Over the years, I've seen lots of source code from many projects, ranging from elegant designs to code that appeared to be bundled together with duct tape. I've written new code and maintained other developers' source code. I'd rather write new code, but I enjoy taking some existing code and reducing complexity in a method or extracting duplicate code into a common class. Earlier in my career, many believed that if you weren't writing new code, you weren't being productive. Fortunately, in the late 1990s, Martin Fowler's book Refactoring (see Resources) helped make the practice of improving existing code without changing external behavior — well — cool.

Much of what I cover in this series is about efficiency: how to reduce the redundancy of time-consuming processes and perform them more quickly. I'll do the same for the tasks I cover in this article and discuss how to perform them more effectively.

A typical approach to refactoring is to make small changes to existing code while you're introducing new code or changing a method. The challenges of this technique are that it's often inconsistently applied among developers on a team, and that it can be easy to miss opportunities for refactoring. This is why I advocate using static analysis tools to identify coding violations. With them, you gain visibility into the code base as a whole, and at the class or method level. Fortunately, in Java™ programming, you can choose from an abundance of freely available open source static analysis tools: CheckStyle, PMD, FindBugs, JavaNCSS, JDepend, and many others.

In this article, you'll learn how to:

• Reduce conditional complexity code smells by measuring cyclomatic complexity using CheckStyle and providing refactorings such as Replace Conditional with Polymorphism
  
  
• Remove duplicated code code smells by assessing code duplication using CheckStyle and providing refactorings such as Pull Up Method
  
  
• Thin large class code smells by counting source lines of code using PMD (or JavaNCSS) and providing refactorings such as Extract Method
  
  
• Wipe out too many imports code smells by determining a class's efferent coupling using CheckStyle (or JDepend) and providing refactorings such as Move Method

I'll use the following general format as we examine each code smell:

1. Describe the smell that can indicate a problem in the code
2. Define the measure that can find that smell
3. Show the tool that measures the code smell
4. Present the refactoring and, in some cases, the patterns to fix the code smell

In essence, this approach provides a framework for finding and fixing code problems throughout the code base. And you'll be better informed about the riskier parts of the code base prior to making changes. Better yet, I'll show you how you integrate this approach into automated builds.

Conditional complexity

Smell: Conditional complexity

Measure: Cyclomatic complexity

Tool: CheckStyle, JavaNCSS, and PMD

Refactorings: Replace Conditional with Polymorphism, Extract Method

Smell

Conditional complexity can manifest in several different ways in source code. One example of this code smell is to have multiple conditional statements such as if, while, or for statements. Another type of conditional complexity can be in the form of switch statements, as demonstrated in Listing 1:

...
switch (beerType) {
  case LAGER:  
    System.out.println("Ingredients are..."); 
	...
	break;
  case BROWNALE:
    System.out.println("Ingredients are..."); 
	...
	break;
  case PORTER  
    System.out.println("Ingredients are..."); 
	...
	break;
  case STOUT:
    System.out.println("Ingredients are..."); 
	...
	break;
  case PALELAGER:
    System.out.println("Ingredients are..."); 
	...
	break;
  ...
  default:
    System.out.println("INVALID."); 
	...
	break;
}
...

switch statements themselves are not a bad thing. But when each statement includes too many choices and too much code, it could be an indication of code that needs to refactored.

Measure

To determine the conditional-complexity code smell, you determine a method's cyclomatic complexity. Cyclomatic complexity is a measure that dates back to 1975 as defined by Thomas McCabe. The Cyclomatic Complexity Number (CCN) measures the number of unique paths in a method. Each method starts with a CCN of 1 regardless of how many paths are in the method. Conditional constructs such as if, switch, while, and for statements are each given a value of 1, along with exception paths. The overall CCN for a method is an indication of its complexity. Many consider a CCN of 10 or more to indicate an overly complex method.

Tool

CheckStyle, JavaNCSS, and PMD are open source tools that measure cyclomatic complexity. Listing 2 shows a snippet of a CheckStyle rules file defined in XML. The CyclomaticComplexity module defines the maximum CCN for a method.

