CODE CLONING: This indicator evaluates and tracks cloning by detecting duplicated code at source code level, and takes duplication in the control flow on an algorithmic level.
COVERAGE COMPLIANCE: Coverage conformity measures test coverage compliance with usual industrial thresholds, or with your own project thresholds. Coupled with complexity, stability and criticity factors, this indicator is used to produce optimized test plans.
COMPLEXITY: Calculation method depends on the object analyzed. Regarding source code, components intrinsic complexity and distribution are taken into account. Whereas for requirements, complexity is computed from data produced by semantical analysis and rigorous writing rule-checking tools.
RULE COMPLIANCE: Compliance indicator with a set of rules or practices rates the adequacy with standards, be they international (ISO), industrial (HIS, SPICE …) or specific to each company.
VIOLATIONS DENSITY: Violations density allows to highlight components with the highest non-compliance rate in respect of a standard, by basic unit (number of lines of code for source code, number of sentences for requirements).
COMPLETION RATE: Completion rate indicates the achievement of a compliance status. The notation of compliance is adapted according the type of object: for example, a requirement is considered as compliant when it reaches a state where all its components are sucessfully achieved.
TEST EFFECTIVENESS: This KPI is based on the ratio of Passed Tests. It is available for test artifacts and for associated source code artifacts in case the traceability between Test and Source Code is available.
MATURITY INDEX: Maturity index indicates project progress. It provides a quick insight on the current state of the project, and its temporal follow-up brings precious information, including early warnings generation.
SELF-DESCRIPTIVENESS: Self-descriptiveness indicator measures the ease of understanding of a component. It is based on the detection and measure of associated comments.
INNOVATION RATE: This indicator is specific to change requests, and measures the rate of evolution requests versus bug reports. In order to be representative and exploitable, its calculation integrates a temporal dimension.