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Paper Digest: ICSE 2019 Highlights

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International Conference on Software Engineering (ICSE) is one of the top conferences on software engineering. In this year, there were 529 paper submissions, of which 109 accepted.In 2019, it is to be held in Montreal, Canada.

To help the community quickly catch up on the work presented in this conference, Paper Digest Team processed all accepted papers, and generated one highlight sentence (typically the main topic) for each paper. Readers are encouraged to read these machine generated highlights / summaries to quickly get the main idea of each paper.

We thank all authors for writing these interesting papers, and readers for reading our digests. If you do not want to miss any interesting academic paper, you are welcome to sign up our free paper digest service to get new paper updates customized to your own interests on a daily basis.

Paper Digest Team
team@paperdigest.org

TABLE 1: ICSE 2019 Papers

Title Authors Highlight
1 Learning to spot and refactor inconsistent method names Kui Liu, Dongsun Kim, Tegawend� F. Bissyand�, Taeyoung Kim, Kisub Kim, Anil Koyuncu, Suntae Kim, Yves Le Traon We thus propose a novel automated approach to debugging method names based on the analysis of consistency between method names and method code.
2 Harnessing evolution for multi-hunk program repair Seemanta Saha, Ripon K. Saha, Mukul R. Prasad In this work, we present a novel APR technique that generalizes single-hunk repair techniques to include an important class of multi-hunk bugs, namely bugs that may require applying a substantially similar patch at a number of locations.
3 On learning meaningful code changes via neural machine translation Michele Tufano, Jevgenija Pantiuchina, Cody Watson, Gabriele Bavota, Denys Poshyvanyk Our goal is to make this first important step by quantitatively and qualitatively investigating the ability of a Neural Machine Translation (NMT) model to learn how to automatically apply code changes implemented by developers during pull requests.
4 Natural software revisited Musfiqur Rahman, Dharani Palani, Peter C. Rigby On re-examination, we find that much of the apparent “naturalness” of source code is due to the presence of language specific syntax, especially separators, such as semi-colons and brackets.
5 Towards automating precision studies of clone detectors Vaibhav Saini, Farima Farmahinifarahani, Yadong Lu, Di Yang, Pedro Martins, Hitesh Sajnani, Pierre Baldi, Cristina V. Lopes We present a semiautomated approach to facilitate precision studies of clone detection tools.
6 Leopard: identifying vulnerable code for vulnerability assessment through program metrics Xiaoning Du, Bihuan Chen, Yuekang Li, Jianmin Guo, Yaqin Zhou, Yang Liu, Yu Jiang In this paper, we propose and implement a generic, lightweight and extensible framework, Leopard, to identify potentially vulnerable functions through program metrics.
7 Smoke: scalable path-sensitive memory leak detection for millions of lines of code Gang Fan, Rongxin Wu, Qingkai Shi, Xiao Xiao, Jinguo Zhou, Charles Zhang In this work, we present Smoke, a staged approach to resolve this paradox.
8 Reasonably-most-general clients for JavaScript library analysis Erik Krogh Kristensen, Anders M�ller In this work, we explore the concept of a reasonably-most-general client, in the context of a new static analysis tool ReaGenT that aims to detect errors in TypeScript declaration files for JavaScript libraries.
9 Resource-aware program analysis via online abstraction coarsening Kihong Heo, Hakjoo Oh, Hongseok Yang We present a new technique for developing a resource-aware program analysis.
10 Automated reporting of anti-patterns and decay in continuous integration Carmine Vassallo, Sebastian Proksch, Harald C. Gall, Massimiliano Di Penta We argue that automated detection can help with early identification and prevent such a process decay.
11 A system identification based Oracle for control-CPS software fault localization Zhijian He, Yao Chen, Enyan Huang, Qixin Wang, Yu Pei, Haidong Yuan This paper proposes an oracle based on the well adopted autoregressive system identification (AR-SI).
