Jtl the java tools language intuitively querying java programs
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JTL – The Java Tools Language Intuitively querying Java programs. Itay Maman The Technion – Israel Institute of Technology Joint work with Tal Cohen and Yossi Gil. October 24, 2006 OOPSLA’06, Portland. Wanted: A class with a static method returning float. The regular expression approach:

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JTL – The Java Tools Language Intuitively querying Java programs

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Jtl the java tools language intuitively querying java programs

JTL – The Java Tools LanguageIntuitively querying Java programs

Itay Maman

The Technion – Israel Institute of Technology

Joint work with Tal Cohen and Yossi Gil

October 24, 2006

OOPSLA’06, Portland

Wanted a class with a static method returning float

Wanted: A class with a static method returning float

  • The regular expression approach:

    static float


    • (Inaccurate)

  • The XQuery approach:


    .[email protected]="float"

    and @modifiers="static"]

    • (Too complicated to be used interactively)

  • There’s also a JTL way…

In this talk

In this Talk

  • Motivation, Design considerations

  • JTL 101

  • Evaluation algorithm

Usage scenarios

Usage scenarios

  • Existing solutions: CodeQuest, BDDBDDB, XIRC, JQuery, ALPHA, …

  • Software engineering tools

    • Code lookup, (anti) pattern detection, …

  • Programming languages

    • Static pointcuts in aspect-oriented programming

    • Mixins (Jam)

    • Concepts (ConceptC++)

    • Pluggable type systems (JavaCOP)

Queries embedded in the program

Queries embedded in the Program

  • Java 5 already provides code queries

    • Syntax close to Java

    • Limited expressive power

  • A hypothetical alternative (SQL)

    • Syntax significantly diverts from Java

    • Difficult to write/read

public<T extends Cloneable & Serializeable>

void f(T ts) { ... }

public<SELECT * FROM extends WHERE (super = 'Cloneable' or super = 'Serializeable') and subclass='T' ...>

void f(T ts) { … }

Mission statement

Mission Statement

Define a logic language (over Java programs) which:

  • Is as powerful as Datalog

  • Has an intuitive, readable syntax

  • Has a simple data model

  • Other solutions fall short

  • Jtl unary predicates

    JTL: Unary Predicates

    • A simple predicate:

      • Three sub-queries

      • Space (and comma) denotes conjunction

    • The subject variable

      • The hash symbol, #, denotes the subject variable

      • A variable in a prefix position => becomes the subject of the callee

        • If not specified, defaults to # (the subject)

    • static, final, etc. are library predicates, not keywords.

    const := static final field;

    const := #static #final #field;

    Jtl binary predicates

    JTL: Binary Predicates

    • Binary predicates

      • Accept a subject + an additional parameter (in a postfix position)

      • (Names of Variables/Parameters must begin with a capital letter)

    • Subject chaining: Repeatedly using a variable as a subject

      • Can be rewritten using the ampersand operator:

    has_static_member X := class declares X, X static;

    extends+ Y := extends Y | extends Y', Y' extends+ Y;

    my_generic_method T :=

    method, T extends Serializeable, T extends Cloneable;

    my_generic_method T := method, T extends Serializeable & Cloneable;

    Jtl quantification

    JTL: Quantification { }

    some_class := class {

    static int field;

    field => private;

    many method;


    • Quantifying the members of a class

      • Subject variable iterates over a set

      • Each condition must hold

      • Quantifiers:

        • Unary: exists, all, no, one, many

        • Binary: => (implies)

    • Quantifying with a generator

    • Default generator for classes: members:

    • Default quantifier: exists


    no_abstract_super := class extends+: {

    no abstract;


    Other features

    Other Features

    Type literal

    sortable_list := class extends /java.util.ArrayList {

    static final long field 'SerialVersionUID;

    public void sort();


    Name matching

    (Regular expression)

    Method signature pattern

    • Type system

      • MEMBER: constructors, methods, fields

      • TYPE: interfaces, classes, primitive types, enum types, annotation types

    Delving into methods

    Delving into methods

    • The idea: Symbolically name intermediate results

    • The SCRATCH type

      • Constants

      • Values passed to parameters

      • Values pushed onto the stack by JVM instructions

    • Represent code sites

    • Library predicates for checking whether a scratch is:

      • Copied

      • Used in a calculation

      • Written/Read from a field

      • Stored/loaded from the local variable array

      • ...

    Scratches in action

    Scratches in Action

    • Default generator expression for a method is: scratches:

      • Generates all scratches of the method

    copy* S := is S | copy S | copy S', S' copy* S;

    chain_method := !void method {

    returned => copy* S, S this;


    getter_method := !void method declared_by C,

    C declares F {

    returned => copy* V, V getfield [I,F], I copy* S,

    S this;


    Evaluation scheme

    Evaluation scheme

    • JTL is translated into Datalog

    • The Datalog program is evaluated top-down

    • “need to know basis”

      • The JTL evaluation algorithm does not see more information than it needs

      • Only necessary facts are extracted from the native predicates

        => No database setup is needed

        - Which is a bottleneck in similar applications

    Q what s special about p2

    Q: What’s special about p2?

    p1 := # extends A, A abstract;

    p2 := A extends #, A abstract;

    p3 := A extends #, A abstract, # p4 A;

    p4 := ...

    • A: Result of p2 is infinite

      • Result of p3 may be infinite (depending on the definition of p4)

    • Consequences

      • Use exhaustive iteration

        • Assume a closed world, usually: the classpath

        • Performance penalty

      • Beware: Fragile results!!

    (Suppose we invoke p1, p2, p3 with some type passed in as a subject)



    • Can we determine whether a query is fragile?

      • In the general case: No

      • In JTL’s case: Yes

        • Requires the native predicates to maintain a simple property

        • Recently proven by Gil and Zarivach

    • JTL’s current implementation is more conservative

      • Subject is not known => a runtime error

      • Works well in most practical situations



    JTL: A powerful language, intuitive notation, simple data model

    • Java-like clauses become Datalog queries

    • Queries on behavior

    • Efficient implementation

    Jtl the java tools language intuitively querying java programs


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