Margaret-Anne D. Storey, Bram Adams, Sonia Haiduc
Proceedings of the 16th Working Conference on Mining Software Repositories
MSR, 2019.

@proceedings{MSR-2019,
	acmid         = "3341883",
	editor        = "Margaret-Anne D. Storey and Bram Adams and Sonia Haiduc",
	ee            = "https://ieeexplore.ieee.org/xpl/conhome/8804710/proceeding",
	isbn          = "978-1-7281-3412-3",
	publisher     = "{IEEE / ACM}",
	title         = "{Proceedings of the 16th Working Conference on Mining Software Repositories}",
	year          = 2019,
}

Contents (79 items)

MSR-2019-AkbarK #named #order #retrieval #semantics #source code

SCOR: source code retrieval with semantics and order (SAA, ACK), pp. 1–12.

MSR-2019-KovalenkoBBB #library #mining #named

PathMiner: a library for mining of path-based representations of code (VK, EB, TB, AB), pp. 13–17.

MSR-2019-TheetenVC #learning #library

Import2vec learning embeddings for software libraries (BT, FV, TVC), pp. 18–28.

MSR-2019-EfstathiouS #identifier #modelling #semantics #source code #using

Semantic source code models using identifier embeddings (VE, DS), pp. 29–33.

MSR-2019-HoangDK0U #fault #framework #learning #named #predict

DeepJIT: an end-to-end deep learning framework for just-in-time defect prediction (TH, HKD, YK, DL0, NU), pp. 34–45.

MSR-2019-DamPN0GGKK #fault #lessons learnt #predict #using

Lessons learned from using a deep tree-based model for software defect prediction in practice (HKD, TP, SWN, TT0, JCG, AG, TK, CJK), pp. 46–57.

MSR-2019-KiehnPC #classification #empirical #using #version control

Empirical study in using version histories for change risk classification (MK, XP, FC), pp. 58–62.

MSR-2019-AhluwaliaFP #dataset #fault #named #predict

Snoring: a noise in defect prediction datasets (AA, DF, MDP), pp. 63–67.

MSR-2019-BiswasVP #analysis #re-engineering #sentiment #word

Exploring word embedding techniques to improve sentiment analysis of software engineering texts (EB, KVS, LLP), pp. 68–78.

MSR-2019-RahmanRPN #stack overflow

Cleaning StackOverflow for machine translation (MR, PCR, DP, TNN), pp. 79–83.

MSR-2019-Treude0 #git #modelling #predict #stack overflow #topic

Predicting good configurations for GitHub and stack overflow topic models (CT, MW0), pp. 84–95.

MSR-2019-WickertREDM #dataset #encryption #parametricity

A dataset of parametric cryptographic misuses (AKW, MR, ME, AD, MM), pp. 96–100.

MSR-2019-RaghuramanHCSV #empirical #fault #modelling #uml

Does UML modeling associate with lower defect proneness?: a preliminary empirical investigation (AR, THQ, MRVC, AS, BV), pp. 101–104.

MSR-2019-ChrenMB0 #analysis #automation #named #reliability

STRAIT: a tool for automated software reliability growth analysis (SC, RM, BB, BR0), pp. 105–110.

MSR-2019-Beyer #fault #invariant #set

A data set of program invariants and error paths (DB0), pp. 111–115.

MSR-2019-ZhaiCD #python #source code #test coverage

Test coverage in python programs (HZ, CC, PTD), pp. 116–120.

MSR-2019-SerraGPFGB #automation #effectiveness #generative #on the #testing #years after

On the effectiveness of manual and automatic unit test generation: ten years later (DS, GG, FP, FF, HCG, AB), pp. 121–125.

MSR-2019-MitropoulosLSS #evolution #javascript

Time present and time past: analyzing the evolution of JavaScript code in the wild (DM, PL, VS, DS), pp. 126–137.

MSR-2019-PietriSZ #dataset #development #graph

The software heritage graph dataset: public software development under one roof (AP, DS, SZ), pp. 138–142.

MSR-2019-MaBAZM #framework #mining #open source

World of code: an infrastructure for mining the universe of open source VCS data (YM, CB, SA, RZ, AM), pp. 143–154.

MSR-2019-KolovosNBMP #distributed #framework #mining #named #repository

Crossflow: a framework for distributed mining of software repositories (DSK, PN, KB, NM, RFP), pp. 155–159.

MSR-2019-OliveiraOCF0 #energy #java #recommendation

Recommending energy-efficient Java collections (WO, RO, FC, BF, GP0), pp. 160–170.

MSR-2019-MatalongaCC0PSF #android #energy #mining

GreenHub farmer: real-world data for Android energy mining (HM, BC, FC, MC0, RP, SMdS, JPF), pp. 171–175.

