ESP [Das et al PLDI 2002] Interface usage rules in documentation –Order of operations, data access –Resource management –Incomplete, wordy, not checked.

ESP [Das et al PLDI 2002] Interface usage rules in documentation –Order of operations, data access –Resource management –Incomplete, wordy, not checked Violated rules ) crashes –Failed runtime checks –Unreliable software CleanL TSys DSL DFA WP/SP MC ATP

ESP [Das et al PLDI 2002] C Program Safe Not Safe Rules ESP CleanL TSys DSL DFA WP/SP MC ATP

ESP [Das et al PLDI 2002] ESP is a program analysis that keeps track of object state at each program point –e.g.: is file handle open or closed? Challenge: scale to large programs –One of scalability issues: merge nodes –Always analyze both sides of merge node ) exponential (or non-terminating) program analyses ESP has a heuristic for handling merges that –avoids exponential blow-up and runs fast in practice –maintains enough precision to verify programs CleanL TSys DSL DFA WP/SP MC ATP

4 Prop Sim example: stdio usage in gcc void main () { if (dump) fil = fopen(dumpFile,”w”); if (p) x = 0; else x = 1; if (dump) fclose(fil); }

5 Prop Sim example: stdio usage in gcc void main () { if (dump) Open; if (p) x = 0; else x = 1; if (dump) Close; }

6 Prop Sim example: stdio usage in gcc $uninit Opened $error Open Print Open Close Print/Close * void main () { if (dump) Open; if (p) x = 0; else x = 1; if (dump) Close; }

7 Example: no path-sensitivity entry dump p x = 0x = 1 Open Close exit dump T T T F F F

8 Example: no path-sensitivity {$uninit,Opened} {$error,$uninit,Opened} {$uninit} {$uninit,Opened} entry dump p x = 0x = 1 Open Close exit dump T T T F F F

9 Example: full path-sensitivity entry dump p x = 0x = 1 Open Close exit dump T T T F F F

11 Example: ESP technique entry dump p x = 0x = 1 Open Close exit dump T T T F F F

13 Case study: stdio usage in gcc cc1 from gcc version 2.5.3 (Spec95) Does cc1 always print to opened files? cc1 is a complex program: –140K non-blank, non-comment lines of C –2149 functions, 66 files, 1086 globals –Call graph includes one 450 function SCC

14 Experimental results Precision –Verification succeeds for every file handle –No transitions to $error ; no false errors Scalability –Average per handle: 72.9 seconds, 49.7 MB –Single 1GHz PIII laptop with 512 MB RAM Proved that: –Each of the 646 calls to fprintf in the source code prints to a valid, open file

15 ESP follow-up ESP has since been run on large real-world applications ESP/X: local intra-procedural version PSE: post-mortem analysis –run ESP backwards to figure out what cause a crash

Recap and conclusion

Course overview Dataflow analysis and variations iterative dataflow analysis program representations interprocedural flow-insensitive path-sensitive Cross-cutting issues Correctness Ordering transformations and analyses Applications Pointer analysis Optimizing OO languages Program reliability Rhodium

Flow-sensitive intraproc dataflow analysis Iterative dataflow analysis –flow functions, lattice-theoretic formulation Termination –monotonic flow functions + finite height lattice Meet over all paths vs. meet over all feasible paths vs. dataflow analysis –For distributive problems, MOP = dataflow analysis

Program representations Simple –AST –CFG More advanced –Dataflow Graph –Control Dependence Graph –Program Dependence Graph –SSA

Interprocedural analysis Context insensitive –caller summaries and callee summaries Context-sensitive –call-strings as context (k-CFA, “call-strings”) –dataflow info as context bottom-up, complete summaries top-down, partial summaries (partial transfer functions)

Flow-insensitive analysis Keep only one piece of information for the entire program/procedure Loses precision, but improves space consumption

Path-sensitive analysis Enhance dataflow to try to keep paths separate Two kinds of path-sensitive analysis: –aim towards MOP –aim towards removing infeasible paths (branch correlations)

Applications Pointer analysis Optimizing OO languages Program reliability Rhodium Course overview Dataflow analysis and variations iterative dataflow analysis program representations interprocedural flow-insensitive path-sensitive Cross-cutting issues Correctness Ordering transformations and analyses

Pointer analysis Started with simple naïve intraproc analysis with allocation site summaries To scale to large programs: –make naïve pointer analysis flow insensitive (Andersen) –make each node have only one outgoing edge, which makes it near linear time (Steensgaard) –add one level of flow to regain some precision (One- level flow)

Applications Pointer analysis Optimizing OO languages Program reliability Rhodium Course overview Dataflow analysis and variations iterative dataflow analysis program representations interprocedural flow-insensitive path-sensitive Cross-cutting issues Correctness Ordering transformations and analyses

Course overview Dataflow analysis and variations iterative dataflow analysis program representations interprocedural flow-insensitive path-sensitive Applications Pointer analysis Optimizing OO languages Program reliability Rhodium Cross-cutting issues Correctness Ordering transformations and analyses

Program analysis and program reliability Property simulation –path sensitive analysis in polynomial time –uses clever heuristic for merges –algorithm behind ESP Predicate abstraction and iterative refinement –given set of predicates, compute predicates that hold at each program point –iteratively refine set of predicates –core of BLAST and SLAM

Course overview Dataflow analysis and variations iterative dataflow analysis program representations interprocedural flow-insensitive path-sensitive Applications Pointer analysis Optimizing OO languages Program reliability Rhodium Cross-cutting issues Correctness Ordering transformations and analyses

Looking forward (discussion) What are the current hot topics in compilers and program analysis? Compilers and program analysis in 20 years from now?

Looking forward: Concurrency Hardware trends are making exploiting concurrency more and more important Language features and compiler technology to express and exploit concurrency Current examples: –race detection –primitives for concurrency and efficient implementations (eg: atomic primitive)

Looking forward: Scalability Scale to large programs while retaining precision Current examples: –Use scalable constraint solvers such as SAT (SATURN) –Use compact representations such as BDDs

Looking forward: Verification Tradeoffs between: –automation –scalability –precision –domain-specificity Current examples –ESP, BLAST, SLAM, Rhodium

Looking forward: Extensibility Removing barrier to entry to the compiler New models of using compilers for –domain-specific checkers –domain-specific optimizations Current examples: –Rhodium, Collider

ESP [Das et al PLDI 2002] Interface usage rules in documentation –Order of operations, data access –Resource management –Incomplete, wordy, not checked.

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ESP [Das et al PLDI 2002] Interface usage rules in documentation –Order of operations, data access –Resource management –Incomplete, wordy, not checked.

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