Marianne Huchard, Christian Kästner, Gordon Fraser
Proceedings of the 33rd International Conference on Automated Software Engineering
ASE, 2018.

@proceedings{ASE-2018,
	doi           = "10.1145/3238147",
	editor        = "Marianne Huchard and Christian Kästner and Gordon Fraser",
	publisher     = "{ACM}",
	title         = "{Proceedings of the 33rd International Conference on Automated Software Engineering}",
	year          = 2018,
}

Contents (112 items)

ASE-2018-Cosmo #source code

Software heritage: collecting, preserving, and sharing all our source code (keynote) (RDC), pp. 1–2.

ASE-2018-Cleland-Huang #automation #challenge #requirements

Automated requirements engineering challenges with examples from small unmanned aerial systems (keynote) (JCH), p. 3.

ASE-2018-Herckis #implementation #re-engineering #research

Implementation science for software engineering: bridging the gap between research and practice (keynote) (LH), p. 4.

ASE-2018-Murphy #re-engineering

The need for context in software engineering (IEEE CS Harlan Mills award keynote) (GCM), p. 5.

ASE-2018-HabchiBR #android #on the #performance

On adopting linters to deal with performance concerns in Android apps (SH, XB0, RR), pp. 6–16.

ASE-2018-HanYL #debugging #learning #named #performance

PerfLearner: learning from bug reports to understand and generate performance test frames (XH, TY, DL0), pp. 17–28.

ASE-2018-BaoLXF #automation #distributed #named

AutoConfig: automatic configuration tuning for distributed message systems (LB, XL0, ZX, BF), pp. 29–40.

ASE-2018-HabibP #documentation #graph #learning #thread #using

Is this class thread-safe? inferring documentation using graph-based learning (AH, MP), pp. 41–52.

ASE-2018-Hilton0M #evolution #scalability #test coverage

A large-scale study of test coverage evolution (MH, JB0, DM), pp. 53–63.

ASE-2018-TerragniP #challenge #concurrent #effectiveness #generative #testing #thread

Effectiveness and challenges in generating concurrent tests for thread-safe classes (VT, MP), pp. 64–75.

ASE-2018-KonatEV #dependence #incremental #scalability

Scalable incremental building with dynamic task dependencies (GK, SE, EV), pp. 76–86.

ASE-2018-GallabaM0M #empirical

Noise and heterogeneity in historical build data: an empirical study of Travis CI (KG, CM, MP0, SM), pp. 87–97.

ASE-2018-UdeshiAC #automation #testing

Automated directed fairness testing (SU, PA, SC0), pp. 98–108.

ASE-2018-SunWRHKK #network #testing

Concolic testing for deep neural networks (YS, MW, WR, XH0, MK, DK), pp. 109–119.

ASE-2018-MaJZSXLCSLLZW #learning #multi #named #testing

DeepGauge: multi-granularity testing criteria for deep learning systems (LM0, FJX, FZ, JS, MX, BL0, CC, TS, LL0, YL0, JZ, YW), pp. 120–131.

ASE-2018-ZhangZZ0K #framework #named #testing #validation

DeepRoad: GAN-based metamorphic testing and input validation framework for autonomous driving systems (MZ, YZ, LZ, CL0, SK), pp. 132–142.

ASE-2018-AbdessalemPNBS #feature model #interactive #testing #using

Testing autonomous cars for feature interaction failures using many-objective search (RBA, AP, SN, LCB, TS), pp. 143–154.

ASE-2018-MukelabaiNMBS #case study #combinator #configuration management #explosion #industrial

Tackling combinatorial explosion: a study of industrial needs and practices for analyzing highly configurable systems (MM, DN, SM, TB, JPS), pp. 155–166.

ASE-2018-He0WZLX #android #comprehension #detection

Understanding and detecting evolution-induced compatibility issues in Android apps (DH, LL0, LW, HZ, GL, JX), pp. 167–177.

ASE-2018-HeCHL #natural language

Characterizing the natural language descriptions in software logging statements (PH, ZC, SH, MRL), pp. 178–189.

