Metrics for implementing automated software testing. For over a decade, the prevailing wisdom has been that analytical errors rarely happen and that preanalytical and postanalytical errors are more important. Defects bugs related definitions in software development testing. Tukeys test is essentially a students ttest, except that it corrects for familywise errorrate. If the bug discovery rate keeps going like this, youre projected to. Senior management expected bug discovery rate to match their. Understanding type i and type ii errors hypothesis testing is the art of testing if variation between two sample distributions can just be explained through random chance or not. Some useful statistics definitions computer science. Test procedure execution metric will indicate the extent of the testing effort still outstanding.
Its important to decide what questions you want answers to. In software testing, metric is a quantitative measure of the degree to which a. Failures defect discovery rate defect removal rate and cost. The test statistic is based on inverse regression and biascorrected group lasso estimates of the regression coefficients and is shown to have an asymptotic chisquared null. A 2011 study of 5 years of laboratory data calls this emphasis into question. Sensitivity and type ii error, specificity and type i error, positive predictive value and false discovery rate, negative predictive value and false omission rate. The error discovery rate is used to analyze and support a rational product. False discovery rate an overview sciencedirect topics. Six sigma isixsigma forums old forums software it is defect discovery rate data in software continuous. Is defect discovery rate data in software continuous. The aim of this thesis is to investigate the metric support for software test planning and.
If software was being changed while testing new bugs could easily be. Following the v model of software development for every. Software test metrics is to monitor and control process and product. It helps to drive the project towards our planned goals without deviation. Software test metrics are classified into two types. False discovery rate columbia university mailman school. An error of omission results in a defect of missing code. The false discovery rate fdr is one way of conceptualizing the rate of type i errors in null hypothesis testing when conducting multiple comparisons. Would also question why the goal is 1 bug per test. The fdr method that was originally proposed was for use in multiple hypothesis testing of independent test statistics. This paper considers joint testing for regression coefficients over multiple responses and develops simultaneous testing methods with false discovery rate control. Discovery sampling involves the use of a sample to determine whether a percentage error does not exceed a designated percentage of the population. Fdrcontrolling procedures are designed to control the expected proportion of discoveries rejected null hypotheses that are false incorrect rejections. It is a measure of the bugfinding ability and quality of a test set.
The client reports one incident where installing the software wipes their hard drive. Implementing automated software testing continuously track progress and. Type i and type ii errors department of statistics. Metrics in software testing test management tutorials. Recovery testing is a system test that forces the software to fail and verifies that data recovery is properly performed. It is to determine the effectiveness of the test cases. If you use a waterfall methodology where formal testing occurs after development, it can be discrete. Yoav benjamini and daniel yekutieli 2001 the control of the false discovery rate in multiple testing under dependency the annals of statistics 2001, vol. Istqb question pattern and tips to solve software testing. Joint testing and false discovery rate control in high. The false discovery rate fdr is a method of conceptualizing the rate of type i errors in null hypothesis testing when conducting multiple comparisons.