Improving Programmer Productivity via Mining Program Source Code Tao Xie Department of Computer...

Improving Programmer Productivity via Mining Program Source Code

Tao XieDepartment of Computer Science

North Carolina State University

http://ase.csc.ncsu.edu/dmse/


T. Xie Mining Program Source Code 2

Mining SE Data

• MAIN GOAL– Transform static record-

keeping SE data to active data

– Make SE data actionable by uncovering hidden patterns and trends

MailingsBugzilla

Code repository

Executiontraces

CVS


Overview of Mining SE Data

code bases

change history

programstates

structuralentities

software engineering data

bugreports/nl

programming defect detection testing debugging maintenance

software engineering tasks helped by data mining

classificationassociation/

patternsclustering

data mining techniques

…

…

…



code bases

change history

programstates

structuralentities


bugreports/nl …

99 ASE 00 ICSE05 FSE*2 ASE PLDI POPL OSDI06 PLDI OOPSLA KDD07 ICSE*3 FSE*3 ASE PLDI*2 ISSTA*2 KDD

04 ICSE05 FSE*206 ASE07 ICSE*2

99 ICSE02 ICSE03 PLDI05 FSE PLDI06 ISSTA07 ISSTA

99 FSE 01 ICSE FSE02 ISSTA POPL KDD03 PLDI04 ASE ISSTA05 ICSE ASE 06 ICSE FSE*207 PLDI

03 ICSE06 ICSE06 ASE07 ICSE SOSP



code bases

change history

programstates

structuralentities


bugreports/nl




patternsclustering


…

…

…





…

99 ASE00 ICSE05 FSE PLDI POPL06 FSE OOPSLA PLDI07 FSE ASE ISSTA KDD

01 SOSP04 OSDI05 FSE*206 ICSE*207 ICSE*2 FSE*2 ISSTA PLDI*2 SOSP

99 ICSE01 ICSE*2 FSE02 ICSE ISSTA POPL04 ISSTA06 ISSTA

03 ICSE PLDI*2 05 ICSE FSE ASE PLDI06 ICSE FSE07 ICSE ISSTA PLDI

02 KDD04 ICSE ASE05 FSE ASE*206 KDD07 ICSE*3



code bases

change history

programstates

structuralentities


bugreports/nl




patternsclustering


…

…

…


Sample Projects on Mining Program Source Code

Data Algorithms TasksSet of functions, variables, etc. in a C function

FrequentItemset

Programming-rules-related bug finding UIUC [FSE 05]

Statement seq in a basic block in C

Frequent subsequence Copy-paste bug finding

UIUC [OSDI 04]Methods seq in a Java method from code search engine

Frequent subsequence API usage patterns

NCSU [MSR 06] Function seq in whole C program

Frequent partial order

API usage patterns/properties

NCSU [FSE 07] System dependence graph in whole C program

Frequent subgraph

Neglected-condition bug finding CASE [ISSTA 07]

Java API method signatures

Plan generation API Jungloids Berkeley [PLDI 05]

Method seq in a Java method from code search engine

Frequent sequences

API Jungloids NCSU [ASE 07]


Some Recent Trends

• Data: dynamic execution data +static code bases

• Task: productivity (programming) + quality (defect detection, testing, debugging)

• Mining algorithm: simple ones (association rule) + frequent itemset/subsequence/ partial order/subgraph

• Data scope: local repositories public repositories with code search engines




Frequentitemset










Frequent subgraph





Frequent sequences



Mining API Usage Patterns

• How should an API be used correctly?– An API may serve multiple functionalities– Different styles of API usage

• MAPO: “I know what method call I need, but I don’t know how to write code before and after this method call” [Xie&Pei MSR 06]


Example Task -- MAPO

• “instrument the bytecode of a Java class by adding an extra method to the class”– org.apache.bcel.generic.ClassGen public void addMethod(Method m)


First Try: ClassGen Java API Doc

addMethod

public void addMethod(Method m) Add a method to this class.

Parameters:

m - method to add


Second Try: Code Search Engine


MAPO Approach

• Analyze code segments relevant to a given API and disclose the inherent usage patterns– Input: an API characterized by a method, class, or

package– Code search engine: used to search relevant source

files from open source repositories – Frequent sequence miner: use BIDE [Wang&Han 04] to

mine closed sequential patterns from extracted method-call sequences

– Output: a short list of frequent API usage patterns related to the API


Sequence Extraction

• Method sequences: extracted from Java source files returned from code search engines

public void generateStubMethod(ClassGen c) InstructionList il = new InstructionList(); MethodGen m= genFromISList(il); m.setMaxLocals(); m.setMaxStack(); c.addMethod(m.getMethod()); System.out.println(“…”); …

}

Call sequenceSource code

InstructionList.<init>()

genFromISList(InstructionList)

MethodGen.setMaxStack()

MethodGen.setMaxLocals()

MethodGen.getMethod()

ClassGen.addMethod(Method)PrintStream.println(String) …


Sequence Preprocessing

• Remove common Java library calls

• Inline callees of the same class• Remove sequences that contain no query

words: ClassGen and addMethod


genFromISList(InstructionList)




