Grigore Rosu, Massimiliano Di Penta, Tien N. Nguyen
Proceedings of the 32nd International Conference on Automated Software Engineering
ASE, 2017.

@proceedings{ASE-2017,
	editor        = "Grigore Rosu and Massimiliano Di Penta and Tien N. Nguyen",
	ee            = "https://ieeexplore.ieee.org/xpl/conhome/8106906/proceeding",
	ee            = "https://www.computer.org/csdl/proceedings/ase/2017/2684/00/index.html",
	isbn          = "978-1-5386-2684-9",
	publisher     = "{IEEE Computer Society}",
	title         = "{Proceedings of the 32nd International Conference on Automated Software Engineering}",
	year          = 2017,
}

Contents (117 items)

ASE-2017-Holzmann #interactive

Cobra - an interactive static code analyzer (GJH), p. 1.

ASE-2017-Han #mining #question #re-engineering

Mining structures from massive text data: will it help software engineering? (JH0), p. 2.

ASE-2017-Deursen #re-engineering

Software engineering without borders (AvD), p. 3.

ASE-2017-ZhangLLC #mobile #testing

Systematically testing background services of mobile apps (LLZ, CJML, YL, EC), pp. 4–15.

ASE-2017-MaoHJ #automation #mobile #testing

Crowd intelligence enhances automated mobile testing (KM, MH, YJ0), pp. 16–26.

ASE-2017-SongQH #android #named #testing #user interface

EHBDroid: beyond GUI testing for Android applications (WS0, XQ, JH0), pp. 27–37.

ASE-2017-ZhangCTCBL #generative #mobile #sketching #testing #user interface

Sketch-guided GUI test generation for mobile applications (CZ, HC, ET, XC0, LB, XL), pp. 38–43.

ASE-2017-ToffolaSP #effectiveness #exclamation #generative #mining #testing

Saying 'hi!' is not enough: mining inputs for effective test generation (LDT, CAS, MP), pp. 44–49.

ASE-2017-GodefroidPS #fuzzing #machine learning

Learn&Fuzz: machine learning for input fuzzing (PG, HP, RS), pp. 50–59.

ASE-2017-ZhaoSZFV #development #empirical #integration #scalability

The impact of continuous integration on other software development practices: a large-scale empirical study (YZ, AS, YZ, VF, BV), pp. 60–71.

ASE-2017-KavalerSHAF #complexity #git

Perceived language complexity in GitHub issue discussions and their effect on issue resolution (DK, SS, VH, RA, VF), pp. 72–83.

ASE-2017-MirhosseiniP #automation #dependence #developer #question

Can automated pull requests encourage software developers to upgrade out-of-date dependencies? (SM, CP), pp. 84–94.

ASE-2017-PaixaoKHRH #architecture #developer #question

Are developers aware of the architectural impact of their changes? (MP, JK, DH, CR, MH), pp. 95–105.

ASE-2017-AhmedBIR #analysis #code review #interactive #named #overview #sentiment

SentiCR: a customized sentiment analysis tool for code review interactions (TA, AB, AI, SR), pp. 106–111.

ASE-2017-RatolR #detection

Detecting fragile comments (IKR, MPR), pp. 112–122.

ASE-2017-LinZZX #concept #retrieval #source code #using

Improving software text retrieval using conceptual knowledge in source code (ZL, YZ, JZ, BX), pp. 123–134.

ASE-2017-JiangAM #automation #commit #generative #using

Automatically generating commit messages from diffs using neural machine translation (SJ, AA, CM), pp. 135–146.

ASE-2017-SunCWB #using

Improving missing issue-commit link recovery using positive and unlabeled data (YS, CC, QW0, BWB), pp. 147–152.

ASE-2017-TianTSL #api #documentation #named

APIBot: question answering bot for API documentation (YT0, FT, AS0, DL0), pp. 153–158.

ASE-2017-UddinK #api #automation #summary

Automatic summarization of API reviews (GU, FK), pp. 159–170.

ASE-2017-CelikPG #named #proving #scalability #verification

iCoq: regression proof selection for large-scale verification projects (AÇ, KP, MG), pp. 171–182.

