Software Development Methodologies and Testing
Various generic software development life cycle methodologies are available for executing software development projects. Although each methodology is designed for a specific purpose and has its own advantages and disadvantages, most methodologies divide the life cycle into phases and share tasks across these phases. This section briefly summarizes common methodologies used for software development and describes their relationship to testing.
Waterfall Model
The waterfall model is one of the earliest structured models for software development. It consists of the following sequential phases through which the development life cycle progresses:
- System feasibility. In this phase, you consider the various aspects of the targeted business process, find out which aspects are worth incorporating into a system, and evaluate various approaches to building the required software.
- Requirement analysis. In this phase, you capture software requirements in such a way that they can be translated into actual use cases for the system. The requirements can derive from use cases, performance goals, target deployment, and so on.
- System design. In this phase, you identify the interacting components that make up the system. You define the exposed interfaces, the communication between the interfaces, key algorithms used, and the sequence of interaction. An architecture and design review is conducted at the end of this phase to ensure that the design conforms to the previously defined requirements.
- Coding and unit testing. In this phase, you write code for the modules that make up the system. You also review the code and individually test the functionality of each module.
- Integration and system testing. In this phase, you integrate all of the modules in the system and test them as a single system for all of the use cases, making sure that the modules meet the requirements.
- Deployment and maintenance. In this phase, you deploy the software system in the production environment. You then correct any errors that are identified in this phase, and add or modify functionality based on the updated requirements.
The waterfall model has the following advantages:
- It allows you to compartmentalize the life cycle into various phases, which allows you to plan the resources and effort required through the development process.
- It enforces testing in every stage in the form of reviews and unit testing. You conduct design reviews, code reviews, unit testing, and integration testing during the stages of the life cycle.
- It allows you to set expectations for deliverables after each phase.
The waterfall model has the following disadvantages:
- You do not see a working version of the software until late in the life cycle. For this reason, you can fail to detect problems until the system testing phase. Problems may be more costly to fix in this phase than they would have been earlier in the life cycle.
- When an application is in the system testing phase, it is difficult to change something that was not carefully considered in the system design phase. The emphasis on early planning tends to delay or restrict the amount of change that the testing effort can instigate, which is not the case when a working model is tested for immediate feedback.
- For a phase to begin, the preceding phase must be complete; for example, the system design phase cannot begin until the requirement analysis phase is complete and the requirements are frozen. As a result, the waterfall model is not able to accommodate uncertainties that may persist after a phase is completed. These uncertainties may lead to delays and extended project schedules.
Incremental or Iterative Development
The incremental, or iterative, development model breaks the project into small parts. Each part is subjected to multiple iterations of the waterfall model. At the end of each iteration, a new module is completed or an existing one is improved on, the module is integrated into the structure, and the structure is then tested as a whole.
For example, using the iterative development model, a project can be divided into 12 one- to four-week iterations. The system is tested at the end of each iteration, and the test feedback is immediately incorporated at the end of each test cycle. The time required for successive iterations can be reduced based on the experience gained from past iterations. The system grows by adding new functions during the development portion of each iteration. Each cycle tackles a relatively small set of requirements; therefore, testing evolves as the system evolves. In contrast, in a classic waterfall life cycle, each phase (requirement analysis, system design, and so on) occurs once in the development cycle for the entire set of system requirements.
The main advantage of the iterative development model is that corrective actions can be taken at the end of each iteration. The corrective actions can be changes to the specification because of incorrect interpretation of the requirements, changes to the requirements themselves, and other design or code-related changes based on the system testing conducted at the end of each cycle.
The main disadvantages of the iterative development model are as follows:
- The communication overhead for the project team is significant, because each iteration involves giving feedback about deliverables, effort, timelines, and so on.
- It is difficult to freeze requirements, and they may continue to change in later iterations because of increasing customer demands. As a result, more iterations may be added to the project, leading to project delays and cost overruns.
- The project requires a very efficient change control mechanism to manage changes made to the system during each iteration.
Prototyping Model
The prototyping model assumes that you do not have clear requirements at the beginning of the project. Often, customers have a vague idea of the requirements in the form of objectives that they want the system to address. With the prototyping model, you build a simplified version of the system and seek feedback from the parties who have a stake in the project. The next iteration incorporates the feedback and improves on the requirements specification. The prototypes that are built during the iterations can be any of the following:
- A simple user interface without any actual data processing logic
- A few subsystems with functionality that is partially or completely implemented
- Existing components that demonstrate the functionality that will be incorporated into the system
The prototyping model consists of the following steps.
