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Duplicate code, for example, reimplementing code that is available in a common library
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Design issue, for example, the design of the implementation is suboptimal or does not solve the coding problem as efficiently as necessary
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Functional issue, for example, the implementation Functional bugs can lead to implementation of new contains a bug or is missing part of the guidelines or techniques to be applied in developer functionality (omission error) testing. Spelling errors Implement spell checking in the integrated development environment (IDE).
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Time Is on My Side An accurate measurement of code review effectiveness requires accurate knowledge of the time spent on reviews. You could just ask the team how much time they spent reviewing code, but the answers, as you'd guess, would be highly inaccurate. This is one of the reasons teams that want to measure the value of code reviews use some type of code review tool for all of their code reviews. If the reviews are conducted in the framework of a review tool, time spent on the review task can be tracked more easily. There are, of course, some difficulties in measuring time spent on review as part of application usage. One mostly accurate solution is to monitor interaction with the application (keystrokes, mouse movements, and focus) to determine whether the reviewer is actively reviewing code or merely has the code review window open. Time spent on code reviews can be an interesting metric in the context of other metrics and can answer
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the following questions: What percentage of our time did we spend on code review versus code implementation How much time do we spend reviewing per thousand lines of code (KLOC) What percentage of our time was spent on code reviews this release versus the last release What is the ratio of time spent to errors discovered (issues per review hour) What is the ratio of issues per review hour to bugs found by test or customer And so on The preceding questions are samples. To determine the right answers for a particular situation, you need to ask yourself what the goals of code review are for your team. If the goals are to spot-check code before check-in, the time on task measurement might not be very interesting. But if you are interested in improving effectiveness or efficiency, some of these questions might help you determine whether you are reaching your goals. More Review Collateral Much more happens in a code review other than identifying rework. An important part of the process that is often lost over time is the conversations and comments about a piece of code. For example, when I have some code ready for review, I don't say, "Here's my code take a look." Instead, I put together an introductory e-mail message with a few sentences or a paragraph describing what the code is doing (for example, fixing a bug or adding a feature), and I might describe some of my implementation decisions. This information helps the reviewers do a better job, but when the review is over, that information is lost. The loss gets worse when considering that the follow-up conversations whether they are in e-mail, in a team review, or face to face are also lost. Over time, this lost information can lead to difficulties in knowledge transfer and maintainability issues. Another way a review tool can aid with code reviews is by tracking some of this collateral data. A code review tool can contain questions, comments, conversations, and other metadata and link them with the code. Anyone on the team can look at a source file and view the changes along with explanations and conversations regarding any change. If someone on the team needs to ramp up quickly on the background pertaining to a single file or component (for example, a new developer on the team), a tool could queue up all of the changes and related review comments and play them back in a movie or slide show. This movie wouldn't win an Oscar, but it would have phenomenal potential for preparing new team members (or existing team members taking on new responsibilities) quickly.
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