Browse minware's detailed reports on bug management, change control/code review compliance, DORA metrics, and uptime/bug SLA reports to ensure your teams maintain a high level of quality.

Stay on top of quality with minware's DORA, uptime, bug, and change control reports.

The uptime dashboard tracks time spent with open high-priority issues. It provides metrics showing both the highest priority (e.g., P1) and a second-tier high priority (e.g., P2).

The dashboard helps you visualize issues that cause downtime by team, issue type and ticket, including a breakdown of how long each high-priority ticket was open.

This report helps you monitor the impact of quality problems across a complex organization with multiple teams and track how well you are doing in one central dashboard.

Uptime and downtime metrics are essential KPIs for ensuring that your teams avoid quality problems with strong test automation, and are able to fix them quickly once they arise.

The difference between this report and what you might see in a system like PagerDuty, OpsGenie, or AWS CloudWatch is that it tracks outages at the ticket level based on data from Jira or other ticketing systems.

Oftentimes non-ticket uptime metrics don’t capture the full scope of outages since they may start prior to alarms going off, or not be fully resolved until tickets are marked done, which can happen after alarms subside. 

Organizations also sometimes have high-priority issues that don’t trip any alarms at all, which makes a ticket-based uptime dashboard critical for comprehensive observability.


Uptime Dashboard

Monitor time with open high-priority issues by team and ticket.

Bugs

Quality

KPIs

Tickets

This report offers the four classic DORA metrics, plus lead time at the ticket level to give you a holistic view of your team’s delivery performance.

The four classic DORA metrics are:

* **Deployment Frequency** - Measure how frequently your team deploys to production. Strong numbers here of one or more deployments per day indicate a healthy build and deployment process with a high degree of automation.
* **Lead Time for Changes** - This metric is computed as the average time from first commit to deployment by pull request (PR). It indicates not only the health and frequency of the deployment process, but also that changes happen in small pull requests that are reviewed and merged quickly. This report additionally shows a breakdown of lead time by stage, including first commit to PR open, PR review, PR merge, and deployment.
* **Change Failure Rate** - This number shows how much of the time a deployment results in a high-severity incident. This report computes change failure rate by dividing the number of new high-priority tickets by the number of deployments in a given time period. This metric is a good indicator of code quality, change complexity, and test coverage.
* **Time to Restore Service** - Also known as mean time to restore (MTTR), this metric shows the average amount of time it takes to resolve an incident once it occurs. It is measured by the time from creation to completion for high-priority incident tickets.

This report also provides a bonus metric: **Ticket Lead Time**. Pull request lead time is important, but it doesn’t show how long it takes for customers to _see value_ for more complex tickets with multiple pull requests. Ticket lead time gives you a more clear picture of how long it takes to deliver finished features.


DORA Metrics

Track the four classic DORA metrics plus ticket lead time.

Workflow

The bug management report tracks how consistently teams are following best practices for managing bugs, and the total portion of time they spend on bug fixes.

First, it looks at whether each project has a system in place for indicating bug severity and if bugs are being filed with non-default severity levels, which is important for providing visibility into the impact of bugs.

Next, the report looks at what portion of new bugs are being fixed within 30 days. If this metric drops too low, it can indicate that the team is deliberately sacrificing quality to maintain their feature velocity.

Finally, the report measures the total amount of time that the team spends on fixing bugs. This can help highlight teams who spend too much time fixing bugs and may benefit from investments in test coverage and infrastructure to reduce the bug load as a portion of overall work time.


Bug Management

Track how consistently teams manage bugs and their overall bug fixing load.


The code/ticket traceability report shows you how consistently software engineers write code in version control systems like GitHub, GitLab, Azure DevOps, or Bitbucket that is traceable to tickets or issues in systems like Jira or GitHub Issues.

The report first looks at how many commits are untraceable because they are made directly to a main/master branch, or to a shared integration branch such as develop, staging or qa.

Next, the report looks for code that is untraceable because it is merged directly (e.g., using the git merge command) to main without using a pull request (called a merge request in GitLab).

Finally, the report shows how often code links to a known ticket. It searches branch names, commit messages, pull request titles, and pull request bodies for ticket links.

Because real life is never 100% perfect, the scores are weighted by how much time developers spend on untraceable code. This helps you focus on improving in areas that will have the biggest impact, with the goal of driving down the percentage of untraceable work.

This report also lets you drill down into teams, people, and specific pull requests to identify the biggest sources of untraceable work.


## Why Is Code/Ticket Traceability Important?

Code/ticket traceability is important because it lets you see where people – your most valuable resource – are spending their time.


### Cost Capitalization

Traceability is crucial for accurately allocating developer salary costs to tasks, projects, and initiatives in your ticketing system.

