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points-to
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Tag #points-to

76 papers:

ECOOPECOOP-2019-Bastani0CAA #analysis #specification
Eventually Sound Points-To Analysis with Specifications (OB, RS0, LC, SA, AA), p. 28.
ECOOPECOOP-2018-SmaragdakisK #analysis #effectiveness #lazy evaluation
Defensive Points-To Analysis: Effective Soundness via Laziness (YS, GK), p. 28.
OOPSLAOOPSLA-2018-JeonJO #analysis #data-driven #precise #scalability
Precise and scalable points-to analysis via data-driven context tunneling (MJ, SJ, HO), p. 29.
OOPSLAOOPSLA-2018-RamaKS #analysis #refinement #slicing
Refinement in object-sensitivity points-to analysis via slicing (GMR, RK, HS), p. 27.
PLDIPLDI-2018-Bastani0AL #learning #specification
Active learning of points-to specifications (OB, RS0, AA, PL), pp. 678–692.
CCCC-2018-ZhaoBS #analysis #parallel
Parallel sparse flow-sensitive points-to analysis (JZ, MGB, VS), pp. 59–70.
OOPSLAOOPSLA-2017-GrechS #analysis #named
P/Taint: unified points-to and taint analysis (NG, YS), p. 28.
OOPSLAOOPSLA-2017-JeongJCO #analysis #context-sensitive grammar #data-driven
Data-driven context-sensitivity for points-to analysis (SJ, MJ, SDC, HO), p. 28.
PLDIPLDI-2017-TanLX #analysis #automaton #modelling #performance #precise
Efficient and precise points-to analysis: modeling the heap by merging equivalent automata (TT0, YL0, JX), pp. 278–291.
SASSAS-2016-BalatsourasS #analysis #c #c++
Structure-Sensitive Points-To Analysis for C and C++ (GB, YS), pp. 84–104.
SASSAS-2016-GharatKM #analysis #graph #using
Flow- and Context-Sensitive Points-To Analysis Using Generalized Points-To Graphs (PMG, UPK, AM), pp. 212–236.
OOPSLAOOPSLA-2015-DietrichHS #analysis #java
Giga-scale exhaustive points-to analysis for Java in under a minute (JD, NH, BS), pp. 535–551.
CCCC-2015-AllenSK #analysis #scalability #staged
Staged Points-to Analysis for Large Code Bases (NA, BS, PK), pp. 131–150.
SEKESEKE-2014-WanZWS #analysis #graph #performance
Efficient Points-To Analysis for Partial Call Graph Construction (ZW, BZ, YW, YS), pp. 416–421.
ECOOPECOOP-2014-WeiR #analysis #behaviour #javascript
State-Sensitive Points-to Analysis for the Dynamic Behavior of JavaScript Objects (SW, BGR), pp. 1–26.
ISMMISMM-2014-RatnakarN #analysis #constraints #graph #performance
Push-pull constraint graph for efficient points-to analysis (BR, RN), pp. 25–33.
VMCAIVMCAI-2014-Fu #abstract domain #analysis #java #scalability
Modularly Combining Numeric Abstract Domains with Points-to Analysis, and a Scalable Static Numeric Analyzer for Java (ZF), pp. 282–301.
OOPSLAOOPSLA-2013-SmaragdakisBK #analysis #preprocessor
Set-based pre-processing for points-to analysis (YS, GB, GK), pp. 253–270.
PLDIPLDI-2013-KastrinisS #analysis #context-sensitive grammar #hybrid
Hybrid context-sensitivity for points-to analysis (GK, YS), pp. 423–434.
SACSAC-2013-CiraciV #code generation
Exploiting points-to maps for de-/serialization code generation (SC, OV), pp. 1712–1719.
CCCC-2013-KastrinisS #analysis #effectiveness #exception #java #performance
Efficient and Effective Handling of Exceptions in Java Points-to Analysis (GK, YS), pp. 41–60.
CCCC-2013-LuSXX #analysis #incremental
An Incremental Points-to Analysis with CFL-Reachability (YL, LS, XX, JX), pp. 61–81.
SCAMSCAM-2012-GutzmannLL #analysis #framework
Collections Frameworks for Points-To Analysis (TG, JL, WL), pp. 4–13.
ECOOPECOOP-2012-SridharanDCST #analysis #correlation #javascript
Correlation Tracking for Points-To Analysis of JavaScript (MS, JD, SC, MS, FT), pp. 435–458.
ASEASE-2012-IbrahimGHA #ambiguity #analysis #kernel #operating system #using
Supporting operating system kernel data disambiguation using points-to analysis (ASI, JG, JHHH, MA), pp. 234–237.
ASEASE-2012-Shang0X #analysis #experience #incremental #performance #precise #summary
Fast and precise points-to analysis with incremental CFL-reachability summarisation: preliminary experience (LS, YL, JX), pp. 270–273.
CCCC-2012-PuttaN #analysis #parallel
Parallel Replication-Based Points-To Analysis (SP, RN), pp. 61–80.
CGOCGO-2012-ShangXX #analysis #on-demand
On-demand dynamic summary-based points-to analysis (LS, XX, JX), pp. 264–274.
ISMMISMM-2012-Nasre #analysis #constraints #graph #performance
Exploiting the structure of the constraint graph for efficient points-to analysis (RN), pp. 121–132.
PPoPPPPoPP-2012-Mendez-LojoBP #analysis #gpu #implementation
A GPU implementation of inclusion-based points-to analysis (MML, MB, KP), pp. 107–116.
POPLPOPL-2011-LhotakC #analysis #performance
Points-to analysis with efficient strong updates (OL, KCAC), pp. 3–16.
ESEC-FSEESEC-FSE-2011-LiCK #analysis #performance #using
Boosting the performance of flow-sensitive points-to analysis using value flow (LL, CC, NK), pp. 343–353.
SACSAC-2011-GutzmannLL #analysis
Feedback-driven points-to analysis (TG, JL, WL), pp. 1341–1342.
CCCC-2011-SunZC #analysis #java #probability
Probabilistic Points-to Analysis for Java (QS, JZ, YC), pp. 62–81.
CGOCGO-2011-NasreG #analysis #constraints #evaluation #performance
Prioritizing constraint evaluation for efficient points-to analysis (RN, RG), pp. 267–276.
ISSTAISSTA-2011-XiaoZ #analysis #encoding #geometry #java #performance
Geometric encoding: forging the high performance context sensitive points-to analysis for Java (XX, CZ), pp. 188–198.
OOPSLAOOPSLA-2010-Mendez-LojoMP #analysis #parallel
Parallel inclusion-based points-to analysis (MML, AM, KP), pp. 428–443.
SASSAS-2010-NasreG #analysis #equation #linear
Points-to Analysis as a System of Linear Equations (RN, RG), pp. 422–438.
SCAMSCAM-2009-GutzmannKLL #analysis #towards
Towards Comparing and Combining Points-to Analyses (TG, AK, JL, WL), pp. 45–54.
ECOOPECOOP-2009-XuRS #alias #analysis #scalability #using
Scaling CFL-Reachability-Based Points-To Analysis Using Context-Sensitive Must-Not-Alias Analysis (G(X, AR, MS), pp. 98–122.
OOPSLAOOPSLA-2009-BravenboerS #analysis #declarative #specification #strict
Strictly declarative specification of sophisticated points-to analyses (MB, YS), pp. 243–262.
SACSAC-2009-JangC #analysis #javascript
Points-to analysis for JavaScript (DJ, KMC), pp. 1930–1937.
ISSTAISSTA-2009-BravenboerS #analysis #exception
Exception analysis and points-to analysis: better together (MB, YS), pp. 1–12.
SCAMSCAM-2008-LundbergGL #analysis #performance #precise
Fast and Precise Points-to Analysis (JL, TG, WL), pp. 133–142.
SCAMSCAM-2008-SunZ #analysis
Aspect-Aware Points-to Analysis (QS, JZ), pp. 143–152.
ISSTAISSTA-2008-XuR #analysis #scalability
Merging equivalent contexts for scalable heap-cloning-based context-sensitive points-to analysis (G(X, AR), pp. 225–236.
PASTEPASTE-2007-Milanova #analysis #java
Light context-sensitive points-to analysis for java (AM), pp. 25–30.
SCAMSCAM-2007-GutzmannLL #analysis #towards
Towards Path-Sensitive Points-to Analysis (TG, JL, WL), pp. 59–68.
PLDIPLDI-2007-LattnerLA #analysis
Making context-sensitive points-to analysis with heap cloning practical for the real world (CL, AL, VSA), pp. 278–289.
PLDIPLDI-2006-SridharanB #analysis #java
Refinement-based context-sensitive points-to analysis for Java (MS, RB), pp. 387–400.
CCCC-2006-LhotakH #analysis #question
Context-Sensitive Points-to Analysis: Is It Worth It? (OL, LJH), pp. 47–64.
OOPSLAOOPSLA-2005-SridharanGSB #analysis #java
Demand-driven points-to analysis for Java (MS, DG, LS, RB), pp. 59–76.
PPDPPPDP-2005-SahaR #analysis #incremental #logic programming #using
Incremental and demand-driven points-to analysis using logic programming (DS, CRR), pp. 117–128.
PLDIPLDI-2003-BerndlLQHU #analysis #using
Points-to analysis using BDDs (MB, OL, FQ, LJH, NU), pp. 103–114.
CCCC-2003-LhotakH #analysis #java #scalability #using
Scaling Java Points-to Analysis Using SPARK (OL, LJH), pp. 153–169.
PPoPPPPoPP-2003-ChenHHJL #analysis #architecture #compilation #multi #probability #thread
Compiler support for speculative multithreading architecture with probabilistic points-to analysis (PSC, MYH, YSH, RDCJ, JKL), pp. 25–36.
SCAMSCAM-J-2001-AndersonBRT02 #set
Flow insensitive points-to sets (PA, DB, GR, TT), pp. 743–754.
SASSAS-2002-WhaleyL #analysis #performance #strict
An Efficient Inclusion-Based Points-To Analysis for Strictly-Typed Languages (JW, MSL), pp. 180–195.
FSEFSE-2002-BrunsC #analysis
Searching for points-to analysis (GB, SC), pp. 61–70.
FSEFSE-2002-MockACE #slicing
Improving program slicing with dynamic points-to data (MM, DCA, CC, SJE), pp. 71–80.
ISSTAISSTA-2002-MilanovaRR #analysis #java
Parameterized object sensitivity for points-to and side-effect analyses for Java (AM, AR, BGR), pp. 1–11.
PASTEPASTE-2001-LiangPH #analysis #java
Extending and evaluating flow-insenstitive and context-insensitive points-to analyses for Java (DL, MP, MJH), pp. 73–79.
PASTEPASTE-2001-MockDCE #analysis #comparison #comprehension #optimisation #set
Dynamic points-to sets: a comparison with static analyses and potential applications in program understanding and optimization (MM, MD, CC, SJE), pp. 66–72.
SCAMSCAM-2001-AndersonBRT #set
Flow Insensitive Points-To Sets (PA, DB, GR, TT), pp. 81–91.
OOPSLAOOPSLA-2001-RountevMR #analysis #constraints #java #using
Points-To Analysis for Java using Annotated Constraints (AR, AM, BGR), pp. 43–55.
PLDIPLDI-2001-GhiyaLS #ambiguity #analysis #c #memory management #on the #source code
On the Importance of Points-to Analysis and Other Memory Disambiguation Methods for C Programs (RG, DML, DCS), pp. 47–58.
CCCC-2001-RountevR #analysis #library #source code
Points-to and Side-Effect Analyses for Programs Built with Precompiled Libraries (AR, BGR), pp. 20–36.
PLDIPLDI-2000-RouhtevC #analysis #scalability
Off-line variable substitution for scaling points-to analysis (AR, SC), pp. 47–56.
SASSAS-2000-FosterFA #analysis #c #polymorphism
Polymorphic versus Monomorphic Flow-Insensitive Points-to Analysis for C (JSF, MF, AA), pp. 175–198.
CSMRCSMR-1999-Tonella #analysis #set
Effects of Different Flow Insensitive Points-to Analyses on DEF/USE Sets (PT), pp. 62–71.
ESECESEC-FSE-1999-LiangH #performance #program analysis
Efficient Points-to Analysis for Whole-Program Analysis (DL, MJH), pp. 199–215.
WPCWPC-1997-TonellaAFM #analysis #comprehension
Points-to Analysis for Program Understanding (PT, GA, RF, EM), pp. 90–99.
POPLPOPL-1997-ShapiroH #analysis #performance
Fast and Accurate Flow-Insensitive Points-To Analysis (MS, SH), pp. 1–14.
POPLPOPL-1996-Steensgaard #analysis #linear
Points-to Analysis in Almost Linear Time (BS), pp. 32–41.
CCCC-1996-Steensgaard #analysis #source code #type inference
Points-to Analysis by Type Inference of Programs with Structures and Unions (BS), pp. 136–150.
PLDIPLDI-1994-EmamiGH #analysis #interprocedural #pointer
Context-Sensitive Interprocedural Points-to Analysis in the Presence of Function Pointers (ME, RG, LJH), pp. 242–256.

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