23 software development metrics to track today

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Software development metrics can reveal an application’s performance and the effectiveness of the development team in their work.

IT organizations rely on a range of these KPIs to fully understand the progress of software engineers, as well as software quality, such as performance and user satisfaction. The range of possible measures spans four key categories:

  1. developer productivity
  2. software performance
  3. faults and safety
  4. user experience (UX)

While an IT organization doesn’t need to compile all of the software metrics, it should prioritize and track those that matter most to its requirements and goals. Analyze these 23 software development metrics and create a set of KPIs for software quality.

Developer productivity indicators

There are many ways to discuss or assess the effectiveness of the team and the work accomplished. Productivity metrics allow development managers to better manage projects. Tab a mix of these software metrics to gauge a project’s progress, developer productivity levels, the amount of additional development time needed, and more.

  1. Lead time. Turnaround time is the time it takes for something from start to finish. In software development, for example, the lead time for a project begins with the proposal and ends with the delivery.
  2. Code quantity. Development teams can view this software metric, also known as thousands of lines of code (KLOC), to determine the size of an application. If this KPI is high, it may indicate that developers have been productive in their programming efforts. However, this metric is not useful when a development team is trying to compare two projects written in different programming languages. Also, keep in mind that more code doesn’t always lead to effective or efficient code, which can lead to more refactoring work down the road.
  3. Work in progress (WIP). In a software engineering context, WIP is development work on which the team has started working and which is no longer in the backlog. A team can express WIP in a burn down chart. A common tool for Agile and Scrum sprints, these charts show how much work the team has completed and how much work remains to be done.
  4. Agile speed. To calculate velocity, an Agile software development team looks at previous sprints and counts the number of user stories or story points completed over time. Agile Velocity is an estimate of the team’s productivity during a single sprint.
  5. Sprint goal success rate. This software metric calculates the percentage of items the development team has completed in the sprint backlog. A team may not complete 100% of the work in a given sprint. However, the team’s progress could still reach its definition of fact – the threshold that a project must reach for an organization to consider it finished. If the iteration meets the definition of done, it is successful.
  6. Number of software versions. Agile and DevOps teams prioritize frequent and continuous software releases. With this KPI, teams can track how often they release software, whether it’s monthly, weekly, daily, hourly, or whatever, and whether that cadence ultimately delivers enough business value.

Software performance indicators

Software performance refers to quantitative measures of the behavior of a software system. Performance metrics assess non-functional attributes, that is, How? ‘Or’ What an application is running, no What He is doing.

  1. Software performance aspects. Performance tests can assess the following characteristics of an application:

Other important expressions of software performance metrics are as follows.

  1. Debit. Throughput is the number of units of data that a system processes in a certain period of time.
  2. Response time. response time measures the time it takes for a system to respond to a request or request.
  3. Reliability, availability and serviceability (RAS). RAS refers to the software’s ability to persistently meet its specifications; how long it works compared to the expected amount; and how easily it can be repaired or maintained.

Defect metrics

Development teams need to understand how applications fail in order to build them better. These software development metrics assess flaws and vulnerabilities.

  1. Density of defects. At the code level, developers can tabulate the number of faults per KLOC to assess the frequency of faults.
  2. Code coverage. This is the proportion of source code covered by automated testing. Software metrics allow testers to identify areas of code that they have not yet properly tested.
  3. Percentage of fault detection. This metric is a ratio of the number of defects found before software releases to the number found after release. To calculate the percentage, take the number of faults found before exit (x) and the number of users encountered after exit (y), then calculate x / (x + y). A high percentage is preferable, as it means that a higher proportion of defects were detected before customers used the software.
  4. Technical debt. Technical debt is a metaphor that reflects the long-term effort, as well as the time and financial costs, of developers failing to address a development problem when it first arises.

16. Security vulnerabilities. Vulnerability scans identify security weaknesses in an application. The lower the number of vulnerabilities found, the more secure the software will be.

17. Real security incidents. This KPI counts the number of times a hacker exploits a vulnerability in the software. Track how often these breaches occur, the severity of the attack – for example, data stolen – and the duration of the incident.

IT organizations use various averages to calculate the occurrence of software failures or defects.

  1. Average time to detect. Average detection time is an average that indicates how long it takes for a team to notice a problem or bug.
  2. Average time between failures. This metric is a calculation of how often a program fails.
  3. Average repair time. Average time to repair is the average that represents how quickly a team resolves failures.

Usability metrics and UX

Users experience and interact with software in different ways. Just as it is difficult to categorize people’s emotions, it is also difficult to gauge their reaction to software. While no software metric can communicate the entire UX, there are a few that are useful.

  1. UX metrics. User experience metrics are often qualitative and can include users’ emotional or bodily responses, such as their trust in software and the way their eyes move on a user interface.
  2. Usability metrics. Usability measures the extent to which the software enables customers to achieve their goals. Usability can be broken down into smaller components, such as the following:
  1. Net Promoter Score (NPS). This software metric reflects the willingness of customers to recommend an application to others. The Net Promoter Score is presented as a range of numbers from 0 to 10. Customers with a score of 0 to 6 are Critics; Notes 7 and 8 are Liabilities; and 9 and 10 are Promoters.

Next steps

Build the five stages of a continuous delivery maturity model

Project management tools and strategies: Gantt charts, PERT charts and PM planning tools


Deepen the design and development of software





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