12 ReCDroid: automatically reproducing Android application crashes from bug reports Yu Zhao, Tingting Yu, Ting Su, Yang Liu, Wei Zheng, Jingzhi Zhang, William G. J. Halfond To improve the productivity of developers in resolving bug reports, in this paper, we introduce a novel approach, called ReCDroid, that can automatically reproduce crashes from bug reports for Android apps.
13 Mining historical test logs to predict bugs and localize faults in the test logs Anunay Amar, Peter C. Rigby In this paper we present techniques with the goal of capturing the maximum number of product faults, while flagging the minimum number of log lines for inspection.
14 Dlfinder: characterizing and detecting duplicate logging code smells Zhenhao Li, Tse-Hsun (Peter) Chen, Jinqiu Yang, Weiyi Shang In this paper, we focus on studying duplicate logging statements, which are logging statements that have the same static text message.
15 The seven sins: security smells in infrastructure as code scripts Akond Rahman, Chris Parnin, Laurie Williams The goal of this paper is to help practitioners avoid insecure coding practices while developing infrastructure as code (IaC) scripts through an empirical study of security smells in IaC scripts.
16 DifFuzz: differential fuzzing for side-channel analysis Shirin Nilizadeh, Yannic Noller, Corina S. Pasareanu We present DifFuzz, a fuzzing-based approach for detecting side-channel vulnerabilities related to time and space.
17 Automatically generating precise Oracles from structured natural language specifications Manish Motwani, Yuriy Brun We present Swami, an automated technique that extracts test oracles and generates executable tests from structured natural language specifications.
18 The product backlog Todd Sedano, Paul Ralph, C�cile P�raire Objective: The purpose of this paper is to determine what is a product backlog, what is its role, and how does it emerge?
19 Easy modelling and verification of unpredictable and preemptive interrupt-driven systems Minxue Pan, Shouyu Chen, Yu Pei, Tian Zhang, Xuandong Li To address this problem, we propose a new modelling language called interrupt sequence diagram (ISD).
20 Towards understanding and reasoning about Android interoperations Sora Bae, Sungho Lee, Sukyoung Ryu In this paper, we present the first formal specification of Android interoperability to establish a firm ground for understanding and reasoning about the interoperations.
21 Zero-overhead path prediction with progressive symbolic execution Richard Rutledge, Sunjae Park, Haider Khan, Alessandro Orso, Milos Prvulovic, Alenka Zajic In previous work, we introduced zero-overhead profiling (ZOP), a technique that leverages the electromagnetic emissions generated by the computer hardware to profile a program without instrumenting it.
22 Mimic: UI compatibility testing system for Android apps Taeyeon Ki, Chang Min Park, Karthik Dantu, Steven Y. Ko, Lukasz Ziarek This paper proposes Mimic, an automated UI compatibility testing system for Android apps.
23 IconIntent: automatic identification of sensitive UI widgets based on icon classification for Android apps Xusheng Xiao, Xiaoyin Wang, Zhihao Cao, Hanlin Wang, Peng Gao In this work, we propose a novel app analysis framework, IconIntent, that synergistically combines program analysis and icon classification to identify sensitive UI widgets in Android apps.
24 Practical GUI testing of Android applications via model abstraction and refinement Tianxiao Gu, Chengnian Sun, Xiaoxing Ma, Chun Cao, Chang Xu, Yuan Yao, Qirun Zhang, Jian Lu, Zhendong Su This paper introduces a new, fully automated model-based approach for effective testing of Android apps.
25 AutoTap: synthesizing and repairing trigger-action programs using LTL properties Lefan Zhang, Weijia He, Jesse Martinez, Noah Brackenbury, Shan Lu, Blase Ur This paper presents AutoTap, a system that lets novice users easily specify desired properties for devices and services.
