Static Race Detection

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Static Race Detection. Nov 19, 2012 CS 8803 FPL. The Hardware Concurrency Revolution. Clock speeds have peaked But #transistors continues to grow exponentially Vendors are shipping multi-core processors. Intel CPU Introductions . The Software Concurrency Revolution.
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Static Race DetectionNov 19, 2012CS 8803 FPLThe Hardware Concurrency Revolution
  • Clock speeds have peaked
  • But #transistors continues to grow exponentially
  • Vendors are shipping multi-core processors
  • Intel CPU Introductions The Software Concurrency Revolution
  • Until now:Increasing clock speeds =>even sequential programs ran faster
  • Henceforth:Increasing #CPU cores =>only concurrent programs will run faster
  • Reasoning about Concurrent Programs is Hardt1 = x;t1 = t1 + 1;x = t1;t2 = x;t2 = t2 + 1;x = t2;x==kx==kx==kt1=xt2=xt1=xt1++t2++t2=xx=t1x=t2t2++. . .t2=xt1=xx=t2(20 total)t2++t1++t1++x=t2x=t1x=t1x==k+2 x==k+1x==k+2Race ConditionsThe same location may be accessed by different threads simultaneously.(And at least one access is a write.)Race Conditions
  • Particularly insidious concurrency bug
  • Triggered non-deterministically
  • No fail-stop behavior even in safe languages like Java
  • Fundamental in concurrency theory and practice
  • Lies at heart of many concurrency problems
  • atomicity checking, deadlock detection, ...
  • Today’s concurrent programs riddled with races
  • “… most Java programs are so rife with concurrency bugs that they work only ‘by accident’.” – Brian Goetz, Java Concurrency in Practice, Addison-Wesley, 2006
  • ExampleLocking for Race Freedomsync (l) {t1 = x;t1 = t1 + 1;x = t1;sync (l) {The same location may be accessed by different threads simultaneously without holding a common lock.(And at least one access is a write.)The same location may be accessed by different threads simultaneously.(And at least one access is a write.)t2 = x;t2 = t2 + 1;x = t2;}}x==kx==kx==kt1=xt2=xt1=xt1++t2++t2=xx=t1x=t2t2++. . .t2=xt1=xx=t2(20 total)t2++t1++t1++x=t2x=t1x=t1x==k+2 x==k+1x==k+2Previous Work
  • Allen & Padua 1987; Miller & Choi 1988; Balasundaram & Kennedy 1989; Karam et al. 1989; Emrath et al. 1989; Schonberg 1989; …
  • Dinning & Schonberg 1990; Hood et al. 1990; Choi & Min 1991; Choi et al. 1991; Netzer & Miller 1991; Netzer & Miller 1992; Sterling 1993; Mellor-Crummey 1993; Bishop & Dilger 1996; Netzer et al. 1996; Savage et al. 1997; Cheng et al. 1998; Richards & Larus 1998; Ronsse & De Bosschere 1999; Flanagan & Abadi 1999; …
  • Aiken et al. 2000; Flanagan & Freund 2000; Christiaens & Bosschere 2001; Flanagan & Freund 2001; von Praun & Gross 2001; Choi et al. 2002; Engler & Ashcraft 2003; Grossman 2003; O’Callahan & Choi 2003; Pozniansky & Schuster 2003; von Praun & Gross 2003; Agarwal & Stoller 2004; Flanagan & Freund 2004; Henzinger et al. 2004; Nishiyama 2004; Qadeer & Wu 2004; Yu et al. 2005; Sasturkar et al. 2005; Elmas et al. 2006; Pratikakis et al. 2006; Sen & Agha 2006; Zhou et al. 2007; ...
  • Observation: Existing techniques and tools findrelatively few bugsOur Results
  • 392 bugs in mature Java programs comprising 1.5 MLOC
  • Many fixed within a week by developers
  • Our Race Detection Approachall pairsracing pairsChallenges
  • Handle multiple aspects
  • Same location accessed
  • … by different threads
  • … simultaneously
  • Correlate locks with locations they guard
  • … without common lock held
  • Same location accessedby different threadssimultaneouslywithout common lock held
  • Precision
  • Showed precise may alias analysisis central (PLDI’06)
  • low false-positive rate (20%)
  • Soundness
  • Devised conditional must not alias analysis (POPL’07)
  • Circumvents must alias analysis
  • Our Race Detection Approachall pairsaliasing pairsshared pairsparallel pairsunlocked pairsracing pairsFalse Pos. Rate: 20% Same location accessedby different threadssimultaneouslywithout common lock heldAlias Analysis for Race Detection
  • Field f is race-free if:
  • // Thread 1:// Thread 2:sync (l1) {sync (l2) {… e1.f …… e2.f …}}e1 and e2never refer to the same value¬ MAY-ALIAS(e1, e2)MUST-NOT-ALIAS(e1, e2)k-Object-Sensitive May Alias AnalysisMay Alias Analysis
  • Large body of work
  • Idea #1: Context-insensitive analysis
  • Abstract value = set of allocation sites
  • foo() {bar() {… e1.f …… e2.f …}}¬ MAY-ALIAS(e1, e2) if Sites(e1) ∩Sites(e2) = ∅
  • Idea #2: Context-sensitive analysis (k-CFA)
  • Context (k=1) = call site
  • foo() {bar() {e1.baz();e2.baz();}} Analyze function baz in two contexts
  • Recent may alias analysis [Milanova et al. ISSTA’03]
  • Solution:
  • Problem: Too few abstract values!
