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Importance of Data Collection and Validation for Systematic Software Development Process


Affiliations
1 Anna University, Coimbatore, India
2 ADE, Defence Research and Development Organization, Bangalore, India
 

Systematic software development process involves estimation of size, effort, schedule and cost of a software project and analysis of critical factors affecting these estimates. In literature there are many methods for software estimation and categorization of critical factors. More than 50% of the projects undertaken have challenged the initially proposed estimates. Even if we consider updating estimates at various phases of software development, the percentage of challenged projects reduces marginally. The reason for such a situation is that the decisions are made on historical and collected data. Therefore, software data collection to a reasonable accuracy and its validation is important both for decision making and validating software development process. In this paper an effort is made to highlight the importance of software data collection. Collected data is utilized to validate effort estimation model formulated by the authors. Comparison of effort values obtained from popular estimation models is also made. The data collected has also helped in identifying the critical factors affecting the estimates.

Keywords

Software Size, Effort, Cost, Schedule, Risk, Estimation.
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  • Importance of Data Collection and Validation for Systematic Software Development Process

Abstract Views: 238  |  PDF Views: 119

Authors

Mala V. Patil
Anna University, Coimbatore, India
A. M. Nageswara Yogi
ADE, Defence Research and Development Organization, Bangalore, India

Abstract


Systematic software development process involves estimation of size, effort, schedule and cost of a software project and analysis of critical factors affecting these estimates. In literature there are many methods for software estimation and categorization of critical factors. More than 50% of the projects undertaken have challenged the initially proposed estimates. Even if we consider updating estimates at various phases of software development, the percentage of challenged projects reduces marginally. The reason for such a situation is that the decisions are made on historical and collected data. Therefore, software data collection to a reasonable accuracy and its validation is important both for decision making and validating software development process. In this paper an effort is made to highlight the importance of software data collection. Collected data is utilized to validate effort estimation model formulated by the authors. Comparison of effort values obtained from popular estimation models is also made. The data collected has also helped in identifying the critical factors affecting the estimates.

Keywords


Software Size, Effort, Cost, Schedule, Risk, Estimation.