[1 of 5] Coding Effort: Taking Software Development Process Improvement to the Next Level

ABSTRACT
The cost of maintaining software applications now accounts for about half of the average IT budget and continues to rise[1]. Labour costs make up more than 80 percent of software development. Yet, labour is also the most difficult resource to optimize.

The key factors in taking control of software development costs are: The transparency of the end-to-end development process to help identify waste and inefficiency, and a clear view of software development resource utilization.
A central tenant of any engineering process is that of being able to reliably measure the output of the production process. Measures of quality are of course crucial however the value of quality metrics can only be realised when evaluated within the context of the overall coding effort or change within which defects were introduced. Metrics around coding effort are remarkably absent from most software development organisations which is surprising given the constant drive to improve the software development process by increasing efficiency and improving quality.

This paper presents different approaches that can be taken to quantifying developer effort and how it can be used to improve the efficiency of the software development process and to enable other initiatives such as risk based testing.

EFFORT IS THE MISSING INCREDIENT
Any of the production engineering processes that have caught the attention of the software development community have the concept of output at their core. For example, recently the concept of "Lean Manufacturing" has garnered some interest from the software development community. Lean Manufacturing inherently has the concept of minimising wastage at its core. Central to understanding waste is understanding where effort is invested - coding effort is clearly one of the major components of the software development process and this is the activity that generates the vast majority of defects that are encountered in the testing phases of most projects.
Obtaining objective and reliable measures of coding effort enables many process improvement initiatives such as:

• Phase Containment: Ensuring that coding effort stays in the coding phase.
• Risk Based Testing: Focusing the testing team's efforts into areas of significant coding effort.
• Application Portfolio Analysis: Consistent measures of coding effort enabling a consistent software development process review across the organisation-wide application portfolio.

CODING EFFORT IN ACTION
This paper will provide real-world case studies of how coding effort metrics have been used to deliver tangible software development process improvements.

[1] Applying Lean to Application Development and Maintenance. Noah B. Kindler, Vasantha Krishnakanthan, and Ranjit Tinaikar, McKinsey on IT, Spring 2007

Category:

Science & Technology

Tags:

• Risk Based Testing
• KPI
• Efficiency
• Process Improvement