<module name="CyclomaticComplexity">
  <property name="max" value="10"/>
</module>

Using the CheckStyle rules file from Listing 2, the Gant example in Listing 3 demonstrates how to run CheckStyle as part of an automated build. Gant is an automated build tool that provides an expressive programming language with support for build dependencies. Developers write Gant scripts using the power of the Groovy programming language. Because Gant provides full access to Ant's API, anything you can run in Ant can be run from a Gant script. (See the "Build software with Gant" tutorial to learn about Gant.)

target(findHighCcn:"Finds method with a high cyclomatic complexity number"){
  Ant.mkdir(dir:"target/reports")
  Ant.taskdef(name:"checkstyle", 
    classname:"com.puppycrawl.tools.checkstyle.CheckStyleTask",
    classpathref:"build.classpath")
  Ant.checkstyle(shortFilenames:"true", config:"config/checkstyle/cs_checks.xml", 
    failOnViolation:"false", failureProperty:"checks.failed", classpathref:"libdir") {
    formatter(type:"xml", tofile:"target/reports/checkstyle_report.xml")
    formatter(type:"html", tofile:"target/reports/checkstyle_report.html")
    fileset(dir:"src"){
      include(name:"**/*.java")
    }
  }
}  

The Gant script in Listing 3 creates the CheckStyle report shown in Figure 1. The bottom of the figure indicates the CheckStyle cyclomatic-complexity violation for a method.

Refactoring

Figure 2 is a UML representation of the Replace Conditional with Polymorphism refactoring:

See the full figure here.

In Figure 2, I:

1. Create a Java interface called BeerType
2. Define a generic showIngredients() method
3. Create implementing classes for each of the BeerTypes

For brevity, I provided one method implementation per class. Ostensibly, you would have more than one method when creating an interface. Refactorings such as Replace Conditional with Polymorphism and Extract Method (which I'll explain later in the article) help make code much easier to maintain.

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Duplicated code

Smell: Duplicated code

Measure: Code duplication

Tool: CheckStyle, PMD

Refactorings: Extract Method, Pull Up Method, Form Template Method, Substitute Algorithm

Smell

Duplicate code can creep into a code base unbeknownst to anyone. Sometimes, it's easier to copy and paste some code than to generalize the behavior into another class. One problem with copy-and-paste is that it forces an awareness of multiple copies of the code and the need to maintain them. A more insidious problem occurs when slight variations to the copied code cause inconsistent behavior, depending on which method is executing the behavior. Listing 4 is an example of code that closes a database connection, with the same code present in two methods:

public Collection findAllStates(String sql) {
...
  try {
    if (resultSet != null) {
      resultSet.close();
    }
    if (stmt != null) {
      stmt.close();
    }
    if (conn != null) {
     conn.close();
   } 
   catch (SQLException se) {
     throw new RuntimeException(se);
   }
 }
...
}
...
public int create(String sql, Beer beer) {
...
  try {
    if (resultSet != null) {
      resultSet.close();
    }
    if (stmt != null) {
      stmt.close();
    }
    if (conn != null) {
     conn.close();
   } 
   catch (SQLException se) {
     throw new RuntimeException(se);
   }
 }
...
}

Measure

The measure for finding duplicated code is to search for code duplication within classes and among other classes in the code base. Duplication among classes is more difficult to assess without the help of a tool. Because of the slight changes that copied code can often undergo, it's important to measure code that is not simply copied verbatim, but also code that is similar.

Tool

PMD's Copy/Paste Detector (CPD) and CheckStyle are two of the open source tools available for finding similar code throughout a Java code base. The CheckStyle configuration file example in Listing 5 demonstrates the use of the StrictDuplicateCode module:

<module name="StrictDuplicateCode">
  <property name="min" value="10"/>
</module>

The min property in Listing 5 sets the minimum number of duplicate lines that CheckStyle will flag for review. In this case, it will only indicate blocks of code that have at least 10 lines that are similar or have been duplicated.

Figure 3 shows the results of the module settings from Listing 5 after the automated build runs:

Refactoring

In Listing 6, I take the duplicated code in Listing 4 and reduce the duplication by using the Pull Up Method refactoring — extracting behavior from a larger method into an abstract class method:

...
} finally {
  closeDbConnection(rs, stmt, conn);
}
...

