomposition via Static and Dynamic Analysis of the Monolith
    arXiv.cs.SE Pub Date : 2020-03-05
    Alexander Krause; Christian Zirkelbach; Wilhelm Hasselbring; Stephan Lenga; Dan Kröger

    Migrating monolithic software systems into microservices requires the application of decomposition techniquesto find and select appropriate service boundaries. These techniques are often based on domain knowledge, static code analysis, and non-functional requirements such as maintainability. In this paper, we present our experience with an approach that extends static analysis with dynamic analysis

    更新日期:2020-03-06
  • Measuring the Quality of B Abstract Machines with ISO/IEC 25010
    arXiv.cs.SE Pub Date : 2020-03-04
    Cheng-Hao Cai; Jing Sun; Gillian Dobbie

    The B method has facilitated the development of software by specifying the design of software as abstract machines and formally verifying the correctness of the abstract machines. The quality of B abstract machines can significantly impact the quality of final software products. In this paper, we propose a set of criteria for measuring the quality of B abstract machines based on ISO/IEC 25010, which

    更新日期:2020-03-06
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