- Capture requirements. This step involves collecting the requirements over a period of time as they become available.
- Design the system. After capturing the requirements, a new design is made or an existing one is modified to address the new requirements.
- Create or modify the prototype. A prototype is created or an existing prototype is modified based on the design from the previous step.
- Assess based on feedback. The prototype is sent to the stakeholders for review. Based on their feedback, an impact analysis is conducted for the requirements, the design, and the prototype. The role of testing at this step is to ensure that customer feedback is incorporated in the next version of the prototype.
- Refine the prototype. The prototype is refined based on the impact analysis conducted in the previous step.
- Implement the system. After the requirements are understood, the system is rewritten either from scratch or by reusing the prototypes. The testing effort consists of the following:
- Ensuring that the system meets the refined requirements
- Code review
- Unit testing
- System testing
The main advantage of the prototyping model is that it allows you to start with requirements that are not clearly defined.
The main disadvantage of the prototyping model is that it can lead to poorly designed systems. The prototypes are usually built without regard to how they might be used later, so attempts to reuse them may result in inefficient systems. This model emphasizes refining the requirements based on customer feedback, rather than ensuring a better product through quick change based on test feedback.
Agile Methodology
Most software development life cycle methodologies are either iterative or follow a sequential model (as the waterfall model does). As software development becomes more complex, these models cannot efficiently adapt to the continuous and numerous changes that occur. Agile methodology was developed to respond to changes quickly and smoothly. Although the iterative methodologies tend to remove the disadvantage of sequential models, they still are based on the traditional waterfall approach. Agile methodology is a collection of values, principles, and practices that incorporates iterative development, test, and feedback into a new style of development. For an overview of agile methodology, see the Agile Modeling site at
http://www.agilemodeling.com/.
The key differences between agile and traditional methodologies are as follows:
- Development is incremental rather than sequential. Software is developed in incremental, rapid cycles. This results in small, incremental releases, with each release building on previous functionality. Each release is thoroughly tested, which ensures that all issues are addressed in the next iteration.
- People and interactions are emphasized, rather than processes and tools. Customers, developers, and testers constantly interact with each other. This interaction ensures that the tester is aware of the requirements for the features being developed during a particular iteration and can easily identify any discrepancy between the system and the requirements.
- Working software is the priority rather than detailed documentation. Agile methodologies rely on face-to-face communication and collaboration, with people working in pairs. Because of the extensive communication with customers and among team members, the project does not need a comprehensive requirements document.
- Customer collaboration is used, rather than contract negotiation. All agile projects include customers as a part of the team. When developers have questions about a requirement, they immediately get clarification from customers.
- Responding to change is emphasized, rather than extensive planning. Extreme Programming does not preclude planning your project. However, it suggests changing the plan to accommodate any changes in assumptions for the plan, rather than stubbornly trying to follow the original plan.
Agile methodology has various derivate approaches, such as Extreme Programming, Dynamic Systems Development Method (DSDM), and SCRUM. Extreme Programming is one of the most widely used approaches.
Extreme Programming
In Extreme Programming, rather than designing whole of the system at the start of the project, the preliminary design work is reduced to solving the simple tasks that have already been identified.
The developers communicate directly with customers and other developers to understand the initial requirements. They start with a very simple task and then get feedback by testing their software as soon as it is developed. The system is delivered to the customers as soon as possible, and the requirements are refined or added based on customer feedback. In this way, requirements evolve over a period of time, and developers are able to respond quickly to changes.
The real design effort occurs when the developers write the code to fulfill the specific engineering task. The engineering task is a part of a greater user story (which is similar to a use case). The user story concerns itself with how the overall system solves a particular problem. It represents a part of the functionality of the overall system. A group of user stories is capable of describing the system as a whole. The developers refactor the previous code iteration to establish the design needed to implement the functionality.
During the Extreme Programming development life cycle, developers usually work in pairs. One developer writes the code for a particular feature, and the second developer reviews the code to ensure that it uses simple solutions and adheres to best design principles and coding practices.
Discussion of the core practices of Extreme Programming is beyond the scope of this chapter. For more information, see the links referred to in "More Information" later in this section.
