Mutation operators for testing Android apps
Context: Due to the widespread use of Android devices, Android applications (apps) have more releases, purchases, and downloads than apps for any other mobile devices. The sheer volume of code in these apps creates significant concerns about the quality of the software. However, testing Android apps...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Deng, Lin [verfasserIn] |
|---|
| Format: |
Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2017 |
|---|
| Schlagwörter: |
|---|
| Übergeordnetes Werk: |
Enthalten in: Information and software technology - London : Butterworth, 1987, 81(2017), Seite 154-168 |
|---|---|
| Übergeordnetes Werk: |
volume:81 ; year:2017 ; pages:154-168 |
| Links: |
|---|
| DOI / URN: |
10.1016/j.infsof.2016.04.012 |
|---|
| Katalog-ID: |
OLC1987691253 |
|---|
| LEADER | 01000caa a2200265 4500 | ||
|---|---|---|---|
| 001 | OLC1987691253 | ||
| 003 | DE-627 | ||
| 005 | 20220216165217.0 | ||
| 007 | tu | ||
| 008 | 170207s2017 xx ||||| 00| ||eng c | ||
| 024 | 7 | |a 10.1016/j.infsof.2016.04.012 |2 doi | |
| 028 | 5 | 2 | |a PQ20170501 |
| 035 | |a (DE-627)OLC1987691253 | ||
| 035 | |a (DE-599)GBVOLC1987691253 | ||
| 035 | |a (PRQ)c1621-8d56282ee40a288feecc59beb27fffdcdb5deb8fcfe9888d231c03979526b3a60 | ||
| 035 | |a (KEY)0050086020170000081000000154mutationoperatorsfortestingandroidapps | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 082 | 0 | 4 | |a 330 |a 004 |q DNB |
| 084 | |a 54.50 |2 bkl | ||
| 100 | 1 | |a Deng, Lin |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Mutation operators for testing Android apps |
| 264 | 1 | |c 2017 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a ohne Hilfsmittel zu benutzen |b n |2 rdamedia | ||
| 338 | |a Band |b nc |2 rdacarrier | ||
| 520 | |a Context: Due to the widespread use of Android devices, Android applications (apps) have more releases, purchases, and downloads than apps for any other mobile devices. The sheer volume of code in these apps creates significant concerns about the quality of the software. However, testing Android apps is different from testing traditional Java programs due to the unique program structure and new features of apps. Simple testing coverage criteria such as statement coverage are insufficient to assure high quality of Android apps. While researchers show significant interest in finding better Android testing approaches, there is still a lack of effective and usable techniques to evaluate their proposed test selection strategies, and to ensure a reasonable number of effective tests. Objective: As mutation analysis has been found to be an effective way to design tests in other software domains, we hypothesize that it is also a viable solution for Android apps. Method: This paper proposes an innovative mutation analysis approach that is specific for Android apps. We define mutation operators specific to the characteristics of Android apps, such as the extensive use of XML files to specify layout and behavior, the inherent event-driven nature, and the unique Activity lifecycle structure. We also report on an empirical study to evaluate these mutation operators. Results: We have built a tool that uses the novel Android mutation operators to mutate the source code of Android apps, then generates mutants that can be installed and run on Android devices. We evaluated the effectiveness of Android mutation testing through an empirical study on real-world apps. This paper introduces several novel mutation operators based on a fault study of Android apps, presents a significant empirical study with real-world apps, and provides conclusions based on an analysis of the results. Conclusion: The results show that the novel Android mutation operators provide comprehensive testing for Android apps. Additionally, as applying mutation testing to Android apps is still at a preliminary stage, we identify challenges, possibilities, and future research directions to make mutation analysis for mobile apps more effective and efficient. | ||
| 650 | 4 | |a Studies | |
| 650 | 4 | |a Testing | |
| 650 | 4 | |a Java | |
| 650 | 4 | |a Software utilities | |
| 700 | 1 | |a Offutt, Jeff |4 oth | |
| 700 | 1 | |a Ammann, Paul |4 oth | |
| 700 | 1 | |a Mirzaei, Nariman |4 oth | |
| 773 | 0 | 8 | |i Enthalten in |t Information and software technology |d London : Butterworth, 1987 |g 81(2017), Seite 154-168 |w (DE-627)130403393 |w (DE-600)607616-6 |w (DE-576)015907074 |x 0950-5849 |7 nnns |
| 773 | 1 | 8 | |g volume:81 |g year:2017 |g pages:154-168 |
| 856 | 4 | 1 | |u http://dx.doi.org/10.1016/j.infsof.2016.04.012 |3 Volltext |
| 856 | 4 | 2 | |u http://search.proquest.com/docview/1837894308 |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a SYSFLAG_A | ||
| 912 | |a GBV_OLC | ||
| 912 | |a SSG-OLC-MAT | ||
| 912 | |a GBV_ILN_70 | ||
| 936 | b | k | |a 54.50 |q AVZ |
| 951 | |a AR | ||
| 952 | |d 81 |j 2017 |h 154-168 | ||
| author_variant |
l d ld |
|---|---|
| matchkey_str |
article:09505849:2017----::uainprtrfretn |
| hierarchy_sort_str |
2017 |
| bklnumber |
54.50 |
| publishDate |
2017 |
| allfields |
10.1016/j.infsof.2016.04.012 doi PQ20170501 (DE-627)OLC1987691253 (DE-599)GBVOLC1987691253 (PRQ)c1621-8d56282ee40a288feecc59beb27fffdcdb5deb8fcfe9888d231c03979526b3a60 (KEY)0050086020170000081000000154mutationoperatorsfortestingandroidapps DE-627 ger DE-627 rakwb eng 330 004 DNB 54.50 bkl Deng, Lin verfasserin aut Mutation operators for testing Android apps 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Context: Due to the widespread use of Android devices, Android applications (apps) have more releases, purchases, and downloads than apps for any other mobile devices. The sheer volume of code in these apps creates significant concerns about the quality of the software. However, testing Android apps is different from testing traditional Java programs due to the unique program structure and new features of apps. Simple testing coverage criteria such as statement coverage are insufficient to assure high quality of Android apps. While researchers show significant interest in finding better Android testing approaches, there is still a lack of effective and usable techniques to evaluate their proposed test selection strategies, and to ensure a reasonable number of effective tests. Objective: As mutation analysis has been found to be an effective way to design tests in other software domains, we hypothesize that it is also a viable solution for Android apps. Method: This paper proposes an innovative mutation analysis approach that is specific for Android apps. We define mutation operators specific to the characteristics of Android apps, such as the extensive use of XML files to specify layout and behavior, the inherent event-driven nature, and the unique Activity lifecycle structure. We also report on an empirical study to evaluate these mutation operators. Results: We have built a tool that uses the novel Android mutation operators to mutate the source code of Android apps, then generates mutants that can be installed and run on Android devices. We evaluated the effectiveness of Android mutation testing through an empirical study on real-world apps. This paper introduces several novel mutation operators based on a fault study of Android apps, presents a significant empirical study with real-world apps, and provides conclusions based on an analysis of the results. Conclusion: The results show that the novel Android mutation operators provide comprehensive testing for Android apps. Additionally, as applying mutation testing to Android apps is still at a preliminary stage, we identify challenges, possibilities, and future research directions to make mutation analysis for mobile apps more effective and efficient. Studies Testing Java Software utilities Offutt, Jeff oth Ammann, Paul oth Mirzaei, Nariman oth Enthalten in Information and software technology London : Butterworth, 1987 81(2017), Seite 154-168 (DE-627)130403393 (DE-600)607616-6 (DE-576)015907074 0950-5849 nnns volume:81 year:2017 pages:154-168 http://dx.doi.org/10.1016/j.infsof.2016.04.012 Volltext http://search.proquest.com/docview/1837894308 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT GBV_ILN_70 54.50 AVZ AR 81 2017 154-168 |
| spelling |
10.1016/j.infsof.2016.04.012 doi PQ20170501 (DE-627)OLC1987691253 (DE-599)GBVOLC1987691253 (PRQ)c1621-8d56282ee40a288feecc59beb27fffdcdb5deb8fcfe9888d231c03979526b3a60 (KEY)0050086020170000081000000154mutationoperatorsfortestingandroidapps DE-627 ger DE-627 rakwb eng 330 004 DNB 54.50 bkl Deng, Lin verfasserin aut Mutation operators for testing Android apps 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Context: Due to the widespread use of Android devices, Android applications (apps) have more releases, purchases, and downloads than apps for any other mobile devices. The sheer volume of code in these apps creates significant concerns about the quality of the software. However, testing Android apps is different from testing traditional Java programs due to the unique program structure and new features of apps. Simple testing coverage criteria such as statement coverage are insufficient to assure high quality of Android apps. While researchers show significant interest in finding better Android testing approaches, there is still a lack of effective and usable techniques to evaluate their proposed test selection strategies, and to ensure a reasonable number of effective tests. Objective: As mutation analysis has been found to be an effective way to design tests in other software domains, we hypothesize that it is also a viable solution for Android apps. Method: This paper proposes an innovative mutation analysis approach that is specific for Android apps. We define mutation operators specific to the characteristics of Android apps, such as the extensive use of XML files to specify layout and behavior, the inherent event-driven nature, and the unique Activity lifecycle structure. We also report on an empirical study to evaluate these mutation operators. Results: We have built a tool that uses the novel Android mutation operators to mutate the source code of Android apps, then generates mutants that can be installed and run on Android devices. We evaluated the effectiveness of Android mutation testing through an empirical study on real-world apps. This paper introduces several novel mutation operators based on a fault study of Android apps, presents a significant empirical study with real-world apps, and provides conclusions based on an analysis of the results. Conclusion: The results show that the novel Android mutation operators provide comprehensive testing for Android apps. Additionally, as applying mutation testing to Android apps is still at a preliminary stage, we identify challenges, possibilities, and future research directions to make mutation analysis for mobile apps more effective and efficient. Studies Testing Java Software utilities Offutt, Jeff oth Ammann, Paul oth Mirzaei, Nariman oth Enthalten in Information and software technology London : Butterworth, 1987 81(2017), Seite 154-168 (DE-627)130403393 (DE-600)607616-6 (DE-576)015907074 0950-5849 nnns volume:81 year:2017 pages:154-168 http://dx.doi.org/10.1016/j.infsof.2016.04.012 Volltext http://search.proquest.com/docview/1837894308 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT GBV_ILN_70 54.50 AVZ AR 81 2017 154-168 |
| allfields_unstemmed |
10.1016/j.infsof.2016.04.012 doi PQ20170501 (DE-627)OLC1987691253 (DE-599)GBVOLC1987691253 (PRQ)c1621-8d56282ee40a288feecc59beb27fffdcdb5deb8fcfe9888d231c03979526b3a60 (KEY)0050086020170000081000000154mutationoperatorsfortestingandroidapps DE-627 ger DE-627 rakwb eng 330 004 DNB 54.50 bkl Deng, Lin verfasserin aut Mutation operators for testing Android apps 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Context: Due to the widespread use of Android devices, Android applications (apps) have more releases, purchases, and downloads than apps for any other mobile devices. The sheer volume of code in these apps creates significant concerns about the quality of the software. However, testing Android apps is different from testing traditional Java programs due to the unique program structure and new features of apps. Simple testing coverage criteria such as statement coverage are insufficient to assure high quality of Android apps. While researchers show significant interest in finding better Android testing approaches, there is still a lack of effective and usable techniques to evaluate their proposed test selection strategies, and to ensure a reasonable number of effective tests. Objective: As mutation analysis has been found to be an effective way to design tests in other software domains, we hypothesize that it is also a viable solution for Android apps. Method: This paper proposes an innovative mutation analysis approach that is specific for Android apps. We define mutation operators specific to the characteristics of Android apps, such as the extensive use of XML files to specify layout and behavior, the inherent event-driven nature, and the unique Activity lifecycle structure. We also report on an empirical study to evaluate these mutation operators. Results: We have built a tool that uses the novel Android mutation operators to mutate the source code of Android apps, then generates mutants that can be installed and run on Android devices. We evaluated the effectiveness of Android mutation testing through an empirical study on real-world apps. This paper introduces several novel mutation operators based on a fault study of Android apps, presents a significant empirical study with real-world apps, and provides conclusions based on an analysis of the results. Conclusion: The results show that the novel Android mutation operators provide comprehensive testing for Android apps. Additionally, as applying mutation testing to Android apps is still at a preliminary stage, we identify challenges, possibilities, and future research directions to make mutation analysis for mobile apps more effective and efficient. Studies Testing Java Software utilities Offutt, Jeff oth Ammann, Paul oth Mirzaei, Nariman oth Enthalten in Information and software technology London : Butterworth, 1987 81(2017), Seite 154-168 (DE-627)130403393 (DE-600)607616-6 (DE-576)015907074 0950-5849 nnns volume:81 year:2017 pages:154-168 http://dx.doi.org/10.1016/j.infsof.2016.04.012 Volltext http://search.proquest.com/docview/1837894308 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT GBV_ILN_70 54.50 AVZ AR 81 2017 154-168 |
| allfieldsGer |
10.1016/j.infsof.2016.04.012 doi PQ20170501 (DE-627)OLC1987691253 (DE-599)GBVOLC1987691253 (PRQ)c1621-8d56282ee40a288feecc59beb27fffdcdb5deb8fcfe9888d231c03979526b3a60 (KEY)0050086020170000081000000154mutationoperatorsfortestingandroidapps DE-627 ger DE-627 rakwb eng 330 004 DNB 54.50 bkl Deng, Lin verfasserin aut Mutation operators for testing Android apps 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Context: Due to the widespread use of Android devices, Android applications (apps) have more releases, purchases, and downloads than apps for any other mobile devices. The sheer volume of code in these apps creates significant concerns about the quality of the software. However, testing Android apps is different from testing traditional Java programs due to the unique program structure and new features of apps. Simple testing coverage criteria such as statement coverage are insufficient to assure high quality of Android apps. While researchers show significant interest in finding better Android testing approaches, there is still a lack of effective and usable techniques to evaluate their proposed test selection strategies, and to ensure a reasonable number of effective tests. Objective: As mutation analysis has been found to be an effective way to design tests in other software domains, we hypothesize that it is also a viable solution for Android apps. Method: This paper proposes an innovative mutation analysis approach that is specific for Android apps. We define mutation operators specific to the characteristics of Android apps, such as the extensive use of XML