26 Active inductive logic programming for code search Aishwarya Sivaraman, Tianyi Zhang, Guy Van den Broeck, Miryung Kim Modern search techniques either cannot efficiently incorporate human feedback to refine search results or cannot express structural or semantic properties of desired code.
27 NL2Type: inferring JavaScript function types from natural language information Rabee Sohail Malik, Jibesh Patra, Michael Pradel This paper presents NL2Type, a learning-based approach for predicting likely type signatures of JavaScript functions.
28 Analyzing and supporting adaptation of online code examples Tianyi Zhang, Di Yang, Crista Lopes, Miryung Kim Using this taxonomy, we build an automated adaptation analysis technique on top of GumTree to classify the entire dataset into these types. We construct a comprehensive dataset linking SO posts to GitHub counterparts based on clone detection, time stamp analysis, and explicit URL references.
29 DockerizeMe: automatic inference of environment dependencies for python code snippets Eric Horton, Chris Parnin We present DockerizeMe, a technique for inferring the dependencies needed to execute a Python code snippet without import error.
30 BugSwarm: mining and continuously growing a dataset of reproducible failures and fixes David A. Tomassi, Naji Dmeiri, Yichen Wang, Antara Bhowmick, Yen-Chuan Liu, Premkumar T. Devanbu, Bogdan Vasilescu, Cindy Rubio-Gonz�lez We describe BugSwarm, a toolset that navigates these obstacles to enable the creation of a scalable, diverse, realistic, continuously growing set of durably reproducible failing and passing versions of real-world, open-source systems.
31 ActionNet: vision-based workflow action recognition from programming screencasts Dehai Zhao, Zhenchang Xing, Chunyang Chen, Xin Xia, Guoqiang Li In this paper, we are the first to present a novel technique for recognizing workflow actions in programming screencasts.
32 How C++ developers use immutability declarations: an empirical study Jonathan Eyolfson, Patrick Lam Our goal is to understand the usage of immutability by C++ developers in practice.
33 Latent patterns in activities: a field study of how developers manage context Souti Chattopadhyay, Nicholas Nelson, Yenifer Ramirez Gonzalez, Annel Amelia Leon, Rahul Pandita, Anita Sarma The goal of this research is to gain a better understanding of how developers structure their tasks and manage context through a field study of ten professional developers in an industrial setting.
34 Developer reading behavior while summarizing Java methods: size and context matters Nahla J. Abid, Bonita Sharif, Natalia Dragan, Hend Alrasheed, Jonathan I. Maletic An eye-tracking study of 18 developers reading and summarizing Java methods is presented.
35 Distilling neural representations of data structure manipulation using fMRI and fNIRS Yu Huang, Xinyu Liu, Ryan Krueger, Tyler Santander, Xiaosu Hu, Kevin Leach, Westley Weimer In a human study involving 76 participants, we examine list, array, tree, and mental rotation tasks using both functional near-infrared spectroscopy (fNIRS) and functional magnetic resonance imaging (fMRI).
36 FastLane: test minimization for rapidly deployed large-scale online services Adithya Abraham Philip, Ranjita Bhagwan, Rahul Kumar, Chandra Sekhar Maddila, Nachiappan Nagappan This paper presents FastLane, a system that performs data-driven test minimization.
37 Scalable approaches for test suite reduction Emilio Cruciani, Breno Miranda, Roberto Verdecchia, Antonia Bertolino Test suite reduction approaches aim at decreasing software regression testing costs by selecting a representative subset from large-size test suites.
38 A framework for checking regression test selection tools Chenguang Zhu, Owolabi Legunsen, August Shi, Milos Gligoric We present RTS Check, the first framework for checking RTS tools.
39 Supporting analysts by dynamic extraction and classification of requirements-related knowledge Zahra Shakeri Hossein Abad, Vincenzo Gervasi, Didar Zowghi, Behrouz H. Far We propose to use both generative and discriminating methods.