ASE-2017-TianDDO #effectiveness #model checking

More effective interpolations in software model checking (CT, ZD, ZD, CHLO), pp. 183–193.

ASE-2017-GhassabaniGWHW #metric #verification

Proof-based coverage metrics for formal verification (EG, AG, MWW, MPEH, LGW), pp. 194–199.

ASE-2017-CastanoBGU #execution #model checking

Model checker execution reports (RC, VAB, DG, SU), pp. 200–205.

ASE-2017-SungKW #composition #verification

Modular verification of interrupt-driven software (CS, MK, CW0), pp. 206–216.

ASE-2017-CorradiniFP0TV #framework #modelling #named #process #verification

BProVe: a formal verification framework for business process models (FC, FF, AP, BR0, FT, AV), pp. 217–228.

ASE-2017-ChenODL #detection #static analysis #web

Static detection of asymptotic resource side-channel vulnerabilities in web applications (JC, OO, ID, CL), pp. 229–239.

ASE-2017-WangKZAKLLMZE #named #programming #web

PAD: programming third-party web advertisement censorship (WW, YK, YZ, YA, ILK, WCL, YL, WM, XZ0, PE), pp. 240–251.

ASE-2017-LeeHR #all about #detection #injection #process #semantics

All about activity injection: threats, semantics, and detection (SL, SH, SR), pp. 252–262.

ASE-2017-MathisASBZ #data flow #detection

Detecting information flow by mutating input data (BM, VA, EOS, MB, AZ), pp. 263–273.

ASE-2017-HeCHSLYHYJF #automation

Automatically assessing crashes from heap overflows (LH, YC0, HH, PS, ZL, YY, HH, JY, XJ, DF), pp. 274–279.

ASE-2017-RafiqDRBYSLCPN #adaptation #learning #network #online #re-engineering #social

Learning to share: engineering adaptive decision-support for online social networks (YR, LD, AR, AKB, MY, AS, ML, GC, BAP, BN), pp. 280–285.

ASE-2017-HuangAPZT #android #reduction #user interface

UI driven Android application reduction (JH0, YA, DMP, XZ0, CT0), pp. 286–296.

ASE-2017-JiangWLC #android #named #performance #sequence

SimplyDroid: efficient event sequence simplification for Android application (BJ0, YW, TL, WKC0), pp. 297–307.

ASE-2017-FazziniO #automation #consistency #detection #mobile #nondeterminism #platform

Automated cross-platform inconsistency detection for mobile apps (MF, AO), pp. 308–318.

ASE-2017-WangW #analysis #fuzzing #in memory #similarity

In-memory fuzzing for binary code similarity analysis (SW0, DW), pp. 319–330.

ASE-2017-RupprechtC0BLB #c #c++ #data type #identification #named

DSIbin: identifying dynamic data structures in C/C++ binaries (TR, XC0, DHW0, JHB, GL, HB), pp. 331–341.

ASE-2017-KargenS #robust #towards

Towards robust instruction-level trace alignment of binary code (UK, NS), pp. 342–352.

ASE-2017-KimFJJOLC #analysis #testing

Testing intermediate representations for binary analysis (SK0, MF, MJ, SJ, DO, JL, SKC), pp. 353–364.

ASE-2017-GerrardD

Comprehensive failure characterization (MJG, MBD), pp. 365–376.

ASE-2017-CoppikSWS #fault #kernel #named #operating system

TrEKer: tracing error propagation in operating system kernels (NC, OS, SW0, NS), pp. 377–387.

ASE-2017-SulirP #named

RuntimeSearch: Ctrl+F for a running program (MS, JP), pp. 388–393.

ASE-2017-LinMXXSPLZD #design #mining #reuse

Mining implicit design templates for actionable code reuse (YL0, GM, YX, ZX, JS0, XP0, YL0, WZ, JSD), pp. 394–404.

ASE-2017-ChapmanWS #comprehension #regular expression

Exploring regular expression comprehension (CC, PW, KTS), pp. 405–416.

ASE-2017-ScalabrinoBVVPO #automation #how #question

Automatically assessing code understandability: how far are we? (SS, GB, CV, MLV, DP, RO), pp. 417–427.