ClassGen.addMethod(Method)PrintStream.println(String) …

public void generateStubMethod(ClassGen c) InstructionList il = new InstructionList(); MethodGen m= genFromISList(il); m.setMaxLocals(); m.setMaxStack(); c.addMethod(m.getMethod()); System.out.println(“…”); …

}


Frequent Seq Postprocessing

• Remove sequences that contain no query words: ClassGen and addMethod

• Compress consecutive calls of the same method into one, e.g., abbba aba

• Remove duplicate frequent sequences after the compression, e.g., aba, aba aba

• Reduce a seq if it is a subseq of another, e.g., aba, abab abab


Tool Architecture

e.g. koders.com


Sample Mined API Sequence


InstructionFactory.createLoad(Type, int)

InstructionList.append(Instruction)

InstructionFactory.createReturn(Type)

InstructionList.append(Instruction)




ClassGen.addMethod(Method)

InstructionList.dispose()




Frequentitemset










Frequent subgraph





Frequent sequences





• Apiartor: “I know what possible set of APIs I need, but I don’t know what need to be used and what orders to use” [Acharya et al. FSE 07]


Usage Patterns as Partial Order#include <abcdef.h>void p ( ) { b ( ); c ( ); }void q ( ) { c ( ); b ( ); }void r ( ) { e ( ); f ( ); }void s ( ) { f ( ); e ( ); }

int main ( ) { int i, j, k; a ( ); if ( i == 1) { f ( ); e ( ); c ( ); exit ( ); } else { if ( j == 1 ) p ( ); else q ( ); d ( ); if ( k == 1 ) r ( ); else s ( ); } }

1 a f e c2 a b c d e f3 a c b d e f4 a b c d f e5 a c b d f e

a

d

c

e

b

f

a b d e a b d fa c d ea c d f

(b) Static program traces

(c) Frequent subseq patterns

(d) Frequent partial order R(a) Example code


Apiartor Overview

User-specified

APIs

Trigger Generator

Triggers

Model Checker

Traces

Scenario Extractor

Independent Scenarios

Miner

Partial Orders

Source Code

Specification Extractor

Specifications

FrequentUsage

Scenarios

Rel

ated

AP

Is

Trace Generator


Example Partial Orders

XOpenDisplay

XCloseDisplay

XCreateWindow

XGetWindowAttributes

XCreateGC

XSetForeground

XGetBackground

XMapWindow

XChageWindowAttributes

XMapWindow

XSelectInput

XGetAtomName

XFreeGC

XNextEvent

A usage scenario around XOpenDisplay API as apartial order.

Specifications are shown with dotted lines.




Frequentitemset










Frequent subgraph





Frequent sequences





• Apiartor: “I know what possible set of APIs I need, but I don’t know what need to be used and what orders to use” [Acharya et al. FSE 07]

• PARSEWeb: “I know what type of object I need, but I don’t know how to write the code to get the object” [Thummalapenta&Xie ASE 07]

T. Xie Mining Program Source Code

Example Task - OpenJMS

• Query: “javax.jms.QueueConnectionFactory ->

javax.jms.QueueSender”• PARSEWeb Solution:FileName:0_UserBean.java MethodName:ingest Rank:1 NumberOfOccurrences:23

Confidence:True Path: 1 2 3

javax.jms.QueueConnectionFactory,createQueueConnection() ReturnType:javax.jms.QueueConnection

javax.jms.QueueConnection,createQueueSession(boolean,javax.jms.Session.AUTO ACKNOWLEDGE) ReturnType:javax.jms.QueueSession

javax.jms.QueueSession,createSender(javax.jms.Queue)

ReturnType:javax.jms.QueueSender

Sun Java Message Services API Spec


PARSEWeb Overview

Code Downloader

Code Search Engine

Open Source Repositories

Local SourceCode Repository

Code Analyzer

MethodInvocationSequences

SequenceMiner

ClusteredMethod Invocation

Sequences

QuerySplitter

Final MethodInvocationSequences

Query


PARSEWeb Overview

Code Downloader

Code Search Engine



Code Analyzer


SequenceMiner


Sequences

QuerySplitter


Query


Code Analyzer

• Collect [Source Destination] method sequences invoked by each public method– Deal with local method calls by inlining methods– Deal with conditionals/loops by traversing

control flow graphs

• Resolve types in sequences– Challenges: downloaded files are partial– Solutions: heuristics are developed


Type Heuristics

• Heuristic 1: The return type of a method-invocation statement contained in an initialization expression is same as the type of the declared variable.

e.g., QueueConnection connect; QueueSession session = connect.createQueueSession(false,int)

• Heuristic 2: The return type of an outer most method-invocation contained in a return statement is same as the return type of the enclosing method declaration.

e.g., public int test(){

...return connect.createQueueSession(false,int);

}


PARSEWeb Overview

Code Downloader

Code Search Engine



Code Analyzer


SequenceMiner


Sequences

QuerySplitter


Query


Sequence Miner

• Candidate sequences produced by the code analyzer may be too many

Solutions:

• Cluster similar sequences– Clustering heuristics are developed

• Rank sequences– Ranking heuristics are developed


Clustering Heuristics

• Heuristic 1: Method-invocation sequences with the same set of statements can be considered similar, although the statements are in different order.e.g., ''2 3 4 5'' and ''2 4 3 5 ''

• Heuristic 2: Method-invocation sequences differing by given cluster precision value can be considered similar.e.g., ''8 9 6 7'' and ''8 6 10 7 '' can be considered similar under cluster precision value one.