40 Analysis and detection of information types of open source software issue discussions Deeksha Arya, Wenting Wang, Jin L. C. Guo, Jinghui Cheng In this paper, we address this challenge by identifying the information types presented in OSS issue discussions. Through qualitative content analysis of 15 complex issue threads across three projects hosted on GitHub, we uncovered 16 information types and created a labeled corpus containing 4656 sentences.
41 Do developers discover new tools on the toilet? Emerson Murphy-Hill, Edward K. Smith, Caitlin Sadowski, Ciera Jaspan, Collin Winter, Matthew Jorde, Andrea Knight, Andrew Trenk, Steve Gross In this paper, we evaluate such a technique, called Testing on the Toilet, by performing a mixed-methods case study.
42 Tool choice matters: JavaScript quality assurance tools and usage outcomes in GitHub projects David Kavaler, Asher Trockman, Bogdan Vasilescu, Vladimir Filkov We propose a general methodology to model the time-dependent effect of automation tool choice on four outcomes of interest: prevalence of issues, code churn, number of pull requests, and number of contributors, all with a multitude of controls.
43 Hunting for bugs in code coverage tools via randomized differential testing Yibiao Yang, Yuming Zhou, Hao Sun, Zhendong Su, Zhiqiang Zuo, Lei Xu, Baowen Xu In this study, we propose a randomized differential testing approach to hunting for bugs in the most widely used C code coverage tools.
44 Rotten green tests Julien Delplanque, St�phane Ducasse, Guillermo Polito, Andrew P. Black, Anne Etien We describe an approach to identify rotten green tests by combining simple static and dynamic call-site analyses.
45 VFix: value-flow-guided precise program repair for null pointer dereferences Xuezheng Xu, Yulei Sui, Hua Yan, Jingling Xue We present VFix, a new value-flow-guided APR approach, to fix null pointer exception (NPE) bugs by considering a substantially reduced solution space in order to greatly increase the number of correct patches generated.
46 On reliability of patch correctness assessment Xuan-Bach D. Le, Lingfeng Bao, David Lo, Xin Xia, Shanping Li, Corina Pasareanu In this work, we propose to assess reliability of author and automated annotations on patch correctness assessment.
47 How reliable is the crowdsourced knowledge of security implementation? Mengsu Chen, Felix Fischer, Na Meng, Xiaoyin Wang, Jens Grossklags To answer these highly important questions, we conducted a comprehensive study on security-related SO posts by contrasting secure and insecure advice with the community-given content evaluation.
48 Pattern-based mining of opinions in Q&A websites Bin Lin, Fiorella Zampetti, Gabriele Bavota, Massimiliano Di Penta, Michele Lanza We propose POME (Pattern-based Opinion MinEr), an approach that leverages natural language parsing and pattern-matching to classify Stack Overflow sentences referring to APIs according to seven aspects (e.g., performance, usability), and to determine their polarity (positive vs negative).
49 Detection and repair of architectural inconsistencies in Java Negar Ghorbani, Joshua Garcia, Sam Malek In this paper, we formally define 8 inconsistent modular dependencies that may arise in Java-9 applications.
50 Could I have a stack trace to examine the dependency conflict issue? Ying Wang, Ming Wen, Rongxin Wu, Zhenwei Liu, Shin Hwei Tan, Zhiliang Zhu, Hai Yu, Shing-Chi Cheung We applied Riddle on 19 real-world Java projects with duplicate libraries or classes.
51 Investigating the impact of multiple dependency structures on software defects Di Cui, Ting Liu, Yuanfang Cai, Qinghua Zheng, Qiong Feng, Wuxia Jin, Jiaqi Guo, Yu Qu In this paper, we present our systematic investigation of this question from the perspective of software architecture.
52 StoryDroid: automated generation of storyboard for Android apps Sen Chen, Lingling Fan, Chunyang Chen, Ting Su, Wenhe Li, Yang Liu, Lihua Xu Before developing a new app, the development team usually endeavors painstaking efforts to review many existing apps with similar purposes.
