Analysis of Test Coverage Data on a Large-Scale Industrial System

Software testing verifies the program's functional behavior, one important process when engineering critical software. Measuring the degree of testing is done with code coverage, describing the amount of production code affected by tests. Both concepts are extensively used for industrial system...

Full description

Bibliographic Details
Main Author: Vasconcelos Jansson, Erik Sven
Format: Others
Language:English
Published: Linköpings universitet, Programvara och system 2016
Subjects:
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-131815
id ndltd-UPSALLA1-oai-DiVA.org-liu-131815
record_format oai_dc
spelling ndltd-UPSALLA1-oai-DiVA.org-liu-1318152018-01-15T07:13:08ZAnalysis of Test Coverage Data on a Large-Scale Industrial SystemengVasconcelos Jansson, Erik SvenLinköpings universitet, Programvara och system2016code coveragesoftware testingindustrialanalysislarge-scalesimilarityjaccardimplementationfeasibilityperformanceSoftware EngineeringProgramvaruteknikComputer SciencesDatavetenskap (datalogi)Software testing verifies the program's functional behavior, one important process when engineering critical software. Measuring the degree of testing is done with code coverage, describing the amount of production code affected by tests. Both concepts are extensively used for industrial systems. Previous research has shown that gathering and analyzing test coverages becomes problematic on large-scale systems. Here, development experience, implementation feasibility, coverage measurements and analysis method are explored; providing potential solutions and insights into these issues. Outlined are methods for constructing and integrating such gathering and analysis system in a large-scale project, along with the problems encountered and given remedies. Instrumentations for gathering coverage information affect performance negatively, these measurements are provided. Since large-scale test suite measurements are quite lacking, the line, branch, and function criteria are presented here. Finally, an analysis method is proposed, by using coverage set operations and Jaccard indices, to find test similarities. Results gathered imply execution time was significantly affected when gathering coverage, [2.656, 2.911] hours for instrumented software, originally between [2.075, 2.260] on the system under test, given under the alpha = 5% and n = 4, while both processor & memory usages were inconclusive. Measured criteria were (59.3, 70.7, 24.6)% for these suites. Analysis method shows potential areas of test redundancy. Student thesisinfo:eu-repo/semantics/bachelorThesistexthttp://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-131815application/pdfinfo:eu-repo/semantics/openAccess
collection NDLTD
language English
format Others
sources NDLTD
topic code coverage
software testing
industrial
analysis
large-scale
similarity
jaccard
implementation
feasibility
performance
Software Engineering
Programvaruteknik
Computer Sciences
Datavetenskap (datalogi)
spellingShingle code coverage
software testing
industrial
analysis
large-scale
similarity
jaccard
implementation
feasibility
performance
Software Engineering
Programvaruteknik
Computer Sciences
Datavetenskap (datalogi)
Vasconcelos Jansson, Erik Sven
Analysis of Test Coverage Data on a Large-Scale Industrial System
description Software testing verifies the program's functional behavior, one important process when engineering critical software. Measuring the degree of testing is done with code coverage, describing the amount of production code affected by tests. Both concepts are extensively used for industrial systems. Previous research has shown that gathering and analyzing test coverages becomes problematic on large-scale systems. Here, development experience, implementation feasibility, coverage measurements and analysis method are explored; providing potential solutions and insights into these issues. Outlined are methods for constructing and integrating such gathering and analysis system in a large-scale project, along with the problems encountered and given remedies. Instrumentations for gathering coverage information affect performance negatively, these measurements are provided. Since large-scale test suite measurements are quite lacking, the line, branch, and function criteria are presented here. Finally, an analysis method is proposed, by using coverage set operations and Jaccard indices, to find test similarities. Results gathered imply execution time was significantly affected when gathering coverage, [2.656, 2.911] hours for instrumented software, originally between [2.075, 2.260] on the system under test, given under the alpha = 5% and n = 4, while both processor & memory usages were inconclusive. Measured criteria were (59.3, 70.7, 24.6)% for these suites. Analysis method shows potential areas of test redundancy.
author Vasconcelos Jansson, Erik Sven
author_facet Vasconcelos Jansson, Erik Sven
author_sort Vasconcelos Jansson, Erik Sven
title Analysis of Test Coverage Data on a Large-Scale Industrial System
title_short Analysis of Test Coverage Data on a Large-Scale Industrial System
title_full Analysis of Test Coverage Data on a Large-Scale Industrial System
title_fullStr Analysis of Test Coverage Data on a Large-Scale Industrial System
title_full_unstemmed Analysis of Test Coverage Data on a Large-Scale Industrial System
title_sort analysis of test coverage data on a large-scale industrial system
publisher Linköpings universitet, Programvara och system
publishDate 2016
url http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-131815
work_keys_str_mv AT vasconcelosjanssoneriksven analysisoftestcoveragedataonalargescaleindustrialsystem
_version_ 1718610603560402944