What is a reasonable code coverage for unit tests and why

Question

If you were to mandate a minimum percentage code-coverage for unit tests  perhaps even as a requirement for committing to a repository  what would it be   Please explain how you arrived at your answer  since if all you did was pick a number  then I could have done that all by myself

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Depending on the criticality of the code  anywhere from 75 -85  is a good rule of thumb  Shipping code should definitely be tested more thoroughly than in house utilities  etc

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I d have another anectode on test coverage I d like to share   We have a huge project wherein  over twitter  I noted that  with 700 unit tests  we only have 20  code coverage   Scott Hanselman replied with words of wisdom      Is it the RIGHT 20   Is it the 20    that represents the code your users   hit the most  You might add 50 more   tests and only add 2     Again  it goes back to my Testivus on Code Coverage Answer  How much rice should you put in the pot  It depends

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I think the best symptom of correct code coverage is that amount of concrete problems unit tests help to fix is reasonably corresponds to size of unit tests code you created

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I think the best symptom of correct code coverage is that amount of concrete problems unit tests help to fix is reasonably corresponds to size of unit tests code you created

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From the Testivus posting I think the answer context should be the second programmer  Having said this from a practical point of view we need parameter   goals to strive for  I consider that this can be  tested  in an Agile process by analyzing the code we have the architecture  functionality  user stories   and then come up with a number  Based on my experience in the Telecom area I would say that 60  is a good value to check

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Check out Crap4j  It s a slightly more sophisticated approach than straight code coverage  It combines code coverage measurements with complexity measurements  and then shows you what complex code isn t currently tested

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Many shops don t value tests  so if you are above zero at least there is some appreciation of worth - so arguably non-zero isn t bad as many are still zero   In the  Net world people often quote 80  as reasonble  But they say this at solution level  I prefer to measure at project level  30  might be fine for UI project if you ve got Selenium  etc or manual tests  20  for the data layer project might be fine  but 95   might be quite achievable for the business rules layer  if not wholly necessary  So the overall coverage may be  say  60   but the critical business logic may be much higher   I ve also heard this  aspire to 100  and you ll hit 80   but aspire to 80  and you ll hit 40    Bottom line  Apply the 80 20 rule  and let your app s bug count guide you

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I don t think there can be such a B W rule  Code should be reviewed  with particular attention to the critical details  However  if it hasn t been tested  it has a bug

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This has to be dependent on what phase of your application development lifecycle you are in     If you ve been at development for a while and have a lot of implemented code already and are just now realizing that you need to think about code coverage then you have to check your current coverage  if it exists  and then use that baseline to set milestones each sprint  or an average rise over a period of sprints   which means taking on code debt while continuing to deliver end user value  at least in my experience the end user doesn t care one bit if you ve increased test coverage if they don t see new features      Depending on your domain it s not unreasonable to shoot for 95   but I d have to say on average your going to be looking at an average case of 85  to 90

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If you ve been doing unit testing for a decent amount of time  I see no reason for it not to be approaching 95    However  at a minimum  I ve always worked with 80   even when new to testing   This number should only include code written in the project  excludes frameworks  plugins  etc   and maybe even exclude certain classes composed entirely of code written of calls to outside code  This sort of call should be mocked stubbed

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Viewing coverage from another perspective  Well-written code with a clear flow of control is the easiest to cover  the easiest to read  and usually the least buggy code  By writing code with clearness and coverability in mind  and by writing the unit tests in parallel with the code  you get the best results IMHO

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Viewing coverage from another perspective  Well-written code with a clear flow of control is the easiest to cover  the easiest to read  and usually the least buggy code  By writing code with clearness and coverability in mind  and by writing the unit tests in parallel with the code  you get the best results IMHO

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I use cobertura  and whatever the percentage  I would recommend keeping the values in the cobertura-check task up-to-date  At the minimum  keep raising totallinerate and totalbranchrate to just below your current coverage  but never lower those values  Also tie in the Ant build failure property to this task  If the build fails because of lack of coverage  you know someone s added code but hasn t tested it  Example    lt cobertura-check linerate  0                   branchrate  0                   totallinerate  70                   totalbranchrate  90                   failureproperty  build failed    gt

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Code Coverage is a misleading metric if 100  coverage is your goal  instead of 100  testing of all features      You could get a 100  by hitting all the lines once  However you could still miss out testing a particular sequence  logical path  in which those lines are hit  You could not get a 100  but still have tested all your 80  freq used code-paths  Having tests that test every  throw ExceptionTypeX  or similar defensive programming guard you ve put in is a  nice to have  not a  must have     So trust yourself or your developers to be thorough and cover every path through their code  Be pragmatic and don t chase the magical 100  coverage  If you TDD your code you should get a 90   coverage as a bonus  Use code-coverage to highlight chunks of code you have missed  shouldn t happen if you TDD though   since you write code only to make a test pass  No code can exist without its partner test

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When I think my code isn t unit tested enough  and I m not sure what to test next  I use coverage to help me decide what to test next   If I increase coverage in a unit test - I know this unit test worth something   This goes for code that is not covered  50  covered or 97  covered

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If this were a perfect world  100  of code would be covered by unit tests  However  since this is NOT a perfect world  it s a matter of what you have time for  As a result  I recommend focusing less on a specific percentage  and focusing more on the critical areas   If your code is well-written  or at least a reasonable facsimile thereof  there should be several key points where APIs are exposed to other code    Focus your testing efforts on these APIs  Make sure that the APIs are 1  well documented and 2  have test cases written that match the documentation  If the expected results don t match up with the docs  then you have a bug in either your code  documentation  or test cases  All of which are good to vet out   Good luck

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If this were a perfect world  100  of code would be covered by unit tests  However  since this is NOT a perfect world  it s a matter of what you have time for  As a result  I recommend focusing less on a specific percentage  and focusing more on the critical areas   If your code is well-written  or at least a reasonable facsimile thereof  there should be several key points where APIs are exposed to other code    Focus your testing efforts on these APIs  Make sure that the APIs are 1  well documented and 2  have test cases written that match the documentation  If the expected results don t match up with the docs  then you have a bug in either your code  documentation  or test cases  All of which are good to vet out   Good luck

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If this were a perfect world  100  of code would be covered by unit tests  However  since this is NOT a perfect world  it s a matter of what you have time for  As a result  I recommend focusing less on a specific percentage  and focusing more on the critical areas   If your code is well-written  or at least a reasonable facsimile thereof  there should be several key points where APIs are exposed to other code    Focus your testing efforts on these APIs  Make sure that the APIs are 1  well documented and 2  have test cases written that match the documentation  If the expected results don t match up with the docs  then you have a bug in either your code  documentation  or test cases  All of which are good to vet out   Good luck

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I don t think there can be such a B W rule  Code should be reviewed  with particular attention to the critical details  However  if it hasn t been tested  it has a bug

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It depends greatly on your application  For example  some applications consist mostly of GUI code that cannot be unit tested