Test-driven development, which is one of the core practices in Extreme Programming, is discussed in greater detail later in this chapter.
When to Use Extreme Programming
Extreme Programming is useful in the following situations:
- When the customer does not have a clear understanding of the details of the new system. The developers interact continuously with the customer, delivering small pieces of the application to the customer for feedback, and taking corrective action as necessary.
- When the technology used to develop the system is new compared to other technologies. Frequent test cycles in Extreme Programming mitigate the risk of incompatibility with other existing systems.
- When you can afford to create automated unit and functional tests. In some situations, you may need to change the system design so that each module can be tested in isolation using automated unit tests.
- When the team size is not very large (usually 2 to 12 people). Extreme Programming is successful in part because it requires close team interaction and working in pairs. A large team would have difficulty in communicating efficiently at a fast pace. However, large teams have used Extreme Programming successfully.
Test-Driven Development
Test-driven development is one of the core practices of Extreme Programming. The practice extends the feedback approach, and requires that you develop test cases before you develop code. Developers develop functionality to pass the existing test cases. The test team then adds new test cases to test the existing functionality, and runs the entire test suite to ensure that the code fails (either because the existing functionality needs to be modified or because required functionality is not yet included). The developers then modify the functionality or create new functionality so that the code can withstand the failed test cases. This cycle continues until the test code passes all of the test cases that the team can create. The developers then refactor the functional code to remove any duplicate or dead code and make it more maintainable and extensible.
Test-driven development reverses the traditional development process. Instead of writing functional code first and then testing it, the team writes the test code before the functional code. The team does this in very small steps—one test and a small amount of corresponding functional code at a time. The developers do not write code for new functionality until a test fails because some functionality is not present. Only when a test is in place do developers do the work required to ensure that the test cases in the test suite pass. In subsequent iterations, when the team has the updated code and another set of test cases, the code may break several existing tests as well as the new tests. The developers continue to develop or modify the functionality to pass all of the test cases.
Test-driven development allows you to start with an unclear set of requirements and relies on the feedback loop between the developers and the customers for input on the requirements. The customer or a customer representative is the part of the core team and immediately provides feedback about the functionality. This practice ensures that the requirements evolve over the course of the project cycle. Testing before writing functional code ensures that the functional code addresses all of the requirements, without including unnecessary functionality.
With test-driven development, you do not need to have a well-defined architectural design before beginning the development phase, as you do with traditional development life cycle methodologies. Test-driven development allows you to tackle smaller problems first and then evolve the system as the requirements become more clear later in the project cycle.
Other advantages of test-driven development are as follows:
- Test-driven development promotes loosely coupled and highly cohesive code, because the functionality is evolved in small steps. Each piece of the functionality needs to be self-sufficient in terms of the helper classes and the data that it acts on so that it can be successfully tested in isolation.
- The test suite acts as documentation for the functional specification of the final system.
- The system uses automated tests, which significantly reduce the time taken to retest the existing functionality for each new build of the system.
- When a test fails, you have a clear idea of the tasks that you must perform to resolve the problem. You also have a clear measure of success when the test no longer fails. This increases your confidence that the system actually meets the customer requirements.
Test-driven development helps ensure that your source code is thoroughly unit tested. However, you still need to consider traditional testing techniques, such as functional testing, user acceptance testing, and system integration testing. Much of this testing can also be done early in your project. In fact, in Extreme Programming, the acceptance tests for a user story are specified by the project stakeholder(s) either before or in parallel to the code being written, giving stakeholders the confidence that the system meets their requirements.
Steps in Test-Driven Development
The test-driven development process consists of the steps shown in Figure 2.1.
Figure 2.1. Test-driven development process
The steps can be summarized as follows:
- Create the test code. Use an automated test framework to create the test code. The test code drives the development of functionality.
- Write/Modify the functional code. Write the functional code for the application block so that it can pass all test cases from the test code. The first iteration involves developing new functionality, and subsequent iterations involve modifying the functionality based on the failed test cases.
- Create additional tests. Develop additional tests for testing of the functional code.
- Test the functional code. Test the functional code based on the test cases developed in Step 3 and Step 1. Repeat steps 2 through 4 until the code is able to pass all of the test cases.
- Refactor the code. Modify the code so that there is no dead code or duplication. The code should adhere to best practices for maintainability, performance, and security.
