Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Investigating the applicability of Software Metrics and Technical Debt on X++ Abstract Syntax Tree in XML format: calculations using XQuery expressions
Linköping University, Department of Computer and Information Science.
2019 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

This thesis investigates how XML representation of X++ abstract syntax trees (AST) residing in an XML database can be subject to static code analysis. Microsoft Dynamics 365 for Finance & Operations comprises a large and complex corpus of X++ source code and intuitive ways of visualizing and analysing the state of the code base in terms of software metrics and technical debt are non-existent. A solution is to extend an internal web application and semantic search tool called SocrateX, to calculate software metrics and technical debt. This is done by creating a web service to construct XQuery and XPath code to be queried to the XML database. The values are stored in a relational database and imported to Power BI for intuitive visualization. Software metrics have been chosen based on the amount of previous research and compatibility with the X++ AST, whereas technical debt has been estimated using the SQALE method. This thesis concludes that XML representations of X++ abstract syntax trees are viable candidates for measuring quality of source codes with the use of functional query programming languages.

Place, publisher, year, edition, pages
2019. , p. 73
Keywords [en]
X++, Abstract syntax tree, software metrics, technical debt, SQALE method, software quality, xquery, xml, xpath
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:liu:diva-162719ISRN: LIU-IDA/LITH-EX-A--19/101—SEOAI: oai:DiVA.org:liu-162719DiVA, id: diva2:1379588
External cooperation
Microsoft
Subject / course
Computer Engineering
Presentation
2019-12-11, Donald Knuth, Linköping, 13:15 (English)
Supervisors
Examiners
Available from: 2019-12-17 Created: 2019-12-17 Last updated: 2019-12-17Bibliographically approved

Open Access in DiVA

fulltext(3081 kB)17 downloads
File information
File name FULLTEXT01.pdfFile size 3081 kBChecksum SHA-512
b6b83a1f89ba1220ee3dda257cba91c2c42eebd2f985dc74999eda768f7bfa45402c22dd0d8d6caa08794e56f221275f1857aacd3bec5b9e4e9d62011d683594
Type fulltextMimetype application/pdf

By organisation
Department of Computer and Information Science
Computer and Information Sciences

Search outside of DiVA

GoogleGoogle Scholar
Total: 17 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

urn-nbn

Altmetric score

urn-nbn
Total: 64 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf