Improving Software Reliability via Static and Dynamic Analysis Tao Xie, Automated Software...
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Transcript of Improving Software Reliability via Static and Dynamic Analysis Tao Xie, Automated Software...
Improving Software Reliability via Static and Dynamic Analysis
Tao Xie, Automated Software Engineering Group
Department of Computer Science
North Carolina State University
http://ase.csc.ncsu.edu/
Group OverviewInputs:• Current funding support
– NSF CyberTrust (3 yrs), NSF SoD (3 yrs), ARO (3 yrs), NIST supplement, IBM Faculty Award, Microsoft Research, ABB Research
• Collaboration with agencies and industry– NIST, NASA, DOE Lab, Army division, Microsoft Research,
IBM Rational, ABB Research
• Current student team– 6 Ph.D. students, 1 M.S. student, 5 probation-staged grad
students
Group Overview cont.Outputs:• Research around two major themes:
– Automated Software Testing; Mining Software Engineering Data
• Industry impact– We found Parasoft Jtest 4.5 generated 90% redundant tests [ASE
04]– Agitar AgitarOne used a similar technique as our Jov [ASE 03]– MSR and NASA adopted Symstra technique [TACAS 05]– MSR Pex adopted our recent techniques
• Research publications– 2008: TOSEM, ICSE, 3*ASE, SIGMETRIC, ISSRE, ICSM, SRDS,
ACSAC, …– 2007: ICSE, FSE, 4*ASE, WWW, ICSM, …– …
Major Research Collaboration Areas
• Mining textual SE data
• Mining program code data
• Automated testing
Mining Textual SE data• Bug reports [ICSE 08]
– Detecting duplicate bug reports– Classifying bug reports
• API documentation• Project documentation
Two duplicate bug reports in Firefox - using only natural language information may fail
• Bug-260331: After closing Firefox, the process is still running. Cannot reopen Firefox after that, unless the previous process is killed manually
• Bug-239223: (Ghostproc) – [Meta] firefox.exe doesn't always exit after closing all windows; session-specific data retained
Two non-duplicate bug reports in Firefox - using only execution information may fail
• Bug-244372: "Document contains no data" message on continuation page of NY Times article
• Bug-219232: random "The Document contains no data." Alerts
• Proposed solution [ICSE 08]: mining both textual information of bug reports and execution information of their failing tests
Classification of Bug Reports
• Bugs related to security issues• Bugs related to design problems• Bugs related to insufficient unit testing• …
Manually label a subset of bug reports with their categories
Apply classification algorithms on unlabeled bug reports to predict their categories
Benefit: reduce manual labeling efforts
Example API Docs
javax.resource.cci.Connection• createInteraction(): “Creates an interaction associated with
this connection”
action-resource pair: create-connection• getMetaData(): “Gets the information on the underlying EIS
instance represented through an active connection” action-resource pair: get-connection
• close(): “Initiates close of the connection handle at the application level” action-resource pair: close-connection
Potential Collaboration Ideas on Text Mining• Documents submitted by device manufacturers are in NL
and are too many or long for manual inspection• Classification problem
– Train learning tools with some labeled documents
• Clustering problem– Without labeling, group documents based on similarity
• Selection problem– Similar to duplicate bug report detection
Potential Collaboration Ideas on Text Mining – Possible Examples• Extract safety-related requirements from documents
manually extract some and then tools recommend some more based on manually extracted ones
• Classify incident reports (e.g., with ontology) manually classify some and then tools recommend categories for the rest
• Detect correlations among incident reports similar to duplicate bug report detection
• Other pre-market textual documents• Other post-market textual documents• …
Major Research Collaboration Areas
• Mining textual SE data
• Mining program code data
• Automated testing
Problem• Software system verification: given properties,
verification tools can be used to detect whether the system violates the properties– Example: malloc return check
• However, these properties often do not exist– Who write these property?– How often these property are written?– How often these property are known?
• Objective: Mine API properties for static verification from the API client code in existing system code bases
Artifacts in Code Mining
•Data: usage info from various code locations of using APIs such as malloc, seteuid, and execl
•Patterns: sequencing constraints among collected API invocation sequences and condition checks
•Anomalies: violations of these patterns as potential defects
Approach Overview
System Code BasesSystem Code Bases
1 2 N…
For each external API
2.Trace/Search
MOPS
• Trace/Search source files that use each external API from existing code
…
Usage Info Around APIs
<cond, API1>...…
3.Analyze
• Analyze collected traces/files to extract usage info around APIs
InputSystem
1.ExtractInternal
APIsExternal
APIs
• Extract external APIs from the input system
Detected Violations as Bugs
5.Verify
• Verify the input system against these properties to detect bugs
Frequent Patternsaround APIs
4.Mine
• Mine frequent usage patterns around APIs as API properties
Example Target Defect Types
• Neglected-condition defects
• Error-handling defects
• Exception-handling defects
• These defect types can result in– Critical security, robustness, reliability issues – Performance degradation
• Example: Failure to release a resource may decrease the performance
Mined Neglected Condition
From Grass open source GIS project
Developer confirmed “I believe this issue has uncovered a bug: the pointer returned by the fopen () call isn't checked at all. The code responsible for this particular issue is surprisingly short, to make it a good example on how not to write the code”
$ nl -ba main.c... 71 fp = fopen("dumpfile", "w"); 72 BM_file_write(fp, map); 73 fclose(fp);...$
Mined Patterns of Error Handling
From Redhat 9.0 routed-0.17-14
Error-check specifications
Multiple-API specifications close() should be called after socket()
If violated, defects are detected
Mined Patterns of Exception Handling
If missing resource cleanup, defects are detected
Resource creation
Resource manipulation
Resource cleanup
Potential Collaboration Ideas on Code Mining• Address problems similar to ones targeted by FDA’s
previous work on “Static Analysis of Medical Device Software using CodeSonar” by Jetley, Jones, and Anderson
• Benefits of our new techniques– Don’t require the code to be compilable (using partial program
analysis)– Don’t require properties to be manually written down– Can accumulate knowledge (API usages) within or across devices
or manufacturers (or even open source world)– May ask manufacturers to submit API usages (if not code itself?)
Potential Collaboration Ideas on Code Mining cont.Our tool development status• Neglected condition bugs: tools for Java and C are ready;
tool for C# is being developed• Error-handling bugs: tool for C is ready• Exception-handling bugs: tool for Java is ready and tool for
C# is being developed• Working on tools for framework reuse bugs
Major Research Collaboration Areas
• Mining textual SE data
• Mining program code data
• Automated testing
Dynamic Symbolic ExecutionDynamic symbolic execution combines static and
dynamic analysis:• Execute program multiple times
with different inputs– build abstract representation of execution path on the
side– plug in concrete results of operations which cannot be
reasoned about symbolically
• Use constraint solver to obtain new inputs– solve constraint system that represents an execution
path not seen before
TestTestInputsInputsTestTest
InputsInputs
Constraint Constraint SystemSystem
Constraint Constraint SystemSystem Execution Execution
PathPathExecution Execution
PathPath
KnownKnownPathsPathsKnownKnownPathsPaths
Run Test and Monitor
RecordPath Condition
Choose an Uncovered Path
Solve
Result: small test suite, Result: small test suite, high code coveragehigh code coverage
Whole-program, white-box code analysis
Initially, choose Arbitrary
Finds only real bugsFinds only real bugsNo false warningsNo false warnings
TestTestInputsInputsTestTest
InputsInputs
Constraint Constraint SystemSystem
Constraint Constraint SystemSystem Execution Execution
PathPathExecution Execution
PathPath