The following subsections describe each step in detail.
Step 1: Create the Test Code
You create the test code before any code is written for the functionality of the application block. You can either write a custom test suite or use a testing framework (such as NUnit) to automate testing of the API. The general guidelines for writing the test code are as follows:
- In Step 1, your goal is to write test code that tests basic functionality.
- Write a test case for each code requirement. The developers will write the functional code based on the tests so that the test cases have an execution result of "pass."
- Avoid writing code for multiple test cases at any one time. Write code for a single test case, and proceed through the remaining cycle of coding and refactoring.
- Write code that tests only small pieces of functionality. If the test code is complex, divide it into smaller tests so that each one tests only a small piece of functionality.
After you complete Step 1, you should have various test suites written to test the functionality. For example, if you need to test the functionality of the CMAB using NUnit, create test code first, as follows:
[Test]
public void GetXmlFileSection() {
string sourceSection = "XmlFile";
CustomConfigurationData custom = ConfigurationManager.Read( sourceSection ) as CustomConfigurationData;
Assert.Equals("Red", custom.Color, "Red color was expected" );
Assert.Equals(45, custom.Size, "45 size was expected" );
Assert.Equals("Some text", custom.SomeText, "Some text was expected" );
}
public class CustomConfigurationData{
public CustomConfigurationData() {}
public string Color{
get{ return _color; }
set{ _color = value; }
} string _color;
public string SomeText {
get{ return _some_text; }
set{ _some_text = value; }
} string _some_text;
public int Size{
get{ return _size; }
set{ _size = value; }
} int _size;
public override string ToString(){
return "Color = " + _color + "; FontSize = " + _size.ToString( System.Globalization.CultureInfo.CurrentUICulture );
}
}
You will not be able to compile the test code until the developer writes the functional code. The developer then writes the code so that the test compiles and has an execution result of "pass."
More Information
Step 2: Write or Modify the Functional Code
In Step 2, your goal is to develop functionality that passes the test cases that were created in Step 1. If you are in the first iteration, in all probability the test code will not compile and you can assume that it failed. You must modify the functionality being tested so that the test code compiles and can be executed.
After the functionality passes all of the test cases created in Step 1, the developer stops developing the module.
The functionality in the following example passes the test case that was created in Step 1.
class ConfigurationManager {
public static object Read(string sourceSection){
CustomConfigurationData customConfiguration = new CustomConfigurationData();
customConfiguration.Color = "Red";
customConfiguration.SomeText = "Some text";
customConfiguration.Size = "45";
return obj;
}
The outcome of Step 2 is code that implements basic functionality. However, in the later iterations, when additional test cases are created to test the functionality, the code in the previous example will fail. The developers must make further changes in subsequent iterations so that all of the functionality can pass the additional test cases. The developers continue to improve the functionality until all of the existing test cases have an execution result of "pass."
Step 3: Create Additional Tests
After Step 2, the code has the basic functionality to pass all of the test cases that were created in Step 1. The tester must now test this functionality for various types of input.
You should ensure that the amount of time spent developing additional test cases is proportionate to the criticality of the feature. For example, if various code paths in an API need to be tested by providing different input, you can write multiple test stubs, with each stub catering to one possible code path.
The general guidelines for creating these additional tests are as follows:
- Create additional tests that could possibly break the code. Continue to create these additional tests until you have no more test cases.
- Write test cases that focus on the goal of the code (what the user needs the code to do), rather than the implementation. For example, if the goal of a function is to return values from a database based on some identifier, test the function by passing both valid and invalid identifier values, rather than testing only those values that the current implementation supports (which can be only a valid set of values).
- If all of the test cases that were created in Step 1 have passed but still the functionality does not work as intended, you have probably missed an important test scenario and must develop additional test cases that reproduce the failure of the functionality. These test cases are in addition to the existing test cases that pass invalid input to the API to force an exception.
- Avoid writing separate test cases for each unique combination of input. The number of test cases you write should be based on the risk assessment of the feature and on ensuring that all critical scenarios and the majority of test input have been accounted for.
The following additional test case will fail the functionality that was written for the example in Step 2.