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For a well designed system  where unit tests have driven the development from the start i would say 85  is a quite low number  Small classes designed to be testable should not be hard to cover better than that   It s easy to dismiss this question with something like    Covered lines do not equal tested logic and one should not read too much into the percentage    True  but there are some important points to be made about code coverage  In my experience this metric is actually quite useful  when used correctly  Having said that  I have not seen all systems and i m sure there are tons of them where it s hard to see code coverage analysis adding any real value  Code can look so different and the scope of the available test framework can vary   Also  my reasoning mainly concerns quite short test feedback loops  For the product that I m developing the shortest feedback loop is quite flexible  covering everything from class tests to inter process signalling  Testing a deliverable sub-product typically takes 5 minutes and for such a short feedback loop it is indeed possible to use the test results  and specifically the code coverage metric that we are looking at here  to reject or accept commits in the repository   When using the code coverage metric you should not just have a fixed  arbitrary  percentage which must be fulfilled  Doing this does not give you the real benefits of code coverage analysis in my opinion  Instead  define the following metrics    Low Water Mark  LWM   the lowest number of uncovered lines ever seen in the system under test High Water Mark  HWM   the highest code coverage percentage ever seen for the system under test   New code can only be added if we don t go above the LWM and we don t go below the HWM  In other words  code coverage is not allowed to decrease  and new code should be covered  Notice how i say should and not must  explained below    But doesn t this mean that it will be impossible to clean away old well-tested rubbish that you have no use for anymore  Yes  and that s why you have to be pragmatic about these things  There are situations when the rules have to be broken  but for your typical day-to-day integration my experience it that these metrics are quite useful  They give the following two implications    Testable code is promoted  When adding new code you really have to make an effort to make the code testable  because you will have to try and cover all of it with your test cases  Testable code is usually a good thing  Test coverage for legacy code is increasing over time  When adding new code and not being able to cover it with a test case  one can try to cover some legacy code instead to get around the LWM rule  This sometimes necessary cheating at least gives the positive side effect that the coverage of legacy code will increase over time  making the seemingly strict enforcement of these rules quite pragmatic in practice    And again  if the feedback loop is too long it might be completely unpractical to setup something like this in the integration process   I would also like to mention two more general benefits of the code coverage metric    Code coverage analysis is part of the dynamic code analysis  as opposed to the static one  i e  Lint   Problems found during the dynamic code analysis  by tools such as the purify family  http   www-03 ibm com software products en rational-purify-family  are things like uninitialized memory reads  UMR   memory leaks  etc  These problems can only be found if the code is covered by an executed test case  The code that is the hardest to cover in a test case is usually the abnormal cases in the system  but if you want the system to fail gracefully  i e  error trace instead of crash  you might want to put some effort into covering the abnormal cases in the dynamic code analysis as well  With just a little bit of bad luck  a UMR can lead to a segfault or worse  People take pride in keeping 100  for new code  and people discuss testing problems with a similar passion as other implementation problems  How can this function be written in a more testable manner  How would you go about trying to cover this abnormal case  etc    And a negative  for completeness    In a large project with many involved developers  everyone is not going to be a test-genius for sure  Some people tend to use the code coverage metric as proof that the code is tested and this is very far from the truth  as mentioned in many of the other answers to this question  It is ONE metric that can give you some nice benefits if used properly  but if it is misused it can in fact lead to bad testing  Aside from the very valuable side effects mentioned above a covered line only shows that the system under test can reach that line for some input data and that it can execute without hanging or crashing

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I prefer to do BDD  which uses a combination of automated acceptance tests  possibly other integration tests  and unit tests  The question for me is what the target coverage of the automated test suite as a whole should be   That aside  the answer depends on your methodology  language and testing and coverage tools  When doing TDD in Ruby or Python it s not hard to maintain 100  coverage  and it s well worth doing so  It s much easier to manage 100  coverage than 90-something percent coverage  That is  it s much easier to fill coverage gaps as they appear  and when doing TDD well coverage gaps are rare and usually worth your time  than it is to manage a list of coverage gaps that you haven t gotten around to and miss coverage regressions due to your constant background of uncovered code   The answer also depends on the history of your project  I ve only found the above to be practical in projects managed that way from the start  I ve greatly improved the coverage of large legacy projects  and it s been worth doing so  but I ve never found it practical to go back and fill every coverage gap  because old untested code is not well understood enough to do so correctly and quickly

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Depending on the criticality of the code  anywhere from 75 -85  is a good rule of thumb  Shipping code should definitely be tested more thoroughly than in house utilities  etc

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85  would be a good starting place for checkin criteria     I d probably chose a variety of higher bars for shipping criteria - depending on the criticality of the subsystems components being tested

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Short answer  60-80   Long answer  I think it totally depends on the nature of your project   I typically start a project by unit testing every practical piece   By the first  release  of the project you should have a pretty good base percentage based on the type of programming you are doing   At that point you can start  enforcing  a minimum code coverage

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In my opinion  the answer is  It depends on how much time you have    I try to achieve 100  but I don t make a fuss if I don t get it with the time I have     When I write unit tests  I wear a different hat compared to the hat I wear when developing production code   I think about what the tested code claims to do and what are the situations that can possible break it   I usually follow the following criteria or rules     That the Unit Test should be a form of documentation on what s the expected behavior of my codes  ie  the expected output given a certain input and the exceptions it may throw that clients may want to catch   What the users of my code should know   That the Unit Test should help me discover the what if conditions that I may not yet have thought of   How to make my code stable and robust     If these two rules doesn t produce 100  coverage then so be it   But once  I have the time  I analyze the uncovered blocks and lines and determine if there are still test cases without unit tests or if the code needs to be refactored to eliminate the unecessary codes

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Viewing coverage from another perspective  Well-written code with a clear flow of control is the easiest to cover  the easiest to read  and usually the least buggy code  By writing code with clearness and coverability in mind  and by writing the unit tests in parallel with the code  you get the best results IMHO

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My favorite code coverage is 100  with an asterisk  The asterisk comes because I prefer to use tools that allow me to mark certain lines as lines that  don t count   If I have covered 100  of the lines which  count   I am done   The underlying process is    I write my tests to exercise all the functionality and edge cases I can think of  usually working from the documentation   I run the code coverage tools I examine any lines or paths not covered and any that I consider not important or unreachable  due to defensive programming  I mark as not counting I write new tests to cover the missing lines and improve the documentation if those edge cases are not mentioned    This way if I and my collaborators add new code or change the tests in the future  there is a bright line to tell us if we missed something important - the coverage dropped below 100   However  it also provides the flexibility to deal with different testing priorities

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This has to be dependent on what phase of your application development lifecycle you are in     If you ve been at development for a while and have a lot of implemented code already and are just now realizing that you need to think about code coverage then you have to check your current coverage  if it exists  and then use that baseline to set milestones each sprint  or an average rise over a period of sprints   which means taking on code debt while continuing to deliver end user value  at least in my experience the end user doesn t care one bit if you ve increased test coverage if they don t see new features      Depending on your domain it s not unreasonable to shoot for 95   but I d have to say on average your going to be looking at an average case of 85  to 90