53 Statistical algorithmic profiling for randomized approximate programs Keyur Joshi, Vimuth Fernando, Sasa Misailovic We present AxProf, an algorithmic profiling framework for analyzing randomized approximate programs.
54 Safe automated refactoring for intelligent parallelization of Java 8 streams Raffi Khatchadourian, Yiming Tang, Mehdi Bagherzadeh, Syed Ahmed In this paper, we present an automated refactoring approach that assists developers in writing efficient stream code in a semantics-preserving fashion.
55 Detecting atomicity violations for event-driven Node.js applications Xiaoning Chang, Wensheng Dou, Yu Gao, Jie Wang, Jun Wei, Tao Huang In this paper, we propose NodeAV, which can predictively detect atomicity violations in Node.js applications based on an execution trace.
56 Parallel refinement for multi-threaded program verification Liangze Yin, Wei Dong, Wanwei Liu, Ji Wang We present a parallel refinement framework which employs multiple engines to refine the abstraction in parallel.
57 Mining software defects: should we consider affected releases? Suraj Yatish, Jirayus Jiarpakdee, Patanamon Thongtanunam, Chakkrit Tantithamthavorn In this paper, we set out to investigate the nature of the difference of defect datasets generated by the heuristic approach and the realistic approach that leverages the earliest affected release that is realistically estimated by a software development team for a given defect.
58 Class imbalance evolution and verification latency in just-in-time software defect prediction George G. Cabral, Leandro L. Minku, Emad Shihab, Suhaib Mujahid Most existing JIT-SDP work assumes that the characteristics of the problem remain the same over time.
59 FLOSS participants’ perceptions about gender and inclusiveness: a survey Amanda Lee, Jeffrey C. Carver Aims: In this paper, we examine the extent to which these problems still exist.
60 Going farther together: the impact of social capital on sustained participation in open source Huilian Sophie Qiu, Alexander Nolte, Anita Brown, Alexander Serebrenik, Bogdan Vasilescu In this paper we report on a mixed-methods empirical study of the role of social capital (i.e., the resources people can gain from their social connections) for sustained participation by women and men in open-source GitHub projects.
61 Investigating the effects of gender bias on GitHub Nasif Imtiaz, Justin Middleton, Joymallya Chakraborty, Neill Robson, Gina Bai, Emerson Murphy-Hill In this paper, we study the effects of that bias by using an existing framework derived from the gender studies literature.
62 SLF: fuzzing without valid seed inputs Wei You, Xuwei Liu, Shiqing Ma, David Perry, Xiangyu Zhang, Bin Liang In this paper, we propose a novel fuzzing technique that features the capability of generating valid seed inputs.
63 Superion: grammar-aware greybox fuzzing Junjie Wang, Bihuan Chen, Lei Wei, Yang Liu To this end, we propose a grammar-aware coverage-based grey-box fuzzing approach to fuzz programs that process structured inputs.
64 Grey-box concolic testing on binary code Jaeseung Choi, Joonun Jang, Choongwoo Han, Sang Kil Cha We present grey-box concolic testing, a novel path-based test case generation method that combines the best of both white-box and grey-box fuzzing.
65 RESTler: stateful REST API fuzzing Vaggelis Atlidakis, Patrice Godefroid, Marina Polishchuk This paper introduces RESTler, the first stateful REST API fuzzer.
66 Training binary classifiers as data structure invariants Facundo Molina, Renzo Degiovanni, Pablo Ponzio, Germ�n Regis, Nazareno Aguirre, Marcelo Frias We present a technique to distinguish valid from invalid data structure objects.
67 Graph embedding based familial analysis of Android malware using unsupervised learning Ming Fan, Xiapu Luo, Jun Liu, Meng Wang, Chunyin Nong, Qinghua Zheng, Ting Liu After that, instead of training a classifier with labeled samples, we construct malware link network based on SRAs and apply community detection algorithms on it to group the unlabeled samples into groups.