ASE-2017-RahmanR #concept #documentation #query #using

Improved query reformulation for concept location using CodeRank and document structures (MMR, CKR), pp. 428–439.

ASE-2017-ShiCWLB #analysis #comprehension #feature model #fuzzy

Understanding feature requests by leveraging fuzzy method and linguistic analysis (LS, CC, QW0, SL, BWB), pp. 440–450.

ASE-2017-QianP0YNZ #collaboration #composition #social

O2O service composition with social collaboration (WQ, XP0, JS0, YY, BN, WZ), pp. 451–461.

ASE-2017-DanielJSC #framework #model transformation #named #scalability

Gremlin-ATL: a scalable model transformation framework (GD, FJ, GS, JC), pp. 462–472.

ASE-2017-RahimiXCL #problem #safety

Diagnosing assumption problems in safety-critical products (MR, WX, JCH, RRL), pp. 473–484.

ASE-2017-IncertoTT #adaptation #performance #predict #self

Software performance self-adaptation through efficient model predictive control (EI, MT, CT), pp. 485–496.

ASE-2017-JamshidiSVKPA #analysis #configuration management #learning #modelling #performance

Transfer learning for performance modeling of configurable systems: an exploratory analysis (PJ, NS, MV, CK, AP, YA), pp. 497–508.

ASE-2017-FrancoGR #debugging

A comprehensive study of real-world numerical bug characteristics (ADF, HG0, CRG), pp. 509–519.

ASE-2017-WangDGGQYW #concurrent #debugging

A comprehensive study on real world concurrency bugs in Node.js (JW, WD, YG, CG, FQ, KY, JW0), pp. 520–531.

ASE-2017-HigoOK #abstract syntax tree #generative

Generating simpler AST edit scripts by considering copy-and-paste (YH, AO, SK), pp. 532–542.

ASE-2017-LessenichAKSS #performance #precise

Renaming and shifted code in structured merging: looking ahead for precision and performance (OL, SA, CK, GS, JS), pp. 543–553.

ASE-2017-MenariniYG #case study #code review #overview #performance #semantics #user study

Semantics-assisted code review: an efficient toolchain and a user study (MM, YY, WGG), pp. 554–565.

ASE-2017-OcarizaP0 #consistency #detection #nondeterminism #web

Detecting unknown inconsistencies in web applications (FSOJ, KP, AM0), pp. 566–577.

ASE-2017-TomasdottirAD #developer #how #javascript #why

Why and how JavaScript developers use linters (KFT, MFA, AvD), pp. 578–589.

ASE-2017-KapusC #automation #difference #execution #generative #symbolic computation #testing

Automatic testing of symbolic execution engines via program generation and differential testing (TK, CC), pp. 590–600.

ASE-2017-LiewSCDZW #case study #execution #float #programming #symbolic computation

Floating-point symbolic execution: a case study in n-version programming (DL, DS, CC, AFD, RZ, KW), pp. 601–612.

ASE-2017-CoppaDD #execution #pointer #reasoning #symbolic computation

Rethinking pointer reasoning in symbolic execution (EC, DCD, CD), pp. 613–618.

ASE-2017-AlatawiSM #abstract interpretation #execution #performance #symbolic computation

Leveraging abstract interpretation for efficient dynamic symbolic execution (EA, HS, TM0), pp. 619–624.

ASE-2017-WeissGB #interactive #named

Tortoise: interactive system configuration repair (AW, AG, YB), pp. 625–636.

ASE-2017-Chen0F #contract #program repair

Contract-based program repair without the contracts (LC, YP0, CAF), pp. 637–647.

ASE-2017-SahaLYP #effectiveness #named #object-oriented #program repair

ELIXIR: effective object oriented program repair (RKS, YL, HY, MRP), pp. 648–659.

ASE-2017-XinR #automation #program repair

Leveraging syntax-related code for automated program repair (QX, SPR), pp. 660–670.

ASE-2017-ZhongW

Boosting complete-code tool for partial program (HZ, XW), pp. 671–681.

ASE-2017-YangJ0SGL

A language model for statements of software code (YY, YJ0, MG0, JS, JG, HL), pp. 682–687.

ASE-2017-GasparicG0 #development #ide #recommendation

Context-aware integrated development environment command recommender systems (MG, TG, FR0), pp. 688–693.

