software metric

Common software measurements include:

• ABC Software Metric
• Balanced scorecard
• Bugs per line of code
• Code coverage
• Cohesion
• Comment density{{cite web|title=Descriptive Information (DI) Metric Thresholds|url=http://www.lsec.dnd.ca/qsd_current_version/eng_support/di/metrics.htm|work=Land Software Engineering Centre|access-date=19 October 2010|url-status=dead|archive-url=https://archive.today/20110706175332/http://www.lsec.dnd.ca/qsd_current_version/eng_support/di/metrics.htm|archive-date=6 July 2011}}
• Connascent software components
• Constructive Cost Model
• Coupling
• Cyclomatic complexity (McCabe's complexity)
• Cyclomatic complexity density{{Cite journal|last1=Gill|first1=G. K.|last2=Kemerer|first2=C. F.|date=December 1991|title=Cyclomatic complexity density and software maintenance productivity|url=https://ieeexplore.ieee.org/document/106988|journal=IEEE Transactions on Software Engineering|volume=17|issue=12|pages=1284–1288|doi=10.1109/32.106988|issn=1939-3520|url-access=subscription}}{{Cite web|title=maintainability - Does it make sense to compute cyclomatic complexity/lines of code ratio?|url=https://softwareengineering.stackexchange.com/questions/56056/does-it-make-sense-to-compute-cyclomatic-complexity-lines-of-code-ratio|access-date=2021-03-01|website=Software Engineering Stack Exchange}}
• Defect density - defects found in a component
• Defect potential - expected number of defects in a particular component
• Defect removal rate
• DSQI (design structure quality index)
• Function Points and Automated Function Points, an Object Management Group standard{{cite web|url=http://www.omg.org/news/releases/pr2013/01-17-13.htm |title=OMG Adopts Automated Function Point Specification |publisher=Omg.org |date=2013-01-17 |access-date=2013-05-19}}
• Halstead Complexity
• Instruction path length
• Maintainability index
• Source lines of code - number of lines of code
• Program execution time
• Program load time
• Program size (binary)
• Weighted Micro Function Points
• Cycle time (software)
• First pass yield
• Corrective Commit Probability{{cite arXiv|last1=Amit|first1=Idan|last2=Feitelson|first2=Dror G.|date=2020-07-21|title=The Corrective Commit Probability Code Quality Metric|class=cs.SE|eprint=2007.10912}}

As software development is a complex process, with high variance on both methodologies and objectives, it is difficult to define or measure software qualities and quantities and to determine a valid and concurrent measurement metric, especially when making such a prediction prior to the detail design. Another source of difficulty and debate is in determining which metrics matter, and what they mean.{{cite web|last=Kolawa|first=Adam|title=When, Why, and How: Code Analysis|url=https://www.codeproject.com/Articles/28440/When-Why-and-How-Code-Analysis|work=The Code Project|date=7 August 2008|access-date=14 February 2021}}

The practical utility of software measurements has therefore been limited to the following domains:

• Scheduling
• Software sizing
• Programming complexity
• Software development effort estimation
• Software quality

A specific measurement may target one or more of the above aspects, or the balance between them, for example as an indicator of team motivation or project performance.

{{cite news |last1=Mike |first1=John |title=Essential Metrics for Effective Incident Response Strategies |url=https://cybercentaurs.com/blog/essential-metrics-for-effective-incident-response-strategies/ |access-date=18 July 2021}}

Additionally metrics vary between static and dynamic program code, as well as for object oriented software (systems).{{Cite book|last1=Gosain|first1=Anjana|last2=Sharma|first2=Ganga|title=Information Systems Design and Intelligent Applications |chapter=Dynamic Software Metrics for Object Oriented Software: A Review |date=2015|editor-last=Mandal|editor-first=J. K.|editor2-last=Satapathy|editor2-first=Suresh Chandra|editor3-last=Kumar Sanyal|editor3-first=Manas|editor4-last=Sarkar|editor4-first=Partha Pratim|editor5-last=Mukhopadhyay|editor5-first=Anirban|chapter-url=https://link.springer.com/chapter/10.1007/978-81-322-2247-7_59|series=Advances in Intelligent Systems and Computing|volume=340|language=en|location=New Delhi|publisher=Springer India|pages=579–589|doi=10.1007/978-81-322-2247-7_59|isbn=978-81-322-2247-7}}{{Cite book|last1=S|first1=Parvinder Singh|title=Dynamic Metrics for Polymorphism in Object Oriented Systems|last2=Singh|first2=Gurdev|citeseerx=10.1.1.193.4307}}

Some software development practitioners point out that simplistic measurements can cause more harm than good.{{citation |last=Kaner|first=Dr. Cem|title=Software Engineer Metrics: What do they measure and how do we know?|year=2004|citeseerx=10.1.1.1.2542}} Others have noted that metrics have become an integral part of the software development process.{{cite web|last=Binstock|first=Andrew|title=Integration Watch: Using metrics effectively|url=http://www.sdtimes.com/link/34157|work=SD Times|date=March 2010|publisher=BZ Media |access-date=19 October 2010}}

Impact of measurement on programmer psychology have raised concerns for harmful effects to performance due to stress, performance anxiety, and attempts to cheat the metrics, while others find it to have positive impact on developers value towards their own work, and prevent them being undervalued. Some argue that the definition of many measurement methodologies are imprecise, and consequently it is often unclear how tools for computing them arrive at a particular result,{{citation|first1=Rüdiger|last1=Lincke|first2=Jonas|last2=Lundberg|first3=Welf|last3=Löwe|title=Comparing software metrics tools|year=2008|work=International Symposium on Software Testing and Analysis 2008|pages=131–142|url=http://www.arisa.se/files/LLL-08.pdf}} while others argue that imperfect quantification is better than none (“You can’t control what you can't measure.”).{{cite book | last = DeMarco | first = Tom | author-link = Tom DeMarco | title = Controlling Software Projects: Management, Measurement and Estimation | year = 1982 | publisher = Yourdon Press | isbn = 0-13-171711-1}} Evidence shows that software metrics are being widely used by government agencies, the US military, NASA,{{cite web |url=http://earthdata.nasa.gov/our-community/esdswg/metrics-planning-and-reporting-mparwg |title=NASA Metrics Planning and Reporting Working Group (MPARWG) |publisher=Earthdata.nasa.gov |access-date=2013-05-19 |url-status=dead |archive-url=https://web.archive.org/web/20111022023020/https://earthdata.nasa.gov/our-community/esdswg/metrics-planning-and-reporting-mparwg |archive-date=2011-10-22 }} IT consultants, academic institutions,{{cite web|url=http://sunset.usc.edu/csse/research/COCOMOII/cocomo_main.html |title=USC Center for Systems and Software Engineering |publisher=Sunset.usc.edu |access-date=2013-05-19}} and commercial and academic development estimation software.

• J. Smith, Introduction to Linear Programming, Acme Press, 2010. An introductory text.

• Reijo M.Savola, Quality of security metrics and measurements, Computers & Security, Volume 37, September 2013, Pages 78-90.{{Cite journal|last=Savola|first=Reijo M.|date=2013-09-01|title=Quality of security metrics and measurements|url=https://www.sciencedirect.com/science/article/pii/S0167404813000850|journal=Computers & Security|language=en|volume=37|pages=78–90|doi=10.1016/j.cose.2013.05.002|issn=0167-4048|url-access=subscription}}

• Goal Question-Metric
• List of tools for static code analysis
• Orthogonal Defect Classification
• Software engineering
• Software package metrics

{{reflist}}

• [http://www.sqa.net/softwarequalitymetrics.html Software Metrics] (SQA.net)
• [http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.1.2542 Software Engineering Metrics: What do they measure and how do we know]
• [https://web.archive.org/web/20201016160155/https://standards.nasa.gov/standard/osma/nasa-std-87398 NASA Standard NASA-STD-8739.8 (Software Assurance and Software Safety Standard)]
• [https://emenda.com/his/ HIS Source Code Metrics] (outdated but for reference; related see AUTOSAR)
• [https://www.exida.com/Blog/software-metrics-iso-26262-iec-61508 HIS Source Code Metrics version 1.3.1 01.04.2008] (outdated but for reference; related see AUTOSAR)
• [https://dl.acm.org/doi/10.1145/1839379.1839400 A framework for source code metrics]
• [https://swehb.nasa.gov/display/SWEHBVB/Metrics+-+Software+Metrics+Report NASA.gov]
• [https://docs.sonarqube.org/latest/user-guide/metric-definitions/ SonarQube Metric Definitions]
• [https://www.researchgate.net/publication/235759663_Metrics_of_Object_Oriented_Software/stats Metrics of Object Oriented Software] (2010)

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Category:Metrics