  • Abstract value = set of strings of ≤ k allocation sites
  • Problem: Too few or too many contexts!
  • Solution:
  • Context (k=1) = allocation site of this parameter
  • k-Object-Sensitive Analysis: Our Contributions
  • No scalable implementations for even k = 1
  • Insights:
  • Symbolic representation of relations
  • BDDs [Whaley-Lam PLDI’04, Lhotak-Hendren PLDI’04]
  • Demand-driven race detection algorithm
  • Begin with k = 1 for all allocation sites
  • Increment k only for those involved in races
  • Allow scalability to k = 5
  • Our Race Detection Approachall pairsaliasing pairsshared pairsparallel pairsunlocked pairsracing pairs Same location accessedby different threadssimultaneouslywithout common lock heldAlias Analysis for Race Detection
  • Field f is race-free if:
  • // Thread 1:// Thread 2:sync (l1) {sync (l2) {… e1.f …… e2.f …}}e1 and e2never refer to the same value¬ MAY-ALIAS(e1, e2)ORl1 and l2always refer to the same valueMUST-ALIAS(l1, l2)Must Alias Analysis
  • Small body of work
  • Much harder problem than may alias analysis
  • Impediment to many previous race detection approaches
  • Folk wisdom: Static race detection is intractable
  • Insight: Must alias analysis not necessary forrace detection!New Idea: Conditional Must Not Alias Analysis
  • Field f is race-free if:
  • // Thread 1:// Thread 2:sync (l1) {sync (l2) {… e1.f …… e2.f …}}Whenever l1 and l2 refer to different values, e1 and e2also refer to different valuesMUST-NOT-ALIAS(l1, l2) => MUST-NOT-ALIAS(e1, e2)a[0]a[N-1]a[i]h1h1……h1gggh2……h2h2Examplea = new h0[N];for (i = 0; i < N; i++) { a[i] = new h1; a[i].g = new h2;}h0x1 = a[*];sync (?) { x1.g.f = …;}x2 = a[*];sync (?) { x2.g.f = …;}h0a[0]a[N-1]a[i]h1h1……h1gggh2……h2h2Easy Case: Coarse-grained Lockinga = new h0[N];for (i = 0; i < N; i++) { a[i] = new h1; a[i].g = new h2;}x1 = a[*];sync (a) { x1.g.f = …;}x2 = a[*];sync (a) { x2.g.f = …;}Field f is race-free if:trueMUST-NOT-ALIAS(a, a) => MUST-NOT-ALIAS(x1.g, x2.g)MUST-NOT-ALIAS(l1, l2) => MUST-NOT-ALIAS(e1, e2)h0a[0]a[N-1]a[i]h1h1……h1gggh2……h2h2Examplea = new h0[N];for (i = 0; i < N; i++) { a[i] = new h1; a[i].g = new h2;}x1 = a[*];sync (?) { x1.g.f = …;}x2 = a[*];sync (?) { x2.g.f = …;}h0a[0]a[N-1]a[i]h1h1……h1gggh2……h2h2Easy Case: Fine-grained Lockinga = new h0[N];for (i = 0; i < N; i++) { a[i] = new h1; a[i].g = new h2;}x1 = a[*];sync (x1.g) { x1.g.f = …;}x2 = a[*];sync (x2.g) { x2.g.f = …;}Field f is race-free if:trueMUST-NOT-ALIAS(l1, l2) => MUST-NOT-ALIAS(e1, e2)MUST-NOT-ALIAS(x1.g, x2.g) => MUST-NOT-ALIAS(x1.g, x2.g)h0a[0]a[N-1]a[i]h1h1……h1gggh2……h2h2Examplea = new h0[N];for (i = 0; i < N; i++) { a[i] = new h1; a[i].g = new h2;}x1 = a[*];sync (?) { x1.g.f = …;}x2 = a[*];sync (?) { x2.g.f = …;}h0a[0]a[N-1]a[i]h1h1……h1gggh2……h2h2Hard Case: Medium-grained Lockinga = new h0[N];for (i = 0; i < N; i++) { a[i] = new h1; a[i].g = new h2;}x1 = a[*];sync (x1) { x1.g.f = …;}x2 = a[*];sync (x2) { x2.g.f = …;}Field f is race-free if:true(fieldg of distinct h1 values linked to distinct h2 values)MUST-NOT-ALIAS(x1, x2) => MUST-NOT-ALIAS(x1.g, x2.g)MUST-NOT-ALIAS(l1, l2) => MUST-NOT-ALIAS(e1, e2)h0a[0]a[N-1]a[i]h1h1…………h1gggh2…………h2h2h0►►►h1h1h1►►►h2h2h2Disjoint Reachability
  • from distincth1 values
  • we can reach (via 1 or more fields)
  • only distincth2 values