ASE-2017-RolfsnesMB #predict #recommendation

Predicting relevance of change recommendations (TR, LM, DWB), pp. 694–705.

ASE-2017-XuXXL #automation #developer #generative #named #summary

AnswerBot: automated generation of answer summary to developersź technical questions (BX, ZX, XX0, DL0), pp. 706–716.

ASE-2017-WangSFY #crowdsourcing #developer #recommendation

Recommending crowdsourced software developers in consideration of skill improvement (ZW, HS0, YF, LY), pp. 717–722.

ASE-2017-Perez-SolerGLJ #modelling #network #social #towards

The rise of the (modelling) bots: towards assisted modelling via social networks (SPS, EG, JdL, FJ0), pp. 723–728.

ASE-2017-ZhouSLCL #detection #named

UNDEAD: detecting and preventing deadlocks in production software (JZ, SS, HL, YC0, TL), pp. 729–740.

ASE-2017-Abdelrasoul #order #random #scheduling #using

Promoting secondary orders of event pairs in randomized scheduling using a randomized stride (MA), pp. 741–752.

ASE-2017-NguyenS0TP #concurrent #parallel #source code

Parallel bug-finding in concurrent programs via reduced interleaving instances (TLN, PS, BF0, SLT, GP), pp. 753–764.

ASE-2017-PintoCCXL #comprehension #parallel

Understanding and overcoming parallelism bottlenecks in ForkJoin applications (GP0, AC, FC, G(X, YDL), pp. 765–775.

ASE-2017-MetzlerSBS #concurrent #scheduling #source code #verification

Quick verification of concurrent programs by iteratively relaxed scheduling (PM, HS, PB, NS), pp. 776–781.

ASE-2017-LiSLLL #automation #generative #invariant #refinement

Automatic loop-invariant generation and refinement through selective sampling (JL0, JS0, LL0, QLL, SWL), pp. 782–792.

ASE-2017-LinSXLSH #invariant #named

FiB: squeezing loop invariants by interpolation between Forward/Backward predicate transformers (SWL, JS0, HX, YL0, DS, HH), pp. 793–803.

ASE-2017-NguyenDV #invariant #named #using

SymInfer: inferring program invariants using symbolic states (TN, MBD, WV), pp. 804–814.

ASE-2017-LeungL #ide #named #parsing #synthesis

Parsimony: an IDE for example-guided synthesis of lexers and parsers (AL, SL), pp. 815–825.

ASE-2017-KrismayerRG #constraints #mining #monitoring

Mining constraints for event-based monitoring in systems of systems (TK, RR, PG), pp. 826–831.

ASE-2017-ZamaniradBBC0 #api #natural language #programming

Programming bots by synthesizing natural language expressions into API invocations (SZ, BB, MCB, FC, CR0), pp. 832–837.

ASE-2017-CandidoMd #case study #open source #parallel #testing

Test suite parallelization in open-source projects: a study on its usage and impact (JC, LM, Md), pp. 838–848.

ASE-2017-ChengYW #reduction #sequence #testing #user interface

Systematic reduction of GUI test sequences (LC, ZY, CW0), pp. 849–860.

ASE-2017-HerfertPP #automation #testing

Automatically reducing tree-structured test inputs (SH, JP, MP), pp. 861–871.

ASE-2017-SoltanaSB #generative #statistics #testing

Synthetic data generation for statistical testing (GS, MS, LCB), pp. 872–882.

ASE-2017-LeeYSNM #android #detection #named #security #visualisation

SEALANT: a detection and visualization tool for inter-app security vulnerabilities in Android (YKL, PY, AS, DN, NM), pp. 883–888.

ASE-2017-KritzingerKVRG #monitoring #requirements #visualisation

Visualization support for requirements monitoring in systems of systems (LMK, TK, MV, RR, PG), pp. 889–894.

ASE-2017-ReissX #development #editing #execution

A demonstration of simultaneous execution and editing in a development environment (SPR, QX), pp. 895–900.

ASE-2017-SchmidtNF #mining #named #specification

TREM: a tool for mining timed regular specifications from system traces (LS, AN, SF), pp. 901–906.