68 A novel neural source code representation based on abstract syntax tree Jian Zhang, Xu Wang, Hongyu Zhang, Hailong Sun, Kaixuan Wang, Xudong Liu In this paper, we propose a novel AST-based Neural Network (ASTNN) for source code representation.
69 A neural model for generating natural language summaries of program subroutines Alexander LeClair, Siyuan Jiang, Collin McMillan In this paper, we present a neural model that combines words from code with code structure from an AST.
70 The list is the process: reliable pre-integration tracking of commits on mailing lists Ralf Ramsauer, Daniel Lohmann, Wolfgang Mauerer We present a novel method for tracking this otherwise invisible evolution of software changes on mailing lists by connecting all early revisions of changes to their final version in repositories.
71 Graph-based mining of in-the-wild, fine-grained, semantic code change patterns Hoan Anh Nguyen, Tien N. Nguyen, Danny Dig, Son Nguyen, Hieu Tran, Michael Hilton We introduce a novel graph-based mining approach, CPatMiner, to detect previously unknown repetitive changes in the wild, by mining fine-grained semantic code change patterns from a large number of repositories.
72 Intention-based integration of software variants Max Lillack, Stefan Stanciulescu, Wilhelm Hedman, Thorsten Berger, Andrzej Wasowski In this work, we show that fine-grained code edits needed for integration can be alleviated by a small set of integration intentions—domain-specific actions declared over code snippets controlling the integration.
73 Supporting the statistical analysis of variability models Ruben Heradio, David Fernandez-Amoros, Christoph Mayr-Dorn, Alexander Egyed Variability models are broadly used to specify the configurable features of highly customizable software.
74 Multifaceted automated analyses for variability-intensive embedded systems Sami Lazreg, Maxime Cordy, Philippe Collet, Patrick Heymans, S�bastien Mosser We propose a model-driven framework to assist engineers in this choice.
75 Exposing library API misuses via mutation analysis Ming Wen, Yepang Liu, Rongxin Wu, Xuan Xie, Shing-Chi Cheung, Zhendong Su Based on these observations, we propose MutApi, the first approach to discovering API misuse patterns via mutation analysis.
76 Pivot: learning API-device correlations to facilitate Android compatibility issue detection Lili Wei, Yepang Liu, Shing-Chi Cheung In this paper, we propose such a technique, PIVOT, that automatically learns API-device correlations of FIC issues from existing Android apps.
77 SafeCheck: safety enhancement of Java unsafe API Shiyou Huang, Jianmei Guo, Sanhong Li, Xiang Li, Yumin Qi, Kingsum Chow, Jeff Huang In this work, we study the Unsafe crash patterns and propose a memory checker to enforce memory safety, thus avoiding the JVM crash caused by the misuse of the Unsafe API at the bytecode level.
78 CTRAS: crowdsourced test report aggregation and summarization Rui Hao, Yang Feng, James A. Jones, Yuying Li, Zhenyu Chen In this paper, instead of focusing on only detecting duplicates based on textual descriptions, we present CTRAS: a novel approach to leveraging duplicates to enrich the content of bug descriptions and improve the efficiency of inspecting these reports.
79 iSENSE: completion-aware crowdtesting management Junjie Wang, Ye Yang, Rahul Krishna, Tim Menzies, Qing Wang This paper aims at exploring automated decision support to effectively manage crowdtesting processes.
80 How practitioners perceive coding proficiency Xin Xia, Zhiyuan Wan, Pavneet Singh Kochhar, David Lo To answer this question, we perform an empirical study by surveying 340 software practitioners from 33 countries across 5 continents.
81 Socio-technical work-rate increase associates with changes in work patterns in online projects Farhana Sarker, Bogdan Vasilescu, Kelly Blincoe, Vladimir Filkov Guided by the responses, we developed regression models to study how communication and committing patterns change with increased work-rates and fit those models to large-scale data gathered from traces left by thousands of GitHub developers.
82 Why do episodic volunteers stay in FLOSS communities? Ann Barcomb, Klaas-Jan Stol, Dirk Riehle, Brian Fitzgerald Using the concept of episodic volunteering (EV) from the general volunteering literature, we derive a model consisting of five key constructs that we hypothesize affect episodic volunteers’ retention in FLOSS communities.
83 When code completion fails: a case study on real-world completions Vincent J. Hellendoorn, Sebastian Proksch, Harald C. Gall, Alberto Bacchelli This paper presents a case study on 15,000 code completions that were applied by 66 real developers, which we study and contrast with artificial completions to inform future research and tools in this area. We publicly release our preprint [https://doi.org/10.5281/zenodo.2565673] and replication data and materials [https://doi.org/10.5281/zenodo.2562249].
84 Interactive production performance feedback in the IDE J�rgen Cito, Philipp Leitner, Martin Rinard, Harald C. Gall We present PerformanceHat, a new system that uses profiling information from production executions to develop a global performance model suitable for integration into interactive development environments.
85 Redundant loads: a software inefficiency indicator Pengfei Su, Shasha Wen, Hailong Yang, Milind Chabbi, Xu Liu We develop LoadSpy, a whole-program profiler to pinpoint redundant memory load operations, which are often a symptom of many redundant operations.
86 View-centric performance optimization for database-backed web applications Junwen Yang, Cong Yan, Chengcheng Wan, Shan Lu, Alvin Cheung In this paper, we present Panorama, a view-centric and database-aware development environment for web developers.
87 Adjust: runtime mitigation of resource abusing third-party online ads Weihang Wang, I Luk Kim, Yunhui Zheng To address these challenges, we propose an effective technique, AdJust, that allows publishers to specify constraints on events associated with third-party ads (e.g., URL requests, HTML element creations, and timers), so that they can mitigate user experience degradations and enforce consistent ads experience to all users.
88 Symbolic repairs for GR(1) specifications Shahar Maoz, Jan Oliver Ringert, Rafi Shalom In this work we present two novel symbolic algorithms for repairing unrealizable GR(1) specifications.
89 CRADLE: Hung Viet Pham, Thibaud Lutellier, Weizhen Qi, Lin Tan Thus, we propose CRADLE, a new approach that focuses on finding and localizing bugs in DL software libraries.
90 Guiding deep learning system testing using surprise adequacy Jinhan Kim, Robert Feldt, Shin Yoo We propose a novel test adequacy criterion for testing of DL systems, called Surprise Adequacy for Deep Learning Systems (SADL), which is based on the behaviour of DL systems with respect to their training data.
91 FOCUS: a recommender system for mining API function calls and usage patterns Phuong T. Nguyen, Juri Di Rocco, Davide Di Ruscio, Lina Ochoa, Thomas Degueule, Massimiliano Di Penta In this paper, we reformulate the problem of usage pattern recommendation in terms of a collaborative-filtering recommender system.
92 Test-driven code review: an empirical study Davide Spadini, Fabio Palomba, Tobias Baum, Stefan Hanenberg, Magiel Bruntink, Alberto Bacchelli In this paper, we aim at empirically understanding whether this practice has an effect on code review effectiveness and how developers’ perceive TDR.
93 Why does code review work for open source software communities? Adam Alami, Marisa Leavitt Cohn, Andrzej Wasowski In the paper, we describe the study design, analyze the collected data and formulate 20 proposals for how what we know about hacker ethics and human and social aspects of code review, could be exploited to improve the effectiveness of the practice in software projects.
94 Distance-based sampling of software configuration spaces Christian Kaltenecker, Alexander Grebhahn, Norbert Siegmund, Jianmei Guo, Sven Apel This way, we cover different kinds of interactions among configuration options in the sample set.
