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11 - Addressing Contemporary Concerns of Project Delivery

Published online by Cambridge University Press:  20 October 2018

Manoj Kumar Lal
Affiliation:
Tata Consultancy Services (TCS)
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Summary

As discussed in the earlier chapters, smooth project delivery is still a challenge and the IT industry is continuously working to make the project delivery more effective. This chapter discusses the relevance of KDD to important topics that are of interest for effective project delivery, other than DevOps and automation. The relevance of KDD to DevOps and automation has been discussed in separate chapters.

Shift Left

Shift Left refers to a practice in software development where teams focus on quality, work on prevention instead of detection and begin testing earlier than ever before. The goal is to increase quality, shorten long test cycles and reduce the possibility of unpleasant surprises towards the end of the development lifecycle.

Following traditional methodologies results in a substantial testing phase of the project delivery, and significant effort is spent on rework due to oversights made in the pre-testing phases. KDD, via its negative relationships and manual review of the catalogued project knowledge elements (requirement, solution design, application design and test design) that are integrated via exhaustive traceability, creates an effective static testing environment that has been largely absent in the existing methodologies.

The cost of quality in a typical project is close to 50% (in my experience) with the break-up as follows:

  • 1. About 25% effort goes in in test design, execution and management.

  • 2. One-third of the remaining 75% effort typically goes towards review and rework.

  • Shift left aims to optimise this one third of the remaining effort so that the test execution can be almost defect free. KDD reduces this one third of the review and rework effort through the catalogued knowledge capturing mechanism, the negative relationships review and manual review. Its benefits are:

  • 1. Review and rework is digitised via 516 data points of project knowledge and the related quality assurance. Due to the scientific way of handling review and rework, KDD reduces this effort up to 50% of the existing effort.

  • 2. Test cases are prepared by reusing inventories of solution design. OATS technique is used for optimised coverage. The entire set of test cases (from unit test to UAT) is prepared at one go and in the same format. Considering traditional end-to-end test design by different teams, the KDD approach has the potential to reduce the efforts spent in test design by half.

  • Type
    Chapter
    Information
    Knowledge Driven Development
    Bridging Waterfall and Agile Methodologies
    , pp. 203 - 213
    Publisher: Cambridge University Press
    Print publication year: 2018

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