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Defect Detection Percentage or Efficiency


What is Defect Detection and why it is necessary?

The Software industry has been progressing and evolving exponentially in the past few years. Software engineers are using their expert knowledge to deliver products that have superior quality and provide innovative and effortless services. To meet the high demand of quality and effective products, software developers and testers use various techniques, methodologies and tools to test and detect discrepancies and errors in the software. Defect detection is one such method, employed by software engineers to test the software application for bugs and defects. A software defect creates deviation between the expected and actual results, therefore it is extremely important for a tester to track them and remove them from the software. To give you a better understanding of Defect Detection and its elements, provided below is its detailed description.

Defining Defect Detection:

Detecting flaws and defects in the software is of utmost importance, as they can affect the quality, effectiveness, functionality and specification of that software. If these flaws or defects are left unattended, they can cause a huge disaster in the later stages, which can further harm the reputation of the organisation it was developed for. Therefore, testers who have complete understanding of the application under test, play a key role in detecting as many defects as possible. They execute well planned testing activities, which include various testing types, such as, System Testing, End to End Testing, Regression Testing, Exploratory Testing and more.

Moreover, several parameters are calculated by the testers in this phase to ensure its effectiveness and quality. These parameters are:

  1. Defect Detection Percentage (DDP): Also known as Defect Removal Efficiency, Defect Detection Percentage gives a measure of the testing effectiveness. It is calculated as a ratio of defects found prior to the release of the software as well as after its release by the customers. Technically Defect Detection Percentage (DDP) can be defined in the form of the following formula:
  2. DDE = [(Number of defects at the moment of software version release) / Total number of defects (raised by the internal testing team and the customers)] * 100

    Calculation: To be able to accurately calculate the metrics, the testers should properly track all the elements of the system during defect detection. Affected version, version of software in which this defect was found, release date, date when version was release, among other things should be calculated.

    Furthermore, Defect Detection Percentage can also be calculated from sub-metrics:

    • Number of escaped defects.
    • Number of defects found at the moment of software version release.

    Dimensions: The dimension in which it should be possible to monitor Defects Detection Percentage are:

    • In the affected versions.
    • Project or product. That is, to aggregate defect detection percentage over all released versions of the project or product.
    • .
    • Date.
    • .

      The Defect Detection Percentage ratio changes over time, as more defects are found by customers working with the version. Therefore, to get accurate visualization, it is best to use a line chart that starts with 100% at moment of software version release and a line representing a trend of how fast Defect Detection Percentage is declining. Furthermore, for iterative processes, one should see a bar chart representing Defect Detection Percentage value for each iteration/sprint after a small period of corresponding version release.

  3. Defect Detection Efficiency (DDE): Defect Detection Efficiency is another parameter that is calculated to ensure the quality and effectiveness of a software application. It is the number or the count of defects or bugs during a phase, which are inserted throughout the same phase and is divided by the complete number of bugs inserted throughout that phase. In Defect Detection Efficiency (DDE), the defects are conformed and agreed upon, not just reported. Also, dropped defects are not counted. It can be calculated in any phase in the Software Development Life Cycle (SDLC), where defects can be injected and detected. For example, Requirement, Design, and Coding. Furthermore, the phase a defect is ‘injected’ in is identified by analysing the defects.
  4. Formula: The formula for Defect Detection Efficiency (DDE) is:

    DDE = (Number of defects injected and detected in a phase/ Total number of defects injected in that phase) * 100.

    In this formula, the unit of the outcome is percentage (%).

    Uses of Defect Detection Efficiency (DDE):

    • Defect Detection Efficiency is used for calculating the quality of the approaches (efficiency of any approach) within the SDLC Software Development Life Cycle (SDLC), by calculating the degree to which bugs initiated throughout that stage are removed ahead they are sent into next stage.
    • For identifying the phases in the Software Development Life Cycle (SDLC) that are the weakest in terms of quality control and for focusing on them.

Benefits of Early Defect Detection:

Nowadays, software developers and testers aspire to create a software that is perfect in functionality and effectiveness. They use several testing techniques and methodologies to ensure that the end product is compatible to the requirements of the client. Defect Detection plays a very important role in Software Development Life Cycle, as it allows team of testers to check for defects and bugs at different levels of software development as well as after its release. Initiating defect detection in the early stages of development ensures that the product is checked for bugs and errors completely. The other benefits of early defect detection are:

  • It reduces fix and remediation cost.
  • The overall ADM spent is reduced.
  • Increases developer and QA staff productivity.
  • Reduces business risk due to outages.
  • Improves application security and overall code quality.

Conclusion

Defect detection is a valuable investment which helps in maintaining the quality of the product. It not only helps in improving the quality of the product but also saves the time and cost of the product, reduce the rework effort, reduce the development time, increase the customer satisfaction, which further enhances the total productivity. Detecting defects in software product development requires serious effort and the team of testers use the most efficient and effective methods ensure its accuracy. Furthermore, with the assistance of Defect Detection Percentage (DDP) and Defect Detection Efficiency (DDE) one can test the number of defects in various phases of software development. The team of tester use both of these parameters to calculate the quality and effectiveness of a software during the various Defect Detection phases and validate exceptional results.

Calculation Metrics

To calculate DDE appropriately, there are certain metrics which have to keep in mind while evaluating efficiency:

  1. Affected Version.
  2. Release Date.
  3. Number of Defects.
  4. Number of Escaped Defects.

There are some important key points which may be observed during testing and DDE calculation::

  1. This calculative approach says a lot about productivity of a team. This mathematical illustration helps to regain productivity by applying required efforts.
  2. Sometimes, it’s not only about team productivity, there may be a serious concern about understanding of a particular domain, may be some training issues, quality of a code in testing process.
  3. At the time of testing, if each phase has lesser number of defects than the previous one then the improvement in the code may be ensured.
  4. After the complete test calculation, a thorough analysis can be carried out by this mathematical concept.

Conclusion:

For better reliability and functionality of a software or an application, the foremost factor during testing is 'Defect Detection' and for accurate approximation it is imperative to calculate defect detection efficiency or percentage (DDE/DDP). This mathematical methodology leads any process in a positive direction which subsequently provides higher productivity and desired results.