ASE-2018-OreEDK

Assessing the type annotation burden (JPO, SGE, CD, LK), pp. 190–201.

ASE-2018-KovalenkoPB #branch #mining #question

Mining file histories: should we consider branches? (VK, FP, AB), pp. 202–213.

ASE-2018-HuangCXLL #comparison #difference

Tell them apart: distilling technology differences from crowd-scale comparison discussions (YH, CC, ZX, TL, YL0), pp. 214–224.

ASE-2018-Shen000ML #named #regular expression

ReScue: crafting regular expression DoS attacks (YS, YJ0, CX0, PY0, XM, JL0), pp. 225–235.

ASE-2018-LiuWX #android #control flow #named

TDroid: exposing app switching attacks in Android with control flow specialization (JL0, DW, JX), pp. 236–247.

ASE-2018-FadhelBB #data access #modelling #policy #runtime

Model-driven run-time enforcement of complex role-based access control policies (ABF, DB, LCB), pp. 248–258.

ASE-2018-JiangLC #contract #detection #fuzzing #named

ContractFuzzer: fuzzing smart contracts for vulnerability detection (BJ, YL, WKC), pp. 259–269.

ASE-2018-ReissXH #development #editing #execution #named

SEEDE: simultaneous execution and editing in a development environment (SPR, QX, JH0), pp. 270–281.

ASE-2018-LiuHN #api #effectiveness #recommendation #repository

Effective API recommendation without historical software repositories (XL, LH, VN), pp. 282–292.

ASE-2018-HuangXXLW #api #recommendation

API method recommendation without worrying about the task-API knowledge gap (QH, XX0, ZX, DL0, XW0), pp. 293–304.

ASE-2018-ChenSXHJ #approach #automation #execution #metric #test coverage

An automated approach to estimating code coverage measures via execution logs (BC, JS, PX, XH, ZM(J), pp. 305–316.

ASE-2018-HabibP18a #case study #debugging #detection #how

How many of all bugs do we find? a study of static bug detectors (AH, MP), pp. 317–328.

ASE-2018-SharifAGZ #named

TRIMMER: application specialization for code debloating (HS, MA, AG, FZ), pp. 329–339.

ASE-2018-HelmKERM #analysis #framework

A unified lattice model and framework for purity analyses (DH, FK, ME, MR, MM), pp. 340–350.

ASE-2018-ChenH #control flow #smt #verification

Control flow-guided SMT solving for program verification (JC, FH), pp. 351–361.

ASE-2018-NagashimaH #higher-order #named #proving #recommendation

PaMpeR: proof method recommendation system for Isabelle/HOL (YN, YH), pp. 362–372.

ASE-2018-LiuXHLXW #commit #generative #how #question

Neural-machine-translation-based commit message generation: how far are we? (ZL, XX0, AEH, DL0, ZX, XW0), pp. 373–384.

ASE-2018-LiuXZ #detection #learning

Deep learning based feature envy detection (HL, ZX, YZ), pp. 385–396.

ASE-2018-WanZYXY0Y #automation #learning #source code #summary

Improving automatic source code summarization via deep reinforcement learning (YW, ZZ, MY0, GX, HY, JW0, PSY), pp. 397–407.

ASE-2018-ChaLO #learning #online #testing

Template-guided concolic testing via online learning (SC, SL, HO), pp. 408–418.

ASE-2018-GaoTDR #android #execution #symbolic computation #testing

Android testing via synthetic symbolic execution (XG, SHT, ZD, AR), pp. 419–429.

ASE-2018-DustmannWC #execution #multi #named #symbolic computation

PARTI: a multi-interval theory solver for symbolic execution (OSD, KW, CC), pp. 430–440.

ASE-2018-Mora0RC #equivalence

Client-specific equivalence checking (FM, YL0, JR, MC), pp. 441–451.

ASE-2018-Arora0IKR #debugging

Replay without recording of production bugs for service oriented applications (NA, JB0, FI, GEK, BR), pp. 452–463.