  • In every execution, if:then {h2} ⊆ DR({h1})Note: Values abstracted by sets of allocation sitesConditional Must Not Alias Analysis usingDisjoint ReachabilitySites(l1)Sites(l2)// Thread 1:// Thread 2:sync (l1) {sync (l2) { … e1.f …… e2.f …}}⊆ DRSites(e1)Sites(e2)Field f is race-free if:
  • (Sites(e1) ∩Sites(e2)) ⊆ DR(Sites(l1) ∪Sites(l2))
  • e1 reachable from l1 and e2 reachable from l2
  • MUST-NOT-ALIAS(l1, l2) => MUST-NOT-ALIAS(e1, e2)h0a[0]a[N-1]a[i]h1h1……h1gggh2……h2h2Hard Case: Medium-grained Lockinga = new h0[N];for (i = 0; i < N; i++) { a[i] = new h1; a[i].g = new h2;}x1 = a[*];sync (x1) { x1.g.f = …;}x2 = a[*];sync (x2) { x2.g.f = …;}Field f is race-free if:
  • (Sites(e1) ∩Sites(e2)) ⊆ DR(Sites(l1) ∪Sites(l2))
  • e1 reachable from l1 and e2 reachable from l2
  • (Sites(x1.g) ∩Sites(x2.g)) ⊆ DR(Sites(x1) ∪Sites(x2))
  • x1.g reachable from x1 and x2.g reachable from x2
  • true
  • true
  • ({h2}) ⊆ DR({h1})
  • x1.g reachable from x1 and x2.g reachable from x2
  • Experience with Chord
  • Experimented with 12 multi-threaded Java programs
  • smaller programs used in previous work
  • larger, mature and widely-used open-source programs
  • whole programs and libraries
  • Tool output and developer discussions available at: http://www.cs.stanford.edu/~mhn/chord.html
  • Programs being used by other researchers in race detection
  • vect1.1htbl1.1htbl1.4vect1.4tsphedcftppooljdbmjdbfjtdsderbyBenchmarksclasses19213663703704224933884614655531746KLOC3375767683103124115122165646descriptionJDK 1.1 java.util.VectorJDK 1.1 java.util.HashtableJDK 1.4 java.util.HashtableJDK 1.4 java.util.VectorTraveling Salesman ProblemWeb crawlerApache FTP serverApache object pooling libraryTransaction managerO/R mapping systemJDBC driverApache RDBMStime0m28s0m27s2m04s2m02s3m03s9m10s11m17s10m29s9m33s9m42s10m23s36m03sPairs Retained After Each Stage (Log scale)vect1.1htbl1.1htbl1.4vect1.4tsphedcftppooljdbmjdbfjtdsderbyClassification of Unlocked Pairsharmful500071704510591130341018benign126900031000140false000044123137341778# bugs100016121721816319Developer Feedback
  • 16 bugs in jTDS
  • Before: “As far as we know, there are no concurrency issues in jTDS …”
  • After: “It is probably the case that the whole synchronization approach in jTDS should be revised from scratch ...”
  • 17 bugs in Apache Commons Pool
  • “Thanks to an audit by Mayur Naik many potential synchronization issues have been fixed” -- Release notes for Commons Pool 1.3
  • 319 bugs in Apache Derby
  • “This looks like *very* valuable information and I for one appreciate you using Derby … Could this tool be run on a regular basis? It is likely that new races could get introduced as new code is submitted ...”
  • Related Work
  • Static (compile-time) race detection
  • Need to approximate multiple aspects
  • Need to perform must alias analysis
  • Sacrifice precision, soundness, scalability
  • Dynamic (run-time) race detection
  • Current state of the art
  • Inherently unsound
  • Cannot analyze libraries
  • Shape Analysis
  • much more expensive than disjoint reachability
  • Summary of Contributions
  • Precise race detection (PLDI’06)
  • Key idea: k-object-sensitive may alias analysis
  • Important client for may alias analyses
  • Sound race detection (POPL’07)
  • Key idea: Conditional must not alias analysis
  • Has applications besides race detection
  • Effective race detection
  • 392 bugs in mature Java programs comprising 1.5 MLOC
  • Many fixed within a week by developers
  • Related Search
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