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I d have another anectode on test coverage I d like to share   We have a huge project wherein  over twitter  I noted that  with 700 unit tests  we only have 20  code coverage   Scott Hanselman replied with words of wisdom      Is it the RIGHT 20   Is it the 20    that represents the code your users   hit the most  You might add 50 more   tests and only add 2     Again  it goes back to my Testivus on Code Coverage Answer  How much rice should you put in the pot  It depends

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We were targeting  80  till few days back  But after we used a lot of Generated code  We do not care for  age  but rather make reviewer take a call on the coverage required

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Check out Crap4j  It s a slightly more sophisticated approach than straight code coverage  It combines code coverage measurements with complexity measurements  and then shows you what complex code isn t currently tested

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Code coverage is great  but functionality coverage is even better  I don t believe in covering every single line I write  But I do believe in writing 100  test coverage of all the functionality I want to provide  even for the extra cool features I came with myself and which were not discussed during the meetings    I don t care if I would have code which is not covered in tests  but I would care if I would refactor my code and end up having a different behaviour  Therefore  100  functionality coverage is my only target

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This has to be dependent on what phase of your application development lifecycle you are in     If you ve been at development for a while and have a lot of implemented code already and are just now realizing that you need to think about code coverage then you have to check your current coverage  if it exists  and then use that baseline to set milestones each sprint  or an average rise over a period of sprints   which means taking on code debt while continuing to deliver end user value  at least in my experience the end user doesn t care one bit if you ve increased test coverage if they don t see new features      Depending on your domain it s not unreasonable to shoot for 95   but I d have to say on average your going to be looking at an average case of 85  to 90

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We were targeting  80  till few days back  But after we used a lot of Generated code  We do not care for  age  but rather make reviewer take a call on the coverage required

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This prose by Alberto Savoia answers precisely that question  in a nicely entertaining manner at that     http   www artima com forums flat jsp forum 106 amp thread 204677     Testivus On Test Coverage      Early one morning  a programmer asked   the great master          I am ready to write some unit tests  What code coverage should I aim   for          The great master replied          Don   t worry about coverage  just write some good tests          The programmer smiled  bowed  and   left                Later that day  a second programmer   asked the same question       The great master pointed at a pot of   boiling water and said          How many grains of rice should I put in that pot          The programmer  looking puzzled    replied          How can I possibly tell you  It depends on how many people you need to   feed  how hungry they are  what other   food you are serving  how much rice   you have available  and so on             Exactly     said the great master       The second programmer smiled  bowed    and left                Toward the end of the day  a third   programmer came and asked the same   question about code coverage          Eighty percent and no less     Replied the master in a stern voice    pounding his fist on the table       The third programmer smiled  bowed    and left                After this last reply  a young   apprentice approached the great   master          Great master  today I overheard you answer the same question about   code coverage with three different   answers  Why          The great master stood up from his   chair          Come get some fresh tea with me and let   s talk about it          After they filled their cups with   smoking hot green tea  the great   master began to answer          The first programmer is new and just getting started with testing    Right now he has a lot of code and no   tests  He has a long way to go    focusing on code coverage at this time   would be depressing and quite useless    He   s better off just getting used to   writing and running some tests  He can   worry about coverage later             The second programmer  on the other hand  is quite experience both   at programming and testing  When I   replied by asking her how many grains   of rice I should put in a pot  I   helped her realize that the amount of   testing necessary depends on a number   of factors  and she knows those   factors better than I do     it   s her   code after all  There is no single    simple  answer  and she   s smart enough   to handle the truth and work with   that             I see     said the young apprentice       but if there is no single simple   answer  then why did you answer the   third programmer    Eighty percent and   no less             The great master laughed so hard and   loud that his belly  evidence that he   drank more than just green tea    flopped up and down          The third programmer wants only simple answers     even when there are   no simple answers     and then does not   follow them anyway          The young apprentice and the grizzled   great master finished drinking their   tea in contemplative silence

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Short answer  60-80   Long answer  I think it totally depends on the nature of your project   I typically start a project by unit testing every practical piece   By the first  release  of the project you should have a pretty good base percentage based on the type of programming you are doing   At that point you can start  enforcing  a minimum code coverage

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Short answer  60-80   Long answer  I think it totally depends on the nature of your project   I typically start a project by unit testing every practical piece   By the first  release  of the project you should have a pretty good base percentage based on the type of programming you are doing   At that point you can start  enforcing  a minimum code coverage

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Code Coverage is a misleading metric if 100  coverage is your goal  instead of 100  testing of all features      You could get a 100  by hitting all the lines once  However you could still miss out testing a particular sequence  logical path  in which those lines are hit  You could not get a 100  but still have tested all your 80  freq used code-paths  Having tests that test every  throw ExceptionTypeX  or similar defensive programming guard you ve put in is a  nice to have  not a  must have     So trust yourself or your developers to be thorough and cover every path through their code  Be pragmatic and don t chase the magical 100  coverage  If you TDD your code you should get a 90   coverage as a bonus  Use code-coverage to highlight chunks of code you have missed  shouldn t happen if you TDD though   since you write code only to make a test pass  No code can exist without its partner test

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The accepted answer makes a good point - there is not a single number that is going to make sense as a standard for every project  There are projects that just don t need such a standard  Where the accepted answer falls short  in my opinion  is in describing how one might make that decision for a given project   I will take a shot at doing so  I am not an expert in test engineering and would be happy to see a more informed answer   When to set code coverage requirements  First  why would you want to impose such a standard in the first place  In general  when you want to introduce empirical confidence in your process  What do I mean by  empirical confidence   Well  the real goal correctness  For most software  we can t possibly know this across all inputs  so we settle for saying that code is well-tested  This is more knowable  but is still a subjective standard  It will always be open to debate whether or not you have met it  Those debates are useful and should occur  but they also expose uncertainty   Code coverage is an objective measurement  Once you see your coverage report  there is no ambiguity about whether standards have been met are useful  Does it prove correctness  Not at all  but it has a clear relationship to how well-tested the code is  which in turn is our best way to increase confidence in its correctness  Code coverage is a measurable approximation of immeasurable qualities we care about   Some specific cases where having an empirical standard could add value    To satisfy stakeholders  For many projects  there are various actors who have an interest in software quality who may not be involved in the day-to-day development of the software  managers  technical leads  etc   Saying  we re going to write all the tests we really need  is not convincing  They either need to trust entirely  or verify with ongoing close oversight  assuming they even have the technical understanding to do so   Providing measurable standards and explaining how they reasonably approximate actual goals is better  To normalize team behavior  Stakeholders aside  if you are working on a team where multiple people are writing code and tests  there is room for ambiguity for what qualifies as  well-tested   Do all of your colleagues have the same idea of what level of testing is good enough  Probably not  How do you reconcile this  Find a metric you can all agree on and accept it as a reasonable approximation  This is especially  but not exclusively  useful in large teams  where leads may not have direct oversight over junior developers  for instance  Networks of trust matter as well  but without objective measurements  it is easy for group behavior to become inconsistent  even if everyone is acting in good faith  To keep yourself honest  Even if you re the only developer and only stakeholder for your project  you might have certain qualities in mind for the software  Instead of making ongoing subjective assessments about how well-tested the software is  which takes work   you can use code coverage as a reasonable approximation  and let machines measure it for you    Which metrics to use  Code coverage is not a single metric  there are several different ways of measuring coverage  Which one you might set a standard upon depends on what you re using that standard to satisfy   I ll use two common metrics as examples of when you might use them to set standards    Statement coverage  What percentage of statements have been executed during testing  Useful to get a sense of the physical coverage of your code  How much of the code that I have written have I actually tested    This kind of coverage supports a weaker correctness argument  but is also easier to achieve  If you re just using code coverage to ensure that things get tested  and not as an indicator of test quality beyond that  then statement coverage is probably sufficient   Branch coverage  When there is branching logic  e g  an if   have both branches been evaluated  This gives a better sense of the logical coverage of your code  How many of the possible paths my code may take have I tested    This kind of coverage is a much better indicator that a program has been tested across a comprehensive set of inputs  If you re using code coverage as your best empirical approximation for confidence in correctness  you should set standards based on branch coverage or similar     There are many other metrics  line coverage is similar to statement coverage  but yields different numeric results for multi-line statements  for instance  conditional coverage and path coverage is similar to branch coverage  but reflect a more detailed view of the possible permutations of program execution you might encounter    What percentage to require  Finally  back to the original question  If you set code coverage standards  what should that number be   Hopefully it s clear at this point that we re talking about an approximation to begin with  so any number we pick is going to be inherently approximate   Some numbers that one might choose    100   You might choose this because you want to be sure everything is tested  This doesn t give you any insight into test quality  but does tell you that some test of some quality has touched every statement  or branch  etc   Again  this comes back to degree of confidence  If your coverage is below 100   you know some subset of your code is untested     Some might argue that this is silly  and you should only test the parts of your code that are really important  I would argue that you should also only maintain the parts of your code that are really important  Code coverage can be improved by removing untested code  too   99   or 95   other numbers in the high nineties   Appropriate in cases where you want to convey a level of confidence similar to 100   but leave yourself some margin to not worry about the occasional hard-to-test corner of code  80   I ve seen this number in use a few times  and don t entirely know where it originates  I think it might be a weird misappropriation of the 80-20 rule  generally  the intent here is to show that most of your code is tested   Yes  51  would also be  most   but 80  is more reflective of what most people mean by most   This is appropriate for middle-ground cases where  well-tested  is not a high priority  you don t want to waste effort on low-value tests   but is enough of a priority that you d still like to have some standard in place    I haven t seen numbers below 80  in practice  and have a hard time imagining a case where one would set them  The role of these standards is to increase confidence in correctness  and numbers below 80  aren t particularly confidence-inspiring   Yes  this is subjective  but again  the idea is to make the subjective choice once when you set the standard  and then use an objective measurement going forward    Other notes  The above assumes that correctness is the goal  Code coverage is just information  it may be relevant to other goals  For instance  if you re concerned about maintainability  you probably care about loose coupling  which can be demonstrated by testability  which in turn can be measured  in certain fashions  by code coverage  So your code coverage standard provides an empirical basis for approximating the quality of  maintainability  as well

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Code coverage is great  but functionality coverage is even better  I don t believe in covering every single line I write  But I do believe in writing 100  test coverage of all the functionality I want to provide  even for the extra cool features I came with myself and which were not discussed during the meetings    I don t care if I would have code which is not covered in tests  but I would care if I would refactor my code and end up having a different behaviour  Therefore  100  functionality coverage is my only target

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It depends greatly on your application  For example  some applications consist mostly of GUI code that cannot be unit tested

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85  would be a good starting place for checkin criteria     I d probably chose a variety of higher bars for shipping criteria - depending on the criticality of the subsystems components being tested

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85  would be a good starting place for checkin criteria     I d probably chose a variety of higher bars for shipping criteria - depending on the criticality of the subsystems components being tested

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If you ve been doing unit testing for a decent amount of time  I see no reason for it not to be approaching 95    However  at a minimum  I ve always worked with 80   even when new to testing   This number should only include code written in the project  excludes frameworks  plugins  etc   and maybe even exclude certain classes composed entirely of code written of calls to outside code  This sort of call should be mocked stubbed

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Check out Crap4j  It s a slightly more sophisticated approach than straight code coverage  It combines code coverage measurements with complexity measurements  and then shows you what complex code isn t currently tested

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Code coverage is great but only as long as the benefits that you get from it outweigh the cost effort of achieving it   We have been working to a standard of 80  for some time  however we have just made the decison to abandon this and instead be more focused on our testing  Concentrating on the complex business logic etc   This decision was taken due to the increasing amount of time we spent chasing code coverage and maintaining existing unit tests  We felt we had got to the point where the benefit we were getting from our code coverage was deemed to be less than the effort that we had to put in to achieve it

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Code coverage is just another metric  In and of itself  it can be very misleading  see www thoughtworks com insights blog are-test-coverage-metrics-overrated   Your goal should therefore not be to achieve 100  code coverage but rather to ensure that you test all relevant scenarios of your application

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Generally speaking  from the several engineering excellence best practices papers that I have read  80  for new code in unit tests is the point that yields the best return   Going above that CC  yields a lower amount of defects for the amount of effort exerted    This is a best practice that is used by many major corporations   Unfortunately  most of these results are internal to companies  so there are no public literatures that I can point you to

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My answer to this conundrum is to have 100  line coverage of the code you can test and 0  line coverage of the code you can t test   My current practice in Python is to divide my  py modules into two folders  app1  and app2  and when running unit tests calculate the coverage of those two folders and visually check  I must automate this someday  that app1 has 100  coverage and app2 has 0  coverage   When if I find that these numbers differ from standard I investigage and alter the design of the code so that coverage conforms to the standard   This does mean that I can recommend achieving 100  line coverage of library code   I also occasionally review app2  to see if I could possible test any code there  and If I can I move it into app1   Now I m not too worried about the aggregate coverage because that can vary wildly depending on the size of the project  but generally I ve seen 70  to over 90    With python  I should be able to devise a smoke test which could automatically run my app while measuring coverage and hopefully gain an aggreagate of 100  when combining the smoke test with unittest figures

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Short answer  60-80   Long answer  I think it totally depends on the nature of your project   I typically start a project by unit testing every practical piece   By the first  release  of the project you should have a pretty good base percentage based on the type of programming you are doing   At that point you can start  enforcing  a minimum code coverage

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Check out Crap4j  It s a slightly more sophisticated approach than straight code coverage  It combines code coverage measurements with complexity measurements  and then shows you what complex code isn t currently tested

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It depends greatly on your application  For example  some applications consist mostly of GUI code that cannot be unit tested

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When I think my code isn t unit tested enough  and I m not sure what to test next  I use coverage to help me decide what to test next   If I increase coverage in a unit test - I know this unit test worth something   This goes for code that is not covered  50  covered or 97  covered

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My favorite code coverage is 100  with an asterisk  The asterisk comes because I prefer to use tools that allow me to mark certain lines as lines that  don t count   If I have covered 100  of the lines which  count   I am done   The underlying process is    I write my tests to exercise all the functionality and edge cases I can think of  usually working from the documentation   I run the code coverage tools I examine any lines or paths not covered and any that I consider not important or unreachable  due to defensive programming  I mark as not counting I write new tests to cover the missing lines and improve the documentation if those edge cases are not mentioned    This way if I and my collaborators add new code or change the tests in the future  there is a bright line to tell us if we missed something important - the coverage dropped below 100   However  it also provides the flexibility to deal with different testing priorities

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For a well designed system  where unit tests have driven the development from the start i would say 85  is a quite low number  Small classes designed to be testable should not be hard to cover better than that   It s easy to dismiss this question with something like    Covered lines do not equal tested logic and one should not read too much into the percentage    True  but there are some important points to be made about code coverage  In my experience this metric is actually quite useful  when used correctly  Having said that  I have not seen all systems and i m sure there are tons of them where it s hard to see code coverage analysis adding any real value  Code can look so different and the scope of the available test framework can vary   Also  my reasoning mainly concerns quite short test feedback loops  For the product that I m developing the shortest feedback loop is quite flexible  covering everything from class tests to inter process signalling  Testing a deliverable sub-product typically takes 5 minutes and for such a short feedback loop it is indeed possible to use the test results  and specifically the code coverage metric that we are looking at here  to reject or accept commits in the repository   When using the code coverage metric you should not just have a fixed  arbitrary  percentage which must be fulfilled  Doing this does not give you the real benefits of code coverage analysis in my opinion  Instead  define the following metrics    Low Water Mark  LWM   the lowest number of uncovered lines ever seen in the system under test High Water Mark  HWM   the highest code coverage percentage ever seen for the system under test   New code can only be added if we don t go above the LWM and we don t go below the HWM  In other words  code coverage is not allowed to decrease  and new code should be covered  Notice how i say should and not must  explained below    But doesn t this mean that it will be impossible to clean away old well-tested rubbish that you have no use for anymore  Yes  and that s why you have to be pragmatic about these things  There are situations when the rules have to be broken  but for your typical day-to-day integration my experience it that these metrics are quite useful  They give the following two implications    Testable code is promoted  When adding new code you really have to make an effort to make the code testable  because you will have to try and cover all of it with your test cases  Testable code is usually a good thing  Test coverage for legacy code is increasing over time  When adding new code and not being able to cover it with a test case  one can try to cover some legacy code instead to get around the LWM rule  This sometimes necessary cheating at least gives the positive side effect that the coverage of legacy code will increase over time  making the seemingly strict enforcement of these rules quite pragmatic in practice    And again  if the feedback loop is too long it might be completely unpractical to setup something like this in the integration process   I would also like to mention two more general benefits of the code coverage metric    Code coverage analysis is part of the dynamic code analysis  as opposed to the static one  i e  Lint   Problems found during the dynamic code analysis  by tools such as the purify family  http   www-03 ibm com software products en rational-purify-family  are things like uninitialized memory reads  UMR   memory leaks  etc  These problems can only be found if the code is covered by an executed test case  The code that is the hardest to cover in a test case is usually the abnormal cases in the system  but if you want the system to fail gracefully  i e  error trace instead of crash  you might want to put some effort into covering the abnormal cases in the dynamic code analysis as well  With just a little bit of bad luck  a UMR can lead to a segfault or worse  People take pride in keeping 100  for new code  and people discuss testing problems with a similar passion as other implementation problems  How can this function be written in a more testable manner  How would you go about trying to cover this abnormal case  etc    And a negative  for completeness    In a large project with many involved developers  everyone is not going to be a test-genius for sure  Some people tend to use the code coverage metric as proof that the code is tested and this is very far from the truth  as mentioned in many of the other answers to this question  It is ONE metric that can give you some nice benefits if used properly  but if it is misused it can in fact lead to bad testing  Aside from the very valuable side effects mentioned above a covered line only shows that the system under test can reach that line for some input data and that it can execute without hanging or crashing

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I think the best symptom of correct code coverage is that amount of concrete problems unit tests help to fix is reasonably corresponds to size of unit tests code you created

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Code Coverage is a misleading metric if 100  coverage is your goal  instead of 100  testing of all features      You could get a 100  by hitting all the lines once  However you could still miss out testing a particular sequence  logical path  in which those lines are hit  You could not get a 100  but still have tested all your 80  freq used code-paths  Having tests that test every  throw ExceptionTypeX  or similar defensive programming guard you ve put in is a  nice to have  not a  must have     So trust yourself or your developers to be thorough and cover every path through their code  Be pragmatic and don t chase the magical 100  coverage  If you TDD your code you should get a 90   coverage as a bonus  Use code-coverage to highlight chunks of code you have missed  shouldn t happen if you TDD though   since you write code only to make a test pass  No code can exist without its partner test

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Many shops don t value tests  so if you are above zero at least there is some appreciation of worth - so arguably non-zero isn t bad as many are still zero   In the  Net world people often quote 80  as reasonble  But they say this at solution level  I prefer to measure at project level  30  might be fine for UI project if you ve got Selenium  etc or manual tests  20  for the data layer project might be fine  but 95   might be quite achievable for the business rules layer  if not wholly necessary  So the overall coverage may be  say  60   but the critical business logic may be much higher   I ve also heard this  aspire to 100  and you ll hit 80   but aspire to 80  and you ll hit 40    Bottom line  Apply the 80 20 rule  and let your app s bug count guide you

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Depending on the criticality of the code  anywhere from 75 -85  is a good rule of thumb  Shipping code should definitely be tested more thoroughly than in house utilities  etc