ASE-2018-AlizadehK #clustering #interactive #multi #refactoring

Reducing interactive refactoring effort via clustering-based multi-objective search (VA, MK), pp. 464–474.

ASE-2018-LemieuxS #named #testing

FairFuzz: a targeted mutation strategy for increasing greybox fuzz testing coverage (CL, KS), pp. 475–485.

ASE-2018-FanSCMLXP #android #fault #programming

Efficiently manifesting asynchronous programming errors in Android apps (LF, TS, SC, GM, YL0, LX, GP), pp. 486–497.

ASE-2018-DouHXZ0 #identification #spreadsheet

Expandable group identification in spreadsheets (WD, SH, LX, DZ, JW0), pp. 498–508.

ASE-2018-Lin0TBWD #debugging #slicing

Break the dead end of dynamic slicing: localizing data and control omission bug (YL0, JS0, LT, GB, HW, JSD), pp. 509–519.

ASE-2018-DegiovanniMRA #algorithm #identification #search-based

A genetic algorithm for goal-conflict identification (RD, FM, GR, NA), pp. 520–531.

ASE-2018-HuangWLC #android #comprehension #detection

Understanding and detecting callback compatibility issues for Android applications (HH, LW, YL, SCC), pp. 532–542.

ASE-2018-MoranWHPP #detection #evolution #mobile #user interface

Detecting and summarizing GUI changes in evolving mobile apps (KM, CW, JH, GP, DP), pp. 543–553.

ASE-2018-ZhaoWLM #empirical #mobile

Empirically assessing opportunities for prefetching and caching in mobile apps (YZ, PW, MSL, NM), pp. 554–564.

ASE-2018-SteinCSC #programming #refinement

Safe stream-based programming with refinement types (BS0, LC, MS, BYEC), pp. 565–576.

ASE-2018-WangSK #alloy #automation

Automated model repair for Alloy (KW, AS, SK), pp. 577–588.

ASE-2018-LinWLSZW #concurrent #data access #debugging #memory management #named

PFix: fixing concurrency bugs based on memory access patterns (HL, ZW, SL, JS0, DZ, GW), pp. 589–600.

ASE-2018-BajammalM0 #component #generative #reuse #web

Generating reusable web components from mockups (MB, DM, AM0), pp. 601–611.

ASE-2018-TonderKG #semantics

Semantic crash bucketing (RvT, JK, CLG), pp. 612–622.

ASE-2018-WangCYJ #analysis #approach #constraints #model checking #string

A symbolic model checking approach to the analysis of string and length constraints (HEW, SYC, FY, JHRJ), pp. 623–633.

ASE-2018-BeyerF #concurrent #independence #model checking #multi #thread

Domain-independent multi-threaded software model checking (DB, KF), pp. 634–644.

ASE-2018-Yin0LW #abstraction #constraints #memory management #modelling #refinement #scheduling

Scheduling constraint based abstraction refinement for weak memory models (LY, WD0, WL, JW0), pp. 645–655.

ASE-2018-SungLEW #concurrent #difference #scalability #semantics #source code

Datalog-based scalable semantic diffing of concurrent programs (CS, SKL, CE, CW0), pp. 656–666.

ASE-2018-LiuHZLLPZ #detection #named #similarity

αDiff: cross-version binary code similarity detection with DNN (BL, WH, CZ0, WL, FL, AP, WZ), pp. 667–678.

ASE-2018-HuangCPZWLZ #difference #generative #named

ClDiff: generating concise linked code differences (KH, BC0, XP0, DZ, YW, YL0, WZ), pp. 679–690.

ASE-2018-YanDWW0Z #android #identification #process

Characterizing and identifying misexposed activities in Android applications (JY, XD, PW, TW, JY0, JZ), pp. 691–701.

ASE-2018-HuWLCH #android #debugging #how

A tale of two cities: how WebView induces bugs to Android applications (JH, LW, YL, SCC, HH), pp. 702–713.

ASE-2018-TangZPAM0Z #comprehension #execution #named

Dual-force: understanding WebView malware via cross-language forced execution (ZT, JZ, MP, YA, SM, XZ0, JZ), pp. 714–725.

ASE-2018-HammadGM #android #communication #component #self

Self-protection of Android systems from inter-component communication attacks (MH, JG, SM), pp. 726–737.

ASE-2018-WangLYCZDX #android #case study #empirical #generative #industrial #testing #tool support

An empirical study of Android test generation tools in industrial cases (WW, DL0, WY0, YC, ZZ, YD, TX0), pp. 738–748.

ASE-2018-GafurovHM #automation #industrial #testing

Achieving test automation with testers without coding skills: an industrial report (DG, AEH, MM), pp. 749–756.

ASE-2018-CashmanCRC #navigation

Navigating the maze: the impact of configurability in bioinformatics software (MC, MBC, PR, RWC), pp. 757–767.

ASE-2018-BugariuWC0 #abstract domain #automation #implementation #testing

Automatically testing implementations of numerical abstract domains (AB, VW, MC, PM0), pp. 768–778.

ASE-2018-MoSCRKN #analysis #architecture #automation #case study #experience

Experiences applying automated architecture analysis tool suites (RM, WS, YC, SR, RK, MN), pp. 779–789.

ASE-2018-VassalloPBG #quality #question

Continuous code quality: are we (really) doing that? (CV, FP, AB, HCG), pp. 790–795.

ASE-2018-HassanRW #analysis #named #recommendation

RUDSEA: recommending updates of Dockerfiles via software environment analysis (FH, RR, XW), pp. 796–801.

ASE-2018-ZhouPX0LJD #debugging

Delta debugging microservice systems (XZ, XP0, TX, JS0, WL, CJ, DD), pp. 802–807.

ASE-2018-Ye0WW #crowdsourcing #developer #personalisation #recommendation

Personalized teammate recommendation for crowdsourced software developers (LY, HS0, XW, JW), pp. 808–813.

ASE-2018-LiuLZJS #contract #named #security #semantics #towards

S-gram: towards semantic-aware security auditing for Ethereum smart contracts (HL, CL, WZ, YJ0, JS), pp. 814–819.

ASE-2018-WangBC #alloy #approach #specification

An evolutionary approach for analyzing Alloy specifications (JW, HB, MBC), pp. 820–825.

ASE-2018-ChenZ #framework #retrieval #source code #summary

A neural framework for retrieval and summarization of source code (QC, MZ), pp. 826–831.

ASE-2018-TufanoWBPWP #empirical #learning

An empirical investigation into learning bug-fixing patches in the wild via neural machine translation (MT, CW, GB, MDP, MW, DP), pp. 832–837.

ASE-2018-GaoL #reduction

Loop path reduction by state pruning (JG, SSL), pp. 838–843.

ASE-2018-QuLCJCHZ #2d #fault #named #network #predict #using

node2defect: using network embedding to improve software defect prediction (YQ, TL0, JC, YJ, DC, AH, QZ), pp. 844–849.

ASE-2018-PatwardhanSSKG #ambiguity #automation #towards #using

Towards automating disambiguation of regulations: using the wisdom of crowds (MP, AS, RS, SK, SG), pp. 850–855.

ASE-2018-PereiraSCS #java #named

jStanley: placing a green thumb on Java collections (RP, PS, JC, JS), pp. 856–859.

ASE-2018-HaririS #c #mutation testing #named #representation #source code #testing #tool support

SRCIROR: a toolset for mutation testing of C source code and LLVM intermediate representation (FH, AS), pp. 860–863.

ASE-2018-OzdemirTEA #lightweight #monitoring #source code

Lightweight source code monitoring with Triggr (AO, AT, HE, RA), pp. 864–867.

ASE-2018-ScalabrinoGNGLG #c #generative #named #search-based #testing

OCELOT: a search-based test-data generation tool for C (SS, GG, DDN, MG, ADL, HCG, RO), pp. 868–871.

ASE-2018-GrigeraGGR #refactoring #version control #web

Live versioning of web applications through refactoring (JG, JCG, AG, GR), pp. 872–875.

ASE-2018-JanesMR #developer #lens #named

code_call_lens: raising the developer awareness of critical code (AJ, MM, BR), pp. 876–879.

ASE-2018-GharibiTL #automation #generative #graph #named #python #source code

Code2graph: automatic generation of static call graphs for Python source code (GG, RT, YL), pp. 880–883.

ASE-2018-BrunelCCM #first-order #model checking #relational #specification

The electrum analyzer: model checking relational first-order temporal specifications (JB, DC, AC, NM), pp. 884–887.

ASE-2018-GadelhaMMC0N #c #model checking

ESBMC 5.0: an industrial-strength C model checker (MYRG, FRM, JM, LCC, BF0, DAN), pp. 888–891.

ASE-2018-CaoLP #automation #named #verification

L-CMP: an automatic learning-based parameterized verification tool (JC, YL, JP0), pp. 892–895.

ASE-2018-GaoYFJS #learning #named #platform #semantics

VulSeeker: a semantic learning based vulnerability seeker for cross-platform binary (JG, XY, YF, YJ0, JS), pp. 896–899.

ASE-2018-BeyerL #execution #named #performance #symbolic computation

CPA-SymExec: efficient symbolic execution in CPAchecker (DB, TL), pp. 900–903.

ASE-2018-SungPW #analysis #framework #named

CANAL: a cache timing analysis framework via LLVM transformation (CS, BP, CW0), pp. 904–907.

ASE-2018-Vera-PerezMB #detection #named #pseudo #tool support

Descartes: a PITest engine to detect pseudo-tested methods: tool demonstration (OLVP, MM, BB), pp. 908–911.

ASE-2018-RoohitavafK #agile #distributed #framework #named #prototype

DKVF: a framework for rapid prototyping and evaluating distributed key-value stores (MR, SSK), pp. 912–915.

ASE-2018-BorgesHZ #android #framework #generative #named #platform #testing

DroidMate-2: a platform for Android test generation (NPBJ, JH, AZ), pp. 916–919.

ASE-2018-Haindl #functional

Assessing and evaluating functional suitability of software (PH), pp. 920–923.

ASE-2018-Krismayer #automation #constraints #mining #monitoring

Automatic mining of constraints for monitoring systems of systems (TK), pp. 924–927.

ASE-2018-Diarra #automation #kernel #strict #towards

Towards automatic restrictification of CUDA kernel arguments (RD), pp. 928–931.

ASE-2018-Galinier #approach #domain-specific language #requirements

A DSL for requirements in the context of a seamless approach (FG), pp. 932–935.

ASE-2018-Traini #distributed #effectiveness #fault #framework #injection #multi #performance

A multi-objective framework for effective performance fault injection in distributed systems (LT), pp. 936–939.

ASE-2018-Sferruzza #modelling #top-down #web #web service

Top-down model-driven engineering of web services from extended OpenAPI models (DS), pp. 940–943.

ASE-2018-Noller #difference #execution #fuzzing #program analysis #symbolic computation

Differential program analysis with fuzzing and symbolic execution (YN), pp. 944–947.

ASE-2018-Delplanque #database #re-engineering #relational

Software engineering techniques applied to relational databases (JD), pp. 948–951.

ASE-2018-AlmasriTK #automation

Automatically quantifying the impact of a change in systems (journal-first abstract) (NA, LT0, BK), p. 952.

ASE-2018-FalessiPCC #traceability

Estimating the number of remaining links in traceability recovery (journal-first abstract) (DF, MDP, GC, GC), p. 953.

ASE-2018-MonteiroGCF #bound #c++ #framework #model checking #platform #source code

Bounded model checking of C++ programs based on the Qt cross-platform framework (journal-first abstract) (FRM, MAPG, LCC, EBdLF), p. 954.

ASE-2018-AcciolyBC #comprehension #java #open source

Understanding Semi-structured merge conflict characteristics in open-source Java projects (journal-first abstract) (PRGA, PB, GC), p. 955.