Question

1). Is the relationship between the module size (Lines of code) and defect density positive or negatvie? carefully explain it

2). Assume you work for an organization that is interested in quantifying its software development. Write a report suggesting appropriate metrics.

Answer 1

Q1) Is the relationship between the module size (Lines of code) and defect density positive or negatvie? carefully explain it?

Source lines of code (SLOC), also known as lines of code (LOC), is a software metric used to measure the size of a computer program by counting the number of lines in the text of the program's source code. SLOC is typically used to predict the amount of effort that will be required to develop a program, as well as to estimate programming productivity or maintainability once the software is produced.

Defect Density is the number of defects confirmed in software/module during a specific period of operation or development divided by the size of the software/module. It enables one to decide if a piece of software is ready to be released. Defect density is counted per thousand lines of code also known as KLOC

Formula to measure Defect Density:

Defect Density = Defect count/ size of the release = Number of Defects Found / KLOC

Positive Defect Density = 1 Defect Found per thousand lines of code is considered to be good / Positive Defect Density

Negative Defect Density = More than 1 Defect Found per thousand lines of code is considered to be bad/ Negative Defect Density.

Q2) Assume you work for an organization that is interested in quantifying its software development. Write a report suggesting appropriate metrics.

• Cycle Time -  Cycle time measures the amount of time spent working on an issue. Cycle time is the time it takes from an issue to “cycle” from one state to another, usually from some open state to a finished state. Cycle time is a way to understand a team’s speed by breaking total throughput down to median time by either issue type, or status. Cycle times help you understand your team’s speed in a different way than velocity or total throughput. By monitoring the time it take for work to progress through your process, you can accurately set expectations or identify bottlenecks affecting your team

• Velocity - Software development Velocity is a measure of delivered value by the team. Delivered value is typically described as the number of features completed within a period that are ready to ship or ready to test. Velocity is one of the most popular metrics for tracking the pacing of the team and the objective is to establish a baseline, so you set delivery expectations (when will we finish given the current backlog?) and understand if the team is blocked (falling velocity) or if your process changes are working (stable or increased velocity). It’s important to consider the volatility of your velocity?—?how iterations are deviating from the average.

• Throughput - Software development Throughput is a measure of total work output by the team. Throughput is the number of features, tasks or chores, and bugs completed within a period that are ready to ship or ready to test. Throughput is another popular pacing metric like Velocity, but it expresses the total number of units of work (usually tickets) that the team has completed. By measuring throughput, you’re looking for alignment with your goals?—?if you’re focused on squashing bugs, you should see a healthy mix of defect tickets being resolved, and if you are focused on features, more featured tickets will be delivered than chores and bugs. If the team is blocked, throughput will drop, and it’s time to dig into root causes

• Release Cycle Time - This metric is a spinoff of of Cycle Time that tracks your team’s total time per release. It measures the time from when a release began to when it was shipped. Tracking Release Cycle Time will help identify areas for improvement (decrease time to/between releases) and set expectations. While this is a Speed metric, it can also be used to help measure how accurate you are at predictably shipping and manage expectations for future releases. Additionally, with a trend over time, this metric can help to raise flags on bottlenecks and process inefficiencies affecting release deliver.

?Please let me know in case of any clarifications required. Thanks!