Ranking Heuristics

• Heuristic 1: Higher frequency -> Higher rank

• Heuristic 2: Shorter length -> Higher rank


PARSEWeb Overview

Code Downloader

Code Search Engine



Code Analyzer


SequenceMiner


Sequences

QuerySplitter


Query


Query Splitter

• Lack of code samples in the results of code search engines– Code samples are split among different files

Solution:• Split the user query into multiple queries• Compose the results for each split query


Query Splitting Example1. User query: “org.eclipse.jface.viewers.IStructuredSelection->java.io.ObjectInputStream”

Results: None

2. Query: “java.io.ObjectInputStream”

Results: 3.

Most used sources are: java.io.InputStream, java.io.ByteArrayInputStream, java.io.FileInputStream

3. Three Queries to be fired:

“org.eclipse.jface.viewers.IStructuredSelection-> java.io.InputStream”

Results: 1

“org.eclipse.jface.viewers.IStructuredSelection-> java.io.ByteArrayInputStream”

Results: 5

“org.eclipse.jface.viewers.IStructuredSelection-> java.io.FileInputStream”

Results: None


Eclipse Plugin


Evaluations• Real Programming Problems: To address problems posted

in developer forums.

• Real Projects: To show that solutions recommended by PARSEWeb are – available in real projects – better than solutions recommended by related tools PROSPECTOR,

Strathcona, Google Code Search Engine averagely


Jakarta BCEL User Forum

• Jakarta BCEL user forum, 2001

Problem: “How to disassemble java byte code”

Query: “Code Instruction”

Solution Sample Code: Code code;

InstructionList il = new InstructionList(code.getCode());

Instruction[] ins = il.getInstructions();


Dev2Dev Newsgroups• Dev 2 Dev Newsgroups, 2006

Problem: “how to connect db by sesseionBean”

Query: javax.naming.InitialContext java.sql.Connection

Solution Sequence: FileName:3 AddressBean.java MethodName:getNextUniqueKey Rank:1

NumberOfOccurrences:34javax.naming.InitialContext,lookup(java.lang.String)

ReturnType:javax.sql.DataSourcejavax.sql.DataSource,getConnection()

ReturnType:java.sql.Connection


Challenges in Mining Code• Sometimes too few data samples

– Scalability is usually not an issue– Static code bases vs. change histories

• Data preparation/preprocessing– Related to traditional program analysis

• Pattern postprocessing (filtering and ranking)– Heuristics play important roles

• Demand-driven mining vs. any gold mining– Programming vs. bug finding


Conclusion• Mining various types of software engineering data

to aid software engineering task

• Mining program source code to improve programmer productivity– MAPO: mining API usage patterns for a given API– Apiartor: mining API usage patterns for a given set of

APIs– PARSEWeb: mining API usage patterns for input-

output-type quries

Questions?

Mining Software Engineering Data Bibliography http://ase.csc.ncsu.edu/dmse/•What software engineering tasks can be helped by data mining?•What kinds of software engineering data can be mined?•How are data mining techniques used in software engineering?•Resources


http://ase.csc.ncsu.edu/dmse/setasks.html

http://ase.csc.ncsu.edu/dmse/sedata.html

http://ase.csc.ncsu.edu/dmse/miningalgs.html

http://ase.csc.ncsu.edu/dmse/resources.html


Demand-Driven Or Not

Any-gold mining

Demand-driven mining

Examples DynaMine, … MAPO, BugTriage, …

Advantages Surface up only cases that are applicable

Exploit demands to filter out irrelevant information

Issues How much gold is good enough given the amount of data to be mined?

How high percentage of cases would work well?


Code vs. Non-Code

Code/Programming Langs

Non-Code/Natural Langs

Examples MAPO, DynaMine, … BugTriage, CVS/Code comments, emails, docs

Advantages Relatively stable and consistent representation

Common source of capturing programmers’ intentions

Issues What project/context-specific heuristics to use?


Static vs. Dynamic

Static Data: code bases, change histories

Dynamic Data: prog states, structural profiles

Examples MAPO, DynaMine, … Spec discovery, …

Advantages No need to set up exec environment;

More scalable

More-precise info

Issues How to reduce false positives?

How to reduce false negatives?

Where tests come from?


Snapshot vs. Changes

Code snapshot Code change history

Examples MAPO, … DynaMine, …

Advantages Larger amount of available data

Revision transactions encode more-focused entity relationships

Issues How to group CVS changes into transactions?

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