95 DeepPerf: performance prediction for configurable software with deep sparse neural network Huong Ha, Hongyu Zhang In this paper, we propose a novel approach to model highly configurable software system using a deep feedforward neural network (FNN) combined with a sparsity regularization technique, e.g. the L1 regularization.
96 GreenBundle: an empirical study on the energy impact of bundled processing Shaiful Alam Chowdhury, Abram Hindle, Rick Kazman, Takumi Shuto, Ken Matsui, Yasutaka Kamei In this paper we show that some simple design choices can have significant effects on energy consumption.
97 Search-based energy testing of Android Reyhaneh Jabbarvand, Jun-Wei Lin, Sam Malek We present Cobweb, a search-based energy testing technique for Android.
98 Global optimization of numerical programs via prioritized stochastic algebraic transformations Xie Wang, Huaijin Wang, Zhendong Su, Enyi Tang, Xin Chen, Weijun Shen, Zhenyu Chen, Linzhang Wang, Xianpei Zhang, This paper introduces a novel global optimization framework to tackle this challenge.
99 Type migration in ultra-large-scale codebases Ameya Ketkar, Ali Mesbah, Davood Mazinanian, Danny Dig, Edward Aftandilian We implemented this approach as an IDE-independent tool called T2R, which integrates with most build systems.
100 Dynamic slicing for Android Tanzirul Azim, Arash Alavi, Iulian Neamtiu, Rajiv Gupta To address these problems, we introduce AndroidSlicer1, the first slicing approach for Android.
101 Recovering variable names for minified code with usage contexts Hieu Tran, Ngoc Tran, Son Nguyen, Hoan Nguyen, Tien N. Nguyen This paper presents JSNeat, an information retrieval (IR)-based approach to recover the variable names in minified JS code.
102 Gigahorse: thorough, declarative decompilation of smart contracts Neville Grech, Lexi Brent, Bernhard Scholz, Yannis Smaragdakis We present the Gigahorse toolchain.
103 Probabilistic disassembly Kenneth Miller, Yonghwi Kwon, Yi Sun, Zhuo Zhang, Xiangyu Zhang, Zhiqiang Lin Therefore, we propose to model such uncertainty using probabilities and propose a novel disassembly technique, which computes a probability for each address in the code space, indicating its likelihood of being a true positive instruction.
104 Software documentation issues unveiled Emad Aghajani, Csaba Nagy, Olga Lucero Vega-M�rquez, Mario Linares-V�squez, Laura Moreno, Gabriele Bavota, Michele Lanza We present a large scale empirical study, where we mined, analyzed, and categorized 878 documentation-related artifacts stemming from four different sources, namely mailing lists, Stack Overflow discussions, issue repositories, and pull requests.
105 9.6 million links in source code comments: purpose, evolution, and decay Hideaki Hata, Christoph Treude, Raula Gaikovina Kula, Takashi Ishio In this paper, we investigate the role of links contained in source code comments from these perspectives.
106 Leveraging artifact trees to evolve and reuse safety cases Ankit Agrawal, Seyedehzahra Khoshmanesh, Michael Vierhauser, Mona Rahimi, Jane Cleland-Huang, Robyn Lutz In this paper we utilize design science to develop a novel solution for identifying areas of a SAC that are affected by changes to the system.
107 Detecting incorrect build rules N�ndor Licker, Andrew Rice We evaluate our method by exhaustively testing build rules of open-source projects, uncovering issues leading to race conditions and faulty builds in 30 of them.
108 Adversarial sample detection for deep neural network through model mutation testing Jingyi Wang, Guoliang Dong, Jun Sun, Xinyu Wang, Peixin Zhang In this work, we propose an alternative approach to detect adversarial samples at runtime.
109 Deep differential testing of JVM implementations Yuting Chen, Ting Su, Zhendong Su This paper tackles this challenge by introducing classming, a novel, effective approach to performing deep, differential JVM testing.