[Test]
public void GetSqlSection() {
string sourceSection = "SQLServer";
CustomConfigurationData custom = ConfigurationManager.Read( sourceSection ) as SqlData;
Assert.Equals("John", custom.FirstName, "John was expected");
Assert.Equals("Trovalds", custom.LastName, "Trovalds was expected");
}
public class SqlData{
public SqlData () {}
public string FirstName{
get{ return _firstname; }
set{ _firstname = value; }
} string _firstname;
public string LastName {
get{ return _lastName; }
set{ _lastName = value; }
} string _lastName;
}
Step 4: Test the Functional Code
The next step is to test the functionality by using the additional test cases. To do so, execute all of the test cases from Step 1and Step 3, and note any test cases that fail the test. The developers must then make changes to the functional code so that it passes all of the existing test cases.
Repeat steps 2, 3, and 4 until the testers can no longer create additional test cases that break the functionality of the code. Each time a test fails, the developers fix the functionality based on the test cases and submit the improved code to the testers for a new round of testing.
Step 5: Refactor the Code
After the completion of the previous steps, the code can be run and is capable of handling all of the test cases. In Step 5, the developers refactor the code to make it maintainable and extensible so that changes in one part of the module can be worked on in isolation without changing the actual interfaces exposed to the end user.
In addition to making code easier to maintain, refactoring removes duplicate code and can reduce code complexity. This helps to ensure that the basic principles of loosely coupled and highly cohesive design are followed without breaking the functionality in any way. For example, if you have the functionality shown in the first example, you can refactor it as shown in the second example. (In these examples, the helper class does not own the data it works on. Instead, the caller passes the data to the helper class. This is typical of the BOB class anti-pattern.)
[Original Code]
Class BOBClass
{
void DoWork()
{
Helper hlpObject = new HelperClass();
If (hlpObject.CanDoWork)
{
Double x = hlpObject.SomeValue + hlpObject.SomeOtherValue;
hlpObject.NewValue = x;
}
}
}
Class Helper
{
bool CanDoWork = true;
double SomeValue;
double SomeOtherValue;
double NewValue;
}
[Refactored Code]
Class BOBClass{
void DoWork(){
Helper hlpObject = new HelperClass();
hlpObject.DoWork();
}
}
Class Helper{
bool CanDoWork = true;
double SomeValue;
double SomeOtherValue;
double NewValue;
void DoWork(){
If (CanDoWork)
NewValue = SomeValue + SomeOtherValue;
}
}
Depending on the size of the application you are developing, you should consider refactoring the code at regular intervals during the development cycle. Doing so helps to reduce code redundancy and to optimize the design, and it prevents the refactoring exercise from being a monumental task at the end of the project.
After completing Step 5, you repeat the test-driven development process for each subsequent feature requirement, until the system being developed is complete.
Although the test-driven model requires you to test each line of code as it is developed, you still need to perform other types of testing, such as performance testing, security testing, and globalization testing.
Agile Testing: Example
Agile methodology with Extreme Programming and test-driven development was used to develop the Smart Client Offline Application Block. The following are highlights of the approach taken on the project:
- The test team and the development team were not formally separated. The developers worked in pairs, with one person developing the test cases and the other writing the functionality for the module.
- There was much more interaction among team members than there is when following a traditional development model. In addition to using the informal chat-and-develop mode, the team held a 30 minute daily standup meeting, which gave team members a forum for asking questions and resolving problems, and weekly iterative review meetings to track the progress for each iterative cycle.
- Project development began without any formal design document. The specifications were in the form of user stories that were agreed upon by the team members. In the weekly iterative review meetings, team members planned how to complete these stories and how many iterations to assign for each story.
- Each story was broken down into several tasks. All of the stories and corresponding tasks were written down on small cards that served as the only source of design documentation for the application block.
- While developing each task or story, NUnit test suites were written to drive the development of features.
- No formal test plans were developed. The testing was primarily based on the tasks or stories for feature development. The development team got immediate feedback from the test team. Having the test team create the quick start samples gave the development team a perspective on the real-life usage of the application block.
- After the task or story passed all of the NUnit test cases and was complete, quick start samples were developed to showcase the functionality. The quick start samples demonstrated the usage of the application block and were useful for further testing the code in the traditional way (functional and integration tests). Any discrepancies found in this stage were reported immediately and were fixed on a case-by-case basis. The modified code was tested again with the automated test suites and then was handed over to be tested again with the quick start samples.
Disclaimer: Stepin2IT is not associated with Microsoft or any of its partners. This is only to encourage testers to follow the best practices widely used in the industry.
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