MSR-2019-Rua0S #android #energy #metric #named #scalability #testing

GreenSource: a large-scale collection of Android code, tests and energy metrics (RR, MC0, JS), pp. 176–180.

MSR-2019-TrockmanTV #git #repository

Striking gold in software repositories?: an econometric study of cryptocurrencies on GitHub (AT, RvT, BV), pp. 181–185.

MSR-2019-TonderTG #development #git #process #set

A panel data set of cryptocurrency development activity on GitHub (RvT, AT, CLG), pp. 186–190.

MSR-2019-BaltesT0 #evolution #named #stack overflow

SOTorrent: studying the origin, evolution, and usage of stack overflow code snippets (SB, CT, SD0), pp. 191–194.

MSR-2019-CamposSMB0 #javascript #mining

Mining rule violations in JavaScript code snippets (UC, GS, JPM, RB, GP0), pp. 195–199.

MSR-2019-RahmanFI #stack overflow

Snakes in paradise?: insecure python-related coding practices in stack overflow (AR, EF, NI), pp. 200–204.

MSR-2019-DietrichLD #case study #identification #stack overflow

Man vs machine: a study into language identification of stack overflow code snippets (JD0, MLR, ED), pp. 205–209.

MSR-2019-BafatakisBBSKOW #python #stack overflow

Python coding style compliance on stack overflow (NB, NB, WB, MCS, JK, GO, RW), pp. 210–214.

MSR-2019-DiamantopoulosS #evolution #mining #stack overflow #towards

Towards mining answer edits to extract evolution patterns in stack overflow (TD, MIS, ALS), pp. 215–219.

MSR-2019-SoniN #stack overflow

Analyzing comment-induced updates on stack overflow (AS, SN), pp. 220–234.

MSR-2019-JinS #empirical #stack overflow #what

What edits are done on the highly answered questions in stack overflow?: an empirical study (XJ, FS), pp. 225–229.

MSR-2019-AbricCCGM #community #development #question #stack overflow

Can duplicate questions on stack overflow benefit the software development community? (DA, OEC, MC, KG, SM), pp. 230–234.

MSR-2019-ManesB #developer #git #how #question #stack overflow #what

How often and what StackOverflow posts do developers reference in their GitHub projects? (SSM, OB), pp. 235–239.

MSR-2019-NishiCD #stack overflow

Characterizing duplicate code snippets between stack overflow and tutorials (MAN, AC, KD), pp. 240–244.

MSR-2019-ImtiazRFW #challenge #static analysis

Challenges with responding to static analysis tool alerts (NI, AR, EF, LW), pp. 245–249.

MSR-2019-AhmadC #case study #stack overflow

Impact of stack overflow code snippets on software cohesion: a preliminary study (MA, MÓC), pp. 250–254.

MSR-2019-BandeiraMPM #analysis #stack overflow

We need to talk about microservices: an analysis from the discussions on StackOverflow (AB, CAM, MP, PHMM), pp. 255–259.

MSR-2019-BangashSCWHA #case study #developer #machine learning #ml #stack overflow #what

What do developers know about machine learning: a study of ML discussions on StackOverflow (AAB, HS, SAC, AWW, AH, KA0), pp. 260–264.

MSR-2019-AmannNNNM #detection

Investigating next steps in static API-misuse detection (SA, HAN, SN, TNN, MM), pp. 265–275.

MSR-2019-MontandonSV #framework #git #identification #library

Identifying experts in software libraries and frameworks among GitHub users (JEM, LLS, MTV), pp. 276–287.

MSR-2019-ScalabrinoBLLO #android #api #data-driven #detection #empirical

Data-driven solutions to detect API compatibility issues in Android: an empirical study (SS, GB, MLV, ML, RO), pp. 288–298.

MSR-2019-LiuLZFDQ #commit #generative #network #using

Generating commit messages from diffs using pointer-generator network (QL, ZL, HZ, HF, BD, YQ), pp. 299–309.

MSR-2019-AlqaimiTT #automation #documentation #generative #java

Automatically generating documentation for lambda expressions in Java (AA, PT, CT), pp. 310–320.

MSR-2019-WangPWZ #api #developer

Extracting API tips from developer question and answer websites (SW0, NP, YW, YZ), pp. 321–332.

MSR-2019-Soto-ValeroBHBB

The emergence of software diversity in maven central (CSV, AB, NH, OB, BB), pp. 333–343.

MSR-2019-BenelallamHSBB #dependence #graph #representation

The maven dependency graph: a temporal graph-based representation of maven central (AB, NH, CSV, BB, OB), pp. 344–348.

MSR-2019-0001PSTB #dependence #version control

Dependency versioning in the wild (JD0, DJP, JS, AT, KB), pp. 349–359.

MSR-2019-MatosFR #api #case study

Splitting APIs: an exploratory study of software unbundling (ASM, JBFF, LSR), pp. 360–370.

MSR-2019-LeSB #assessment #automation #concept

Automated software vulnerability assessment with concept drift (THML, BS, MAB), pp. 371–382.

MSR-2019-PontaPSBD #dataset #open source

A manually-curated dataset of fixes to vulnerabilities of open-source software (SEP, HP, AS, MB, CD), pp. 383–387.

MSR-2019-GaoKLBK #android #mining

Negative results on mining crypto-API usage rules in Android apps (JG, PK, LL0, TFB, JK), pp. 388–398.

MSR-2019-RaduN #dataset #debugging #non-functional

A dataset of non-functional bugs (AR, SN), pp. 399–403.

MSR-2019-WangSL0 #android #dataset #metadata #named #reliability #towards

RmvDroid: towards a reliable Android malware dataset with app metadata (HW, JS, HL, YG0), pp. 404–408.

MSR-2019-Zhu0 #email #empirical #multi #repository #version control

An empirical study of multiple names and email addresses in OSS version control repositories (JZ, JW0), pp. 409–420.

MSR-2019-MilewiczPR #open source

Characterizing the roles of contributors in open-source scientific software projects (RM, GP0, PR), pp. 421–432.

MSR-2019-GoteSS #git #mining #named #network #repository #scalability

git2net: mining time-stamped co-editing networks from large git repositories (CG, IS, FS), pp. 433–444.

MSR-2019-HabchiMR #android #question #smell

The rise of Android code smells: who is to blame? (SH, NM, RR), pp. 445–456.

MSR-2019-BleserNR #scala #smell

Assessing diffusion and perception of test smells in scala projects (JDB, DDN, CDR), pp. 457–467.

MSR-2019-MarkovtsevLMSB #algorithm #consistency #named #nondeterminism

STYLE-ANALYZER: fixing code style inconsistencies with interpretable unsupervised algorithms (VM, WL, HM, KS, EB), pp. 468–478.

MSR-2019-Mondal0R #case study #stack overflow

Can issues reported at stack overflow questions be reproduced?: an exploratory study (SM, MMR0, CKR), pp. 479–489.

MSR-2019-ChatterjeeDPAK #case study #mining #re-engineering #tool support

Exploratory study of slack Q&A chats as a mining source for software engineering tools (PC, KD, LLP, VA, NAK), pp. 490–501.

MSR-2019-HayashiHMK #development

Impacts of daylight saving time on software development (JH, YH, SM, SK), pp. 502–506.

MSR-2019-PimentelMBF #quality #scalability

A large-scale study about quality and reproducibility of jupyter notebooks (JFP, LM, VB, JF), pp. 507–517.

MSR-2019-PerezC #abstract syntax tree #clone detection #detection #learning #syntax

Cross-language clone detection by learning over abstract syntax trees (DP, SC), pp. 518–528.

MSR-2019-KampKP #java #named #semantics #set

SeSaMe: a data set of semantically similar Java methods (MK, PK, MP), pp. 529–533.

MSR-2019-YangC0 #behaviour #development #predict #source code #specification

Predicting co-changes between functionality specifications and source code in behavior driven development (AZHY, DAdC, YZ0), pp. 534–544.

MSR-2019-SchipperAD #research

Tracing back log data to its log statement: from research to practice (DS, MFA, AvD), pp. 545–549.

MSR-2019-MatsumotoHK #approach #hybrid

Beyond GumTree: a hybrid approach to generate edit scripts (JM, YH, SK), pp. 550–554.

MSR-2019-FunakiHS #slicing

The impact of systematic edits in history slicing (RF, SH, MS), pp. 555–559.

MSR-2019-Owhadi-KareshkN #scalability

Scalable software merging studies with MergAnser (MOK, SN), pp. 560–564.

MSR-2019-KottiS

Standing on shoulders or feet?: the usage of the MSR data papers (ZK, DS), pp. 565–576.

MSR-2019-BiswasIHR #dataset #python

Boa meets python: a boa dataset of data science software in python language (SB, MJI, YH, HR), pp. 577–581.

MSR-2019-RiganelliMMM #android #benchmark #debugging #metric

A benchmark of data loss bugs for Android apps (OR, MM, DM, LM), pp. 582–586.

MSR-2019-JoshiC #agile #dataset #git #named

RapidRelease: a dataset of projects and issues on github with rapid releases (SDJ, SC), pp. 587–591.

MSR-2019-ZeroualiCRGM #named

ConPan: a tool to analyze packages in software containers (AZ, VC, GR, JMGB, TM), pp. 592–596.

MSR-2019-ScocciaPPCK #android #empirical #open source

An empirical history of permission requests and mistakes in open source Android apps (GLS, AP, VP, BC, DEK), pp. 597–601.