KnownKnownPathsPathsKnownKnownPathsPaths
Run Test and Monitor
RecordPath Condition
Choose an Uncovered Path
Solve
Result: small test suite, Result: small test suite, high code coveragehigh code coverage
Whole-program, white-box code analysis
Initially, choose Arbitrary
Finds only real bugsFinds only real bugsNo false warningsNo false warnings
a[0] = 0;a[1] = 0;a[2] = 0;a[3] = 0;…
a[0] = 0;a[1] = 0;a[2] = 0;a[3] = 0;…
TestTestInputsInputsTestTest
InputsInputs
Constraint Constraint SystemSystem
Constraint Constraint SystemSystem Execution Execution
PathPathExecution Execution
PathPath
KnownKnownPathsPathsKnownKnownPathsPaths
Run Test and Monitor
RecordPath Condition
Choose an Uncovered Path
Solve
Result: small test suite, Result: small test suite, high code coveragehigh code coverage
Initially, choose Arbitrary
Finds only real bugsFinds only real bugsNo false warningsNo false warnings
Path Condition:… ⋀ magicNum != 0x95673948
Whole-program, white-box code analysis
TestTestInputsInputsTestTest
InputsInputs
Constraint Constraint SystemSystem
Constraint Constraint SystemSystem Execution Execution
PathPathExecution Execution
PathPath
KnownKnownPathsPathsKnownKnownPathsPaths
Run Test and Monitor
RecordPath Condition
Choose an Uncovered Path
Solve
Result: small test suite, Result: small test suite, high code coveragehigh code coverage
Initially, choose Arbitrary
Finds only real bugsFinds only real bugsNo false warningsNo false warnings
… ⋀ magicNum != 0x95673948… ⋀ magicNum == 0x95673948
Whole-program, white-box code analysis
TestTestInputsInputsTestTest
InputsInputs
Constraint Constraint SystemSystem
Constraint Constraint SystemSystem Execution Execution
PathPathExecution Execution
PathPath
KnownKnownPathsPathsKnownKnownPathsPaths
Run Test and Monitor
RecordPath Condition
Choose an Uncovered Path
Solve
Result: small test suite, Result: small test suite, high code coveragehigh code coverage
Finds only real bugsFinds only real bugsNo false warningsNo false warnings
a[0] = 206;a[1] = 202;a[2] = 239;a[3] = 190;
a[0] = 206;a[1] = 202;a[2] = 239;a[3] = 190;
Initially, choose Arbitrary
Whole-program, white-box code analysis
TestTestInputsInputsTestTest
InputsInputs
Constraint Constraint SystemSystem
Constraint Constraint SystemSystem Execution Execution
PathPathExecution Execution
PathPath
KnownKnownPathsPathsKnownKnownPathsPaths
Run Test and Monitor
RecordPath Condition
Choose an Uncovered Path
Solve
Result: small test suite, Result: small test suite, high code coveragehigh code coverage
Initially, choose Arbitrary
Finds only real bugsFinds only real bugsNo false warningsNo false warnings
Whole-program, white-box code analysis
Potential Collaboration Ideas on Automated Testing• Address problems similar to ones targeted by FDA’s
previous work on “Static Analysis of Medical Device Software using CodeSonar” by Jetley, Jones, and Anderson
• Benefits of our new techniques (also in contrast to existing testing techniques)– No false positives. Each reported issue is a REAL one– Much more powerful than existing commercial tools (Parasoft
C#Test, Parasoft Jtest, Agitar AgitarOne, …)
Potential Collaboration Ideas on Automated Testing cont.Our tool development status• Most mature/powerful for C# testing (built around MSR Pex
by collaborating with MSR Researchers) • Java testing tools based on NASA Java Pathfinder, jCUTE, • C testing tools based on Crest and Splat
Potential Collaboration Ideas on Automated Testing cont.• Regression test generation/differential testing: Given two
versions, try to find test inputs to show different behavior– Possible idea 1: given a buggy version and claimed fixed version
submitted by manufacturers, generate test inputs to show different behaviors
– Possible idea 2: change impact analysis on models or code submitted by manufacturers
• Use code mining to find targets to violate by testing– Address false positive issues
Other Research Areas
• Mining program execution to aid program understanding, debugging, …
• Mining version histories• Security policy testing• Attack generation• Design testing• Web app/service testing• DB app testing• Performance testing• …