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This prose by Alberto Savoia answers precisely that question  in a nicely entertaining manner at that     http   www artima com forums flat jsp forum 106 amp thread 204677     Testivus On Test Coverage      Early one morning  a programmer asked   the great master          I am ready to write some unit tests  What code coverage should I aim   for          The great master replied          Don   t worry about coverage  just write some good tests          The programmer smiled  bowed  and   left                Later that day  a second programmer   asked the same question       The great master pointed at a pot of   boiling water and said          How many grains of rice should I put in that pot          The programmer  looking puzzled    replied          How can I possibly tell you  It depends on how many people you need to   feed  how hungry they are  what other   food you are serving  how much rice   you have available  and so on             Exactly     said the great master       The second programmer smiled  bowed    and left                Toward the end of the day  a third   programmer came and asked the same   question about code coverage          Eighty percent and no less     Replied the master in a stern voice    pounding his fist on the table       The third programmer smiled  bowed    and left                After this last reply  a young   apprentice approached the great   master          Great master  today I overheard you answer the same question about   code coverage with three different   answers  Why          The great master stood up from his   chair          Come get some fresh tea with me and let   s talk about it          After they filled their cups with   smoking hot green tea  the great   master began to answer          The first programmer is new and just getting started with testing    Right now he has a lot of code and no   tests  He has a long way to go    focusing on code coverage at this time   would be depressing and quite useless    He   s better off just getting used to   writing and running some tests  He can   worry about coverage later             The second programmer  on the other hand  is quite experience both   at programming and testing  When I   replied by asking her how many grains   of rice I should put in a pot  I   helped her realize that the amount of   testing necessary depends on a number   of factors  and she knows those   factors better than I do     it   s her   code after all  There is no single    simple  answer  and she   s smart enough   to handle the truth and work with   that             I see     said the young apprentice       but if there is no single simple   answer  then why did you answer the   third programmer    Eighty percent and   no less             The great master laughed so hard and   loud that his belly  evidence that he   drank more than just green tea    flopped up and down          The third programmer wants only simple answers     even when there are   no simple answers     and then does not   follow them anyway          The young apprentice and the grizzled   great master finished drinking their   tea in contemplative silence

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I think that what may matter most is knowing what the coverage trend is over time and understanding the reasons for changes in the trend   Whether you view the changes in the trend as good or bad will depend upon your analysis of the reason

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I think that what may matter most is knowing what the coverage trend is over time and understanding the reasons for changes in the trend   Whether you view the changes in the trend as good or bad will depend upon your analysis of the reason

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I use cobertura  and whatever the percentage  I would recommend keeping the values in the cobertura-check task up-to-date  At the minimum  keep raising totallinerate and totalbranchrate to just below your current coverage  but never lower those values  Also tie in the Ant build failure property to this task  If the build fails because of lack of coverage  you know someone s added code but hasn t tested it  Example    lt cobertura-check linerate  0                   branchrate  0                   totallinerate  70                   totalbranchrate  90                   failureproperty  build failed    gt

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I don t think there can be such a B W rule  Code should be reviewed  with particular attention to the critical details  However  if it hasn t been tested  it has a bug

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From the Testivus posting I think the answer context should be the second programmer  Having said this from a practical point of view we need parameter   goals to strive for  I consider that this can be  tested  in an Agile process by analyzing the code we have the architecture  functionality  user stories   and then come up with a number  Based on my experience in the Telecom area I would say that 60  is a good value to check

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I d have another anectode on test coverage I d like to share   We have a huge project wherein  over twitter  I noted that  with 700 unit tests  we only have 20  code coverage   Scott Hanselman replied with words of wisdom      Is it the RIGHT 20   Is it the 20    that represents the code your users   hit the most  You might add 50 more   tests and only add 2     Again  it goes back to my Testivus on Code Coverage Answer  How much rice should you put in the pot  It depends

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Generally speaking  from the several engineering excellence best practices papers that I have read  80  for new code in unit tests is the point that yields the best return   Going above that CC  yields a lower amount of defects for the amount of effort exerted    This is a best practice that is used by many major corporations   Unfortunately  most of these results are internal to companies  so there are no public literatures that I can point you to

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If you ve been doing unit testing for a decent amount of time  I see no reason for it not to be approaching 95    However  at a minimum  I ve always worked with 80   even when new to testing   This number should only include code written in the project  excludes frameworks  plugins  etc   and maybe even exclude certain classes composed entirely of code written of calls to outside code  This sort of call should be mocked stubbed

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My answer to this conundrum is to have 100  line coverage of the code you can test and 0  line coverage of the code you can t test   My current practice in Python is to divide my  py modules into two folders  app1  and app2  and when running unit tests calculate the coverage of those two folders and visually check  I must automate this someday  that app1 has 100  coverage and app2 has 0  coverage   When if I find that these numbers differ from standard I investigage and alter the design of the code so that coverage conforms to the standard   This does mean that I can recommend achieving 100  line coverage of library code   I also occasionally review app2  to see if I could possible test any code there  and If I can I move it into app1   Now I m not too worried about the aggregate coverage because that can vary wildly depending on the size of the project  but generally I ve seen 70  to over 90    With python  I should be able to devise a smoke test which could automatically run my app while measuring coverage and hopefully gain an aggreagate of 100  when combining the smoke test with unittest figures

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This prose by Alberto Savoia answers precisely that question  in a nicely entertaining manner at that     http   www artima com forums flat jsp forum 106 amp thread 204677     Testivus On Test Coverage      Early one morning  a programmer asked   the great master          I am ready to write some unit tests  What code coverage should I aim   for          The great master replied          Don   t worry about coverage  just write some good tests          The programmer smiled  bowed  and   left                Later that day  a second programmer   asked the same question       The great master pointed at a pot of   boiling water and said          How many grains of rice should I put in that pot          The programmer  looking puzzled    replied          How can I possibly tell you  It depends on how many people you need to   feed  how hungry they are  what other   food you are serving  how much rice   you have available  and so on             Exactly     said the great master       The second programmer smiled  bowed    and left                Toward the end of the day  a third   programmer came and asked the same   question about code coverage          Eighty percent and no less     Replied the master in a stern voice    pounding his fist on the table       The third programmer smiled  bowed    and left                After this last reply  a young   apprentice approached the great   master          Great master  today I overheard you answer the same question about   code coverage with three different   answers  Why          The great master stood up from his   chair          Come get some fresh tea with me and let   s talk about it          After they filled their cups with   smoking hot green tea  the great   master began to answer          The first programmer is new and just getting started with testing    Right now he has a lot of code and no   tests  He has a long way to go    focusing on code coverage at this time   would be depressing and quite useless    He   s better off just getting used to   writing and running some tests  He can   worry about coverage later             The second programmer  on the other hand  is quite experience both   at programming and testing  When I   replied by asking her how many grains   of rice I should put in a pot  I   helped her realize that the amount of   testing necessary depends on a number   of factors  and she knows those   factors better than I do     it   s her   code after all  There is no single    simple  answer  and she   s smart enough   to handle the truth and work with   that             I see     said the young apprentice       but if there is no single simple   answer  then why did you answer the   third programmer    Eighty percent and   no less             The great master laughed so hard and   loud that his belly  evidence that he   drank more than just green tea    flopped up and down          The third programmer wants only simple answers     even when there are   no simple answers     and then does not   follow them anyway          The young apprentice and the grizzled   great master finished drinking their   tea in contemplative silence

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I think the best symptom of correct code coverage is that amount of concrete problems unit tests help to fix is reasonably corresponds to size of unit tests code you created

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I don t think there can be such a B W rule  Code should be reviewed  with particular attention to the critical details  However  if it hasn t been tested  it has a bug