Cost allocation is a requirement if you’re doing R&D or cost capitalization for accounting (which is now mandatory for U.S. companies due to [Section 174](https://www.kbkg.com/tax-insight/kbkg-tax-insight-irs-releases-guidance-on-section-174-re-expenses)). But, even if you’re not capitalizing development costs on your balance sheet, CEOs, CFOs, and boards often want to see where their engineering salary costs are going for management purposes.

Without automated code/ticket traceability, organizations often resort to manual time tracking. Not only does manual time tracking actually waste developers’ time; it is less accurate because people tend not to log separate entries for small tasks and interruptions, which can have a big impact in aggregate.


### Change Control Compliance

Code/ticket traceability is also a critical component of a secure software development process.

If developers write code that makes it into production without having an associated pull request and ticket, then there is no record of whether it was properly reviewed and prioritized according to the organization’s change control policies.

Failure to follow change control guidelines can result in insecure or improperly vetted code reaching customers, which can compromise the organization’s security.

Furthermore, if you undergo a security audit for standards like SOC 2, untraceable code puts you at risk of having an audit exception if discovered by the auditor. The code/ticket traceability report can also be a great piece of evidence to provide to auditors to demonstrate consistent compliance with change control procedures.


## How Does the Code/Ticket Traceability Report Work?

The code/ticket traceability works by identifying all of the commits made by each author in your organization. It then associates these commits with merges and pull requests. Finally, it looks at commit messages, branch names, pull request titles, and pull request bodies to find ticket IDs that link back to your ticketing system.

The report then calculates how much time is spent on each commit to provide an overall score showing the percentage of traceable coding time, which is aggregated by team, person, and pull request.


## FAQ


### How does the code/ticket traceability report match ticket identifiers?

The code/ticket traceability matches ticket identifiers using a regular expression pattern that looks for valid ticket identifiers. It is case-insensitive and tolerates certain typos.

Additionally, the report verifies that any matches correspond to actual tickets, so, e.g., DEV-99999999 would not count as traceable unless a ticket with that ID actually exists.


### Where does the report look for ticket identifiers?

The report looks for ticket identifier matches in the branch name (also called a “ref”), pull request title, and pull request body. It also looks in commit messages, but commits with ticket identifiers in the commit message can still fail the “use of branches” and “use of pull requests” scorecard checks in this report if they are on a main/master branch or not part of a pull request because they bypass the change control process.


### Does the report handle squash and rebase merges?

Yes, the report properly follows commits through squash and rebase merges using metadata available in pull request records so that they are treated the same way as regular merges. Code written in squashed or rebased commits will be checked for use of pull requests and ticket traceability.


### How does the report handle Git flows with multiple levels of pull requests?

For Git flows with multiple levels of pull requests, like having a side branch that is merged into a feature branch, then into development, and finally into main/master, the report searches for ticket identifiers in all pull requests until the code reaches an integration branch.

In the above example, if the first side branch pull request does not have a ticket identifier, but the PR from the feature branch into development does, then commits on the side branch will be properly counted as linking to a ticket.

However, if the feature branch PR also does not have a ticket, but the PR from development into master mentions some ticket in the body, then the side and feature branch commits will _not_ count as linking to a ticket because they did not have a ticket before reaching development – an integration branch associated with multiple features. In this scenario, mentions of tickets when merging from development to master are disregarded because it’s unclear which specific commits they are associated with.


### What version control systems are supported?

minware currently supports GitHub, GitLab, Bitbucket, and Azure DevOps Git version control systems.


### What ticketing systems are supported?

minware currently supports Jira and GitHub Issues as ticketing systems.


### How are deleted or moved tickets handled?

The report is currently unable to identify code that is linked to a ticket that no longer exists at its original ID because it has been deleted or moved. Deleting tickets is generally an anti-pattern and instead they should be resolved as “won’t fix” or a similar status to preserve traceability.


### How is code from bots or outside contributors treated?

This report excludes commits from bots and users outside of your organization in forked repositories so that they don’t count against the metrics.


Code/Ticket Traceability Report Screenshot

Code/Ticket Traceability

Track how consistently code is traceable to tickets via linked pull requests.

Capitalization

The Change Control Compliance report automatically calculates the percentage of time where work is done in compliance with the following change control best practices: use of branches, use of pull requests, and code reviews.

The Change Control Compliance report displays the percentage of time spent spent in the following ways:

  1. On commits in a non-main branch
  2. On branches merged through a pull/merge request
  3. On merged branches that received a code review

You can easily customize the report to filter by team or person to see more detail on how well various groups perform on these metrics.

Adhering to these best practices results in the following benefits:

  1. Shared knowledge across the team
  2. Improved code quality, security, and performance
  3. Auditability of code changes for compliance purposes

This report is useful to team leads, engineering leaders, security teams, and anyone interested in how well the organization complies with change control best practices.

Change Control Compliance Report Screen Shot

Report Templates: Quality

Code/Ticket Traceability

Bug Management

Change Control Compliance

Uptime Dashboard

DORA Metrics

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