ASE-2017-ErataGGSLTKM #documentation #framework #named #platform

ModelWriter: text and model-synchronized document engineering platform (FE, CG, BG, AS, YL, BT, GK, AM), pp. 907–912.

ASE-2017-PietschOKK #incremental #slicing

Incrementally slicing editable submodels (CP, MO, UK, TK), pp. 913–918.

ASE-2017-AbateBCCCDKKP #automation #named #physics #synthesis

DSSynth: an automated digital controller synthesis tool for physical plants (AA, IB, DC, LCC, LCC, CD, PK, DK, EP), pp. 919–924.

ASE-2017-WangZJS0S #optimisation #reachability #static analysis

A static analysis tool with optimizations for reachability determination (YW, MZ0, YJ0, XS, MG0, JS), pp. 925–930.

ASE-2017-KrugerNRAMBGGWD #developer #encryption #named #using

CogniCrypt: supporting developers in using cryptography (SK, SN, MR, KA0, MM, EB, FG, FG0, CW, DD, RK), pp. 931–936.

ASE-2017-CorradiniFP0TV17a #named #process #tool support #verification

BProVe: tool support for business process verification (FC, FF, AP, BR0, FT, AV), pp. 937–942.

ASE-2017-KjolstadCLKA #algebra #kernel #named

taco: a tool to generate tensor algebra kernels (FK, SC, DL, SK, SPA), pp. 943–948.

ASE-2017-LegunsenSM #named #testing

STARTS: STAtic regression test selection (OL, AS, DM), pp. 949–954.

ASE-2017-SaddlerC #generative #named #testing #user interface

EventFlowSlicer: a tool for generating realistic goal-driven GUI tests (JAS, MBC), pp. 955–960.

ASE-2017-MeftahGRC #in the large #mobile #named #peer-to-peer #testing

ANDROFLEET: testing WiFi peer-to-peer mobile apps in the large (LM, MG0, RR, IC), pp. 961–966.

ASE-2017-AsaduzzamanRSH #framework #named #recommendation

FEMIR: a tool for recommending framework extension examples (MA, CKR, KAS, DH), pp. 967–972.

ASE-2017-LinL0CGLLMR #interface #named #natural language #query

TiQi: a natural language interface for querying software project data (JL, YL, JG0, JCH, WG, WL, SL, NM, AR), pp. 973–977.

ASE-2017-UddinK17a #api #named #summary

Opiner: an opinion search and summarization engine for APIs (GU, FK), pp. 978–983.

ASE-2017-KhatchadourianM #automation #java #refactoring

Defaultification refactoring: a tool for automatically converting Java methods to default (RK, HM), pp. 984–989.

ASE-2017-GrigeraGR #as a service #named #usability #web

Kobold: web usability as a service (JG, AG, GR), pp. 990–995.

ASE-2017-ChengZS0S #automation #fault #integer #named #type inference

IntPTI: automatic integer error repair with proper-type inference (XC, MZ0, XS, MG0, JS), pp. 996–1001.

ASE-2017-Krishna #effectiveness #learning

Learning effective changes for software projects (RK), pp. 1002–1005.

ASE-2017-Wang #debugging #javascript #nondeterminism

Characterizing and taming non-deterministic bugs in JavaScript applications (JW), pp. 1006–1009.

ASE-2017-Nielebock #automation #program repair #towards

Towards API-specific automatic program repair (SN0), pp. 1010–1013.

ASE-2017-Li #evolution #semantics #slicing

Managing software evolution through semantic history slicing (YL0), pp. 1014–1017.

ASE-2017-Mills #automation #classification #towards #traceability

Towards the automatic classification of traceability links (CM), pp. 1018–1021.

ASE-2017-Sultana #metric #predict #towards #using

Towards a software vulnerability prediction model using traceable code patterns and software metrics (KZS), pp. 1022–1025.

ASE-2017-Busari #analysis #architecture #modelling #requirements #search-based #towards

Towards search-based modelling and analysis of requirements and architecture decisions (SAB), pp. 1026–1029.

ASE-2017-Guerriero #data-driven #privacy

Privacy-aware data-intensive applications (MG), pp. 1030–1033.