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by Dinesh Thakur Category: Software Engineering

To assess the quality of the engineered product or system and to better understand the models that are created, some measures are used. These measures are collected throughout the software development life cycle with an intention to improve the software process on a continuous basis. Measurement helps in estimation, quality control, productivity assessment and project control throughout a software project. Also, measurement is used by software engineers to gain insight into the design and development of the work products. In addition, measurement assists in strategic decision-making as a project proceeds.

Software measurements are of two categories, namely, direct measures and indirect measures. Direct measures include software processes like cost and effort applied and products like lines of code produced, execution speed, and other defects that have been reported. Indirect measures include products like functionality, quality, complexity, reliability, maintainability, and many more.

Generally, software measurement is considered as a management tool which if conducted in an effective manner, helps the project manager and the entire software team to take decisions that lead to successful completion of the project. Measurement process is characterized by a set of five activities, which are listed below.

  • Formulation: This performs measurement and develops appropriate metric for software under consideration.
  • Collection: This collects data to derive the formulated metrics.
  • Analysis: This calculates metrics and the use of mathematical tools.
  • Interpretation: This analyzes the metrics to attain insight into the quality of representation.
  • Feedback: This communicates recommendation derived from product metrics to the software team.

Note that collection and analysis activities drive the measurement process. In order to perform these activities effectively, it is recommended to automate data collection and analysis, establish guidelines and recommendations for each metric, and use statistical techniques to interrelate external quality features and internal product attributes.

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