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sudha
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Quote sudha Replybullet Topic: Software Testing Overview
    Posted: 04Apr2007 at 4:02am
Software Testing Overview

Purpose of Testing
Testing accomplishes a variety of things, but most importantly it measures the quality of the software you are developing. This view presupposes there are defects in your software waiting to be discovered and this view is rarely disproved or even disputed.

Several factors contribute to the importance of making testing a high priority of any software development effort. These include:

1. Reducing the cost of developing the program. Minimal savings that might occur in the early stages of the development cycle by delaying testing efforts are almost certainly bound to increase development costs later. Common estimates indicate that a problem that goes undetected and unfixed until a program is actually in operation can be 40 – 100 times more expensive to resolve than resolving the problem early in the development cycle.
2. Ensuring that your application behaves exactly as you explain to the user. For the vast majority of programs, unpredictability is the least desirable consequence of using an application.
3. Reducing the total cost of ownership. By providing software that looks and behaves as shown in your documentation, your customers require fewer hours of training and less support from product experts.
4. Developing customer loyalty and word-of-mouth market share. Finding success with a program that offers the kind of quality that only thorough testing can provide is much easier than trying to build a customer base on buggy and defect-riddled code.

Organize the Testing Effort
The earlier in the development cycle that testing becomes part of the effort the better. Planning is crucial to a successful testing effort, in part because it has a great deal to do with setting expectations. Considering budget, schedule, and performance in test plans increases the likelihood that testing does take place and is effective and efficient. Planning also ensures tests are not forgotten or repeated unless necessary for regression testing.

Requirements-Based Testing
The requirements section of the software specification does more than set benchmarks and list features. It also provides the basis for all testing on the product. After all, testing generally identifies defects that create, cause, or allow behavior not expected in the software based on descriptions in the specification; thus, the test team should be involved in the specification-writing process. Specification writers should maintain the following standards when presenting requirements:

1. All requirements should be unambiguous and interpretable only one way.
2. All requirements must be testable in a way that ensures the program complies.
3. All requirements should be binding because customers demand them.
You should begin designing test cases as the specification is being written. Analyze each specification from the viewpoint of how well it supports the development of test cases. The actual exercise of developing a test case forces you to think more critically about your specifications.

Develop a Test Plan
The test plan outlines the entire testing process and includes the individual test cases. To develop a solid test plan, you must systematically explore the program to ensure coverage is thorough, but not unnecessarily repetitive. A formal test plan establishes a testing process that does not depend upon accidental, random testing.

Testing, like development, can easily become a task that perpetuates itself. As such, the application specifications, and subsequently the test plan, should define the minimum acceptable quality to ship the application.

Test Plan Approaches: Waterfall versus Evolutionary
Two common approaches to testing are the waterfall approach and the evolutionary approach.

The waterfall approach is a traditional approach to testing that descends directly from the development team in which each person works in phases, from requirements analysis to various types of design and specification, to coding, final testing, and release. For the test team, this means waiting for a final spec and then following the pattern set by development. A significant disadvantage of this approach is that it eliminates the opportunity for testing to identify problems early in the process; therefore, it is best used only on small projects of limited complexity.

An alternative is the evolutionary approach in which you develop a modular piece (or unit) of an application, test it, fix it, feel somewhat satisfied with it, and then add another small piece that adds functionality. You then test the two units as an integrated component, increasing the complexity as you proceed. Some of the advantages to this approach are as follows:

1. You have low-cost opportunities to reappraise requirements and refine the design, as you understand the application better.
2. You are constantly delivering a working, useful product. If you are adding functionality in priority order, you could stop development at any time and know that the most important work is completed.
3. Rather than trying to develop one huge test plan, you can start with small, modular pieces of what will become part of the large, final test plan. In the interim, you can use the smaller pieces to find bugs.
4. You can add new sections to the test plan or go into depth in new areas, and use each part.
The range of the arguments associated with different approaches to testing is very large and well beyond the scope of this documentation. If the suggestions here do not seem to fit your project, you may want to do further research.

Optimization
A process closely related to testing is optimization. Optimization is the process by which bottlenecks are identified and removed by tuning the software, the hardware, or both. The optimization process consists of four key phases: collection, analysis, configuration, and testing. In the first phase of optimizing an application, you need to collect data to determine the baseline performance. Then by analyzing this data you can develop theories that identify potential bottlenecks. After making and documenting adjustments in configuration or code, you must repeat the initial testing and determine if your theories proved true. Without baseline performance data, it is impossible to determine if your modifications helped or hindered your application. For more information, see Performance Tuning Overview.
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