Duplicated code will happen. I would never recommend to a team to set the unrealistic goal of having no duplication whatsoever. However, an appropriate goal is to ensure that duplicate code within the code base does not increase. By using a static analysis tool such as PMD's CPD or CheckStyle, you can determine areas of high code duplication on a continual basis as part of running an automated build.

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Long method (and large class)

Smell: Long method (and large class)

Measure: Source lines of code (SLOC)

Tool: PMD, JavaNCSS, CheckStyle

Refactorings: Extract Method, Replace Temp with Query, Introduce Parameter Object, Preserve Whole Object, Replace Method with Method Object

Smell

A general rule of thumb I try to adhere to is to keep my methods to 20 lines of code or fewer. Of course, there may be exceptions to this rule, but if I've got methods over 20 lines, I want to know about it. Often, there's a correlation between long methods and conditional complexity. And there's a connection between large classes and long methods. I'd love to show the example of the 2,200-line method I found on a project I had to maintain. I printed an entire class containing 25,000 lines of code and asked my colleagues to find the bugs. Let's just say I made my point as I rolled the printed code down the hallway.

The highlighted section in Listing 7 shows a small portion of an example of a long method code smell:

public void saveLedgerInformation() {
...
try {
  if (ledger.getId() != null && filename == null) {
    getLedgerService().saveLedger(ledger);
  } else {
    accessFiles().decompressFiles(files, filenames);
  } 
  if (!files.get(0).equals(upload)) {
    upload = files.get(0);
    filename = filenames.get(0);
  }
  if (invalidFiles.isUnsupported(filename)) {
    setError(fileName, message.getMessage());
  } else {
  LedgerFile entryFile = accessFiles().add(upload, filename);
  if (fileType != null && FileType.valueOf(fileType) != null) {
    entryFile.setFileType(FileType.valueOf(fileType));
  }
  getFileManagementService().saveLedger(ledger, entryFile);
  if (!FileStatus.OPENED.equals(entryFile.getFileStatus())) {
    getFileManagementService().importLedgerDetails(ledger);
  }
  if (uncompressedFiles.size() > 1) {
    Helper.saveMessage(getText("ledger.file"));
  }
  
  if (user.getLastName() != null) {
    SearchInfo searchInfo = ServiceLocator.getSearchInfo();
    searchInfo.setLedgerInfo(null);
    isValid = false;
    setDefaultValues();
    resetSearchInfo();
    if (searchInfoValid && ledger != null) {
      isValid = true;
    }
  }
  
} catch (InvalidDataFileException e) {
  ResultType result = e.getResultType();
  for (ValidationMessage message : result.getMessages()) {
    setError(fileName, message.getMessage());
  }
  ledger.setEntryFile(null);


} ...

Measure

The SLOC measure has been misused in years past as an indication of productivity. We all know, though, that it's not necessarily true that the more lines you write, the better. However, SLOC can be a useful measure when it comes to complexity. The more lines in a method (or class), the more likely it will be difficult to maintain the code in the future.

Tool

The script in Listing 8 finds SLOC measures for long methods (and, optionally, large classes):

target(findLongMethods:"runs static code analysis"){
 Ant.mkdir(dir:"target/reports")
 Ant.taskdef(name:"pmd", classname:"net.sourceforge.pmd.ant.PMDTask",
   classpathref:"build.classpath")
 Ant.pmd(shortFilenames:"true"){
   codeSizeRules.each{ rfile ->
    ruleset(rfile)
   }
   formatter(type:"xml", tofile:"target/reports/pmd_report.xml")
   formatter(type:"html", tofile:"target/reports/pmd_report.html")
   fileset(dir:"src"){
     include(name:"**/*.java")
   }
  }  
}

Once again, I'm using Gant to access the Ant API to run Ant tasks. In Listing 8, I'm calling the PMD static analysis tool to search for long methods in the code base. PMD (along with JavaNCSS and CheckStyle) can also be used to find long methods, large classes, and many other code smells.

Refactoring

Listing 9 shows an example of the Extract Method refactoring to reduce the long method smell in Listing 7. After extracting behavior from the method in Listing 7 to the code in Listing 9, I can call the newly created isUserValid() method from the saveLedgerInformation() method in Listing 7:

private boolean isUserValid(User user) {
  boolean isValid = false;
  if (user.getLastName() != null) {
    SearchInfo searchInfo = ServiceLocator.getSearchInfo();
    searchInfo.setLedgerInfo(null);
    setDefaultValues();
    resetSearchInfo();
    if (searchInfoValid && ledger != null) {
      isValid = true;
    }
  }
  return isValid;
}

Often, long methods and large classes are indications of other code smells, such as conditional complexity and duplicated code. By finding these methods and classes, you can fix other problems.

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Too many imports

Smell: Too many imports

Measure: Efferent coupling (fan-out per class)

Tool: CheckStyle

Refactorings: Move Method, Extract Class

Smell

Too many imports is an indication that a class relies on too many other classes. You'll notice you've got this code smell when a change to one class necessitates making changes to many other classes, because they are so tightly coupled to the class you are changing. The multiple imports in Listing 10 are an example:

import com.integratebutton.search.SiteQuery;
import com.integratebutton.search.OptionsQuery;
import com.integratebutton.search.UserQuery;
import com.integratebutton.search.VisitsQuery;
import com.integratebutton.search.SiteQuery;
import com.integratebutton.search.DateQuery;
import com.integratebutton.search.EvaluationQuery;
import com.integratebutton.search.RangeQuery
import com.integratebutton.search.BuildingQuery;
import com.integratebutton.search.IPQuery;
import com.integratebutton.search.SiteDTO;
import com.integratebutton.search.UrlParams;
import com.integratebutton.search.SiteUtil;

import java.text.DateFormat;
import java.text.ParseException;
import java.text.SimpleDateFormat;
import java.util.ArrayList;
import java.util.Calendar;
import java.util.Collection;
import java.util.Collections;
import java.util.Date;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import org.apache.log4j.Logger;
...

Measure

A way to find a class with too much responsibility is through the efferent coupling measure, also referred to as fan out complexity. Fan out complexity assigns a 1 to every class the analyzed class is dependent on.

Tool

Listing 11 shows an example of using CheckStyle to set the maximum number of fan out complexity:

<module name="ClassFanOutComplexity">
  <property name="max" value="10"/>
</module>

Refactoring

There are several ways to fix the tight coupling that can occur as a result of too many imports. For code such as Listing 10, these refactorings include the Move Method refactoring: I move methods from the individual *Query classes into a Java interface and define common methods that all Query classes must implement. Then, I use the factory method pattern so that the coupling is with the interface.

By using a Gant automated build script to execute the CheckStyle Ant task, I can search my code base for classes that rely on too many other classes. When I modify code in these classes, I can implement certain refactorings such as Move Method along with certain design patterns to improve the ease of maintenance incrementally.

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Refactor ... early and often

Continuous Integration (CI) is the practice of integrating changes often. As it's typically practiced, an automated CI server, run from a separate machine, triggers an automated build with every change applied to a project's version-control repository. To ensure that the build scripts from Listing 3 and Listing 8 are run consistently and with every change to a code base, you'll want to configure a CI server such as Hudson (see Resources). Hudson is distributed as a WAR file that you can drop into any Java Web container.

Because the examples in Listing 3 and Listing 8 use Gant, I'll walk through the steps for configuring the Hudson CI server to run Gant scripts:

1. From the Hudson dashboard, install the Gant plug-in for Hudson by selecting Manage Hudson, followed by Manage Plugins, and then select the Available tab. From this tab, select the Gant plug-in check box and click the Install button.
   
   
2. Restart the Web container (for example, Tomcat).
   
   
3. Select Manage Hudson, then Configure System. From the Gant installation section, enter a unique name and the location of the Groovy installation on the machine where Hudson is running. Save the changes.
   
   
4. Go back to the Dashboard (by selecting the Hudson link) and select an existing Hudson Job, select Configure, click the Add build step button, and select the Invoke Gant script option.

With Hudson configured to run the automated build scripts written in Gant, you can get rapid feedback on measures that are related to code smells such as long method and conditional complexity as soon as they are introduced into the code base.

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Other smells and refactorings

Not all smells have correlating measures. However, static analysis tools can uncover other smells than the ones I've demonstrated. Table 1 lists examples of other code smells, tools, and possible refactorings:

This article provides a pattern of correlating a code smell to a measure that can be configured to be flagged from an automated static analysis tool. You can apply refactorings with or without the use of certain design patterns. This gives you a framework for consistently finding and fixing code smells in a repeatable manner. I'm confident that the examples in this article will help you use static analysis tools to find other types of code smells than the ones I've demonstrated.

Resources

Learn

• Automation for the people (Paul Duvall, developerWorks): Read the complete series. The "Continuous Inspection" (August 2006) and "Improving code with Eclipse plugins" (January 2007) installments are especially relevant to this article's topic.
  
  
• Smells to Refactorings: A table of recommended refactorings for specific code smells.
  
  
• Refactoring: Improving the Design of Existing Code (Martin Fowler, Addison-Wesley Professional, 1999): The seminal book on improving the design of an existing code base.
  
  
• Alpha List of Refactorings: Martin Fowler's list of refactorings.
  
  
• Refactoring to Patterns (Joshua Kereviesky, Addison-Wesley Professional, 2004): Applying design patterns to refactorings to improve code. I got the idea of printing out a large class from one of Josh's talks at Agile 2005 in Denver.
  
  
• "In pursuit of code quality: Monitoring cyclomatic complexity" (Andrew Glover, IBM developerWorks, March 2006): What to do when code complexity is off the charts.
  
  
• "In pursuit of code quality: Refactoring with code metrics" (Andrew Glover, IBM developerWorks, May 2006): On-target refactoring with code metrics and the Extract Method pattern.
  
  
• "Continuous Integration: Improving Software Quality and Reducing Risk" (Paul Duvall et al., Addison-Wesley Signature Series, 2007): Chapter 7, Continuous Inspection, covers many of the tools covered in this article.
  
  
• "Build software with Gant" (Andrew Glover, developerWorks, May 2008): Read this tutorial to learn how to use Gant for flexible builds.
  
  
• "(Ant to Gant) automagically" (Andrew Glover, The Disco Blog, April 2008): Generate Gant scripts based on an existing Ant script.
  
  
• "Gant with Hudson in 5 steps" (Andrew Glover, The Disco Blog, May 2008): Configuring the Hudson Continuous Integration server to run a Gant build script.
  
  
• "In pursuit of code quality: Code quality for software architects" (Andrew Glover, IBM developerWorks, April 2006): Use coupling metrics to support your system architecture.
  
  
• Browse the technology bookstore for books on these and other technical topics.
  
  
• developerWorks Java technology zone: Hundreds of articles about every aspect of Java programming.
  
  

Get products and technologies

• Gant: Download Gant and start building software in a predictable and repeatable manner.
  
  
• CheckStyle: Download CheckStyle to gather metrics and better assess certain code smells.
  
  
• PMD: Download PMD to gather metrics and better assess certain code smells.
  
  
• Hudson: A freely available open source server for Continuous Integration.
  
  

Discuss

• Improve Your Code Quality discussion forum: Regular developerWorks contributor Andrew Glover brings his considerable expertise as a consultant focused on improving code quality to this moderated discussion forum.
  
  
• Accelerate development space: Regular developerWorks contributor Andrew Glover hosts a one stop portal for all things related to developer testing, continuous integration, code metrics, and refactoring.
  
  
• Check out developerWorks blogs and get involved in the developerWorks community.
  
  

About the author

Paul Duvall is the CTO of Stelligent Incorporated, an Agile consultancy that helps development teams deliver production-ready software. He is the co-author of the Addison-Wesley Signature Series book Continuous Integration: Improving Software Quality and Reducing Risk (Addison-Wesley Professional, 2007; Jolt Award 2008 winner). He also contributed to the UML 2 Toolkit (Wiley, 2003) and the No Fluff Just Stuff Anthology (Pragmatic Programmers, 2007).

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Table of contents

• Conditional complexity
• Duplicated code
• Long method (and large class)
• Too many imports
• Refactor ... early and often
• Other smells and refactorings
• Resources
• About the author
• Comments

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