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I prefer to do BDD  which uses a combination of automated acceptance tests  possibly other integration tests  and unit tests  The question for me is what the target coverage of the automated test suite as a whole should be   That aside  the answer depends on your methodology  language and testing and coverage tools  When doing TDD in Ruby or Python it s not hard to maintain 100  coverage  and it s well worth doing so  It s much easier to manage 100  coverage than 90-something percent coverage  That is  it s much easier to fill coverage gaps as they appear  and when doing TDD well coverage gaps are rare and usually worth your time  than it is to manage a list of coverage gaps that you haven t gotten around to and miss coverage regressions due to your constant background of uncovered code   The answer also depends on the history of your project  I ve only found the above to be practical in projects managed that way from the start  I ve greatly improved the coverage of large legacy projects  and it s been worth doing so  but I ve never found it practical to go back and fill every coverage gap  because old untested code is not well understood enough to do so correctly and quickly

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In my opinion  the answer is  It depends on how much time you have    I try to achieve 100  but I don t make a fuss if I don t get it with the time I have     When I write unit tests  I wear a different hat compared to the hat I wear when developing production code   I think about what the tested code claims to do and what are the situations that can possible break it   I usually follow the following criteria or rules     That the Unit Test should be a form of documentation on what s the expected behavior of my codes  ie  the expected output given a certain input and the exceptions it may throw that clients may want to catch   What the users of my code should know   That the Unit Test should help me discover the what if conditions that I may not yet have thought of   How to make my code stable and robust     If these two rules doesn t produce 100  coverage then so be it   But once  I have the time  I analyze the uncovered blocks and lines and determine if there are still test cases without unit tests or if the code needs to be refactored to eliminate the unecessary codes

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Code coverage is great but only as long as the benefits that you get from it outweigh the cost effort of achieving it   We have been working to a standard of 80  for some time  however we have just made the decison to abandon this and instead be more focused on our testing  Concentrating on the complex business logic etc   This decision was taken due to the increasing amount of time we spent chasing code coverage and maintaining existing unit tests  We felt we had got to the point where the benefit we were getting from our code coverage was deemed to be less than the effort that we had to put in to achieve it

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We were targeting  80  till few days back  But after we used a lot of Generated code  We do not care for  age  but rather make reviewer take a call on the coverage required

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This prose by Alberto Savoia answers precisely that question  in a nicely entertaining manner at that     http   www artima com forums flat jsp forum 106 amp thread 204677     Testivus On Test Coverage      Early one morning  a programmer asked   the great master          I am ready to write some unit tests  What code coverage should I aim   for          The great master replied          Don   t worry about coverage  just write some good tests          The programmer smiled  bowed  and   left                Later that day  a second programmer   asked the same question       The great master pointed at a pot of   boiling water and said          How many grains of rice should I put in that pot          The programmer  looking puzzled    replied          How can I possibly tell you  It depends on how many people you need to   feed  how hungry they are  what other   food you are serving  how much rice   you have available  and so on             Exactly     said the great master       The second programmer smiled  bowed    and left                Toward the end of the day  a third   programmer came and asked the same   question about code coverage          Eighty percent and no less     Replied the master in a stern voice    pounding his fist on the table       The third programmer smiled  bowed    and left                After this last reply  a young   apprentice approached the great   master          Great master  today I overheard you answer the same question about   code coverage with three different   answers  Why          The great master stood up from his   chair          Come get some fresh tea with me and let   s talk about it          After they filled their cups with   smoking hot green tea  the great   master began to answer          The first programmer is new and just getting started with testing    Right now he has a lot of code and no   tests  He has a long way to go    focusing on code coverage at this time   would be depressing and quite useless    He   s better off just getting used to   writing and running some tests  He can   worry about coverage later             The second programmer  on the other hand  is quite experience both   at programming and testing  When I   replied by asking her how many grains   of rice I should put in a pot  I   helped her realize that the amount of   testing necessary depends on a number   of factors  and she knows those   factors better than I do     it   s her   code after all  There is no single    simple  answer  and she   s smart enough   to handle the truth and work with   that             I see     said the young apprentice       but if there is no single simple   answer  then why did you answer the   third programmer    Eighty percent and   no less             The great master laughed so hard and   loud that his belly  evidence that he   drank more than just green tea    flopped up and down          The third programmer wants only simple answers     even when there are   no simple answers     and then does not   follow them anyway          The young apprentice and the grizzled   great master finished drinking their   tea in contemplative silence

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Generally speaking  from the several engineering excellence best practices papers that I have read  80  for new code in unit tests is the point that yields the best return   Going above that CC  yields a lower amount of defects for the amount of effort exerted    This is a best practice that is used by many major corporations   Unfortunately  most of these results are internal to companies  so there are no public literatures that I can point you to

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Code coverage is just another metric  In and of itself  it can be very misleading  see www thoughtworks com insights blog are-test-coverage-metrics-overrated   Your goal should therefore not be to achieve 100  code coverage but rather to ensure that you test all relevant scenarios of your application

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Viewing coverage from another perspective  Well-written code with a clear flow of control is the easiest to cover  the easiest to read  and usually the least buggy code  By writing code with clearness and coverability in mind  and by writing the unit tests in parallel with the code  you get the best results IMHO

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The accepted answer makes a good point - there is not a single number that is going to make sense as a standard for every project  There are projects that just don t need such a standard  Where the accepted answer falls short  in my opinion  is in describing how one might make that decision for a given project   I will take a shot at doing so  I am not an expert in test engineering and would be happy to see a more informed answer   When to set code coverage requirements  First  why would you want to impose such a standard in the first place  In general  when you want to introduce empirical confidence in your process  What do I mean by  empirical confidence   Well  the real goal correctness  For most software  we can t possibly know this across all inputs  so we settle for saying that code is well-tested  This is more knowable  but is still a subjective standard  It will always be open to debate whether or not you have met it  Those debates are useful and should occur  but they also expose uncertainty   Code coverage is an objective measurement  Once you see your coverage report  there is no ambiguity about whether standards have been met are useful  Does it prove correctness  Not at all  but it has a clear relationship to how well-tested the code is  which in turn is our best way to increase confidence in its correctness  Code coverage is a measurable approximation of immeasurable qualities we care about   Some specific cases where having an empirical standard could add value    To satisfy stakeholders  For many projects  there are various actors who have an interest in software quality who may not be involved in the day-to-day development of the software  managers  technical leads  etc   Saying  we re going to write all the tests we really need  is not convincing  They either need to trust entirely  or verify with ongoing close oversight  assuming they even have the technical understanding to do so   Providing measurable standards and explaining how they reasonably approximate actual goals is better  To normalize team behavior  Stakeholders aside  if you are working on a team where multiple people are writing code and tests  there is room for ambiguity for what qualifies as  well-tested   Do all of your colleagues have the same idea of what level of testing is good enough  Probably not  How do you reconcile this  Find a metric you can all agree on and accept it as a reasonable approximation  This is especially  but not exclusively  useful in large teams  where leads may not have direct oversight over junior developers  for instance  Networks of trust matter as well  but without objective measurements  it is easy for group behavior to become inconsistent  even if everyone is acting in good faith  To keep yourself honest  Even if you re the only developer and only stakeholder for your project  you might have certain qualities in mind for the software  Instead of making ongoing subjective assessments about how well-tested the software is  which takes work   you can use code coverage as a reasonable approximation  and let machines measure it for you    Which metrics to use  Code coverage is not a single metric  there are several different ways of measuring coverage  Which one you might set a standard upon depends on what you re using that standard to satisfy   I ll use two common metrics as examples of when you might use them to set standards    Statement coverage  What percentage of statements have been executed during testing  Useful to get a sense of the physical coverage of your code  How much of the code that I have written have I actually tested    This kind of coverage supports a weaker correctness argument  but is also easier to achieve  If you re just using code coverage to ensure that things get tested  and not as an indicator of test quality beyond that  then statement coverage is probably sufficient   Branch coverage  When there is branching logic  e g  an if   have both branches been evaluated  This gives a better sense of the logical coverage of your code  How many of the possible paths my code may take have I tested    This kind of coverage is a much better indicator that a program has been tested across a comprehensive set of inputs  If you re using code coverage as your best empirical approximation for confidence in correctness  you should set standards based on branch coverage or similar     There are many other metrics  line coverage is similar to statement coverage  but yields different numeric results for multi-line statements  for instance  conditional coverage and path coverage is similar to branch coverage  but reflect a more detailed view of the possible permutations of program execution you might encounter    What percentage to require  Finally  back to the original question  If you set code coverage standards  what should that number be   Hopefully it s clear at this point that we re talking about an approximation to begin with  so any number we pick is going to be inherently approximate   Some numbers that one might choose    100   You might choose this because you want to be sure everything is tested  This doesn t give you any insight into test quality  but does tell you that some test of some quality has touched every statement  or branch  etc   Again  this comes back to degree of confidence  If your coverage is below 100   you know some subset of your code is untested     Some might argue that this is silly  and you should only test the parts of your code that are really important  I would argue that you should also only maintain the parts of your code that are really important  Code coverage can be improved by removing untested code  too   99   or 95   other numbers in the high nineties   Appropriate in cases where you want to convey a level of confidence similar to 100   but leave yourself some margin to not worry about the occasional hard-to-test corner of code  80   I ve seen this number in use a few times  and don t entirely know where it originates  I think it might be a weird misappropriation of the 80-20 rule  generally  the intent here is to show that most of your code is tested   Yes  51  would also be  most   but 80  is more reflective of what most people mean by most   This is appropriate for middle-ground cases where  well-tested  is not a high priority  you don t want to waste effort on low-value tests   but is enough of a priority that you d still like to have some standard in place    I haven t seen numbers below 80  in practice  and have a hard time imagining a case where one would set them  The role of these standards is to increase confidence in correctness  and numbers below 80  aren t particularly confidence-inspiring   Yes  this is subjective  but again  the idea is to make the subjective choice once when you set the standard  and then use an objective measurement going forward    Other notes  The above assumes that correctness is the goal  Code coverage is just information  it may be relevant to other goals  For instance  if you re concerned about maintainability  you probably care about loose coupling  which can be demonstrated by testability  which in turn can be measured  in certain fashions  by code coverage  So your code coverage standard provides an empirical basis for approximating the quality of  maintainability  as well

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If this were a perfect world  100  of code would be covered by unit tests  However  since this is NOT a perfect world  it s a matter of what you have time for  As a result  I recommend focusing less on a specific percentage  and focusing more on the critical areas   If your code is well-written  or at least a reasonable facsimile thereof  there should be several key points where APIs are exposed to other code    Focus your testing efforts on these APIs  Make sure that the APIs are 1  well documented and 2  have test cases written that match the documentation  If the expected results don t match up with the docs  then you have a bug in either your code  documentation  or test cases  All of which are good to vet out   Good luck

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We were targeting  80  till few days back  But after we used a lot of Generated code  We do not care for  age  but rather make reviewer take a call on the coverage required

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Depending on the criticality of the code  anywhere from 75 -85  is a good rule of thumb  Shipping code should definitely be tested more thoroughly than in house utilities  etc

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This has to be dependent on what phase of your application development lifecycle you are in     If you ve been at development for a while and have a lot of implemented code already and are just now realizing that you need to think about code coverage then you have to check your current coverage  if it exists  and then use that baseline to set milestones each sprint  or an average rise over a period of sprints   which means taking on code debt while continuing to deliver end user value  at least in my experience the end user doesn t care one bit if you ve increased test coverage if they don t see new features      Depending on your domain it s not unreasonable to shoot for 95   but I d have to say on average your going to be looking at an average case of 85  to 90

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It depends greatly on your application  For example  some applications consist mostly of GUI code that cannot be unit tested

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If you ve been doing unit testing for a decent amount of time  I see no reason for it not to be approaching 95    However  at a minimum  I ve always worked with 80   even when new to testing   This number should only include code written in the project  excludes frameworks  plugins  etc   and maybe even exclude certain classes composed entirely of code written of calls to outside code  This sort of call should be mocked stubbed

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Generally speaking  from the several engineering excellence best practices papers that I have read  80  for new code in unit tests is the point that yields the best return   Going above that CC  yields a lower amount of defects for the amount of effort exerted    This is a best practice that is used by many major corporations   Unfortunately  most of these results are internal to companies  so there are no public literatures that I can point you to

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Code Coverage is a misleading metric if 100  coverage is your goal  instead of 100  testing of all features      You could get a 100  by hitting all the lines once  However you could still miss out testing a particular sequence  logical path  in which those lines are hit  You could not get a 100  but still have tested all your 80  freq used code-paths  Having tests that test every  throw ExceptionTypeX  or similar defensive programming guard you ve put in is a  nice to have  not a  must have     So trust yourself or your developers to be thorough and cover every path through their code  Be pragmatic and don t chase the magical 100  coverage  If you TDD your code you should get a 90   coverage as a bonus  Use code-coverage to highlight chunks of code you have missed  shouldn t happen if you TDD though   since you write code only to make a test pass  No code can exist without its partner test

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I d have another anectode on test coverage I d like to share   We have a huge project wherein  over twitter  I noted that  with 700 unit tests  we only have 20  code coverage   Scott Hanselman replied with words of wisdom      Is it the RIGHT 20   Is it the 20    that represents the code your users   hit the most  You might add 50 more   tests and only add 2     Again  it goes back to my Testivus on Code Coverage Answer  How much rice should you put in the pot  It depends

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85  would be a good starting place for checkin criteria     I d probably chose a variety of higher bars for shipping criteria - depending on the criticality of the subsystems components being tested

[unit-testing] What is a reasonable code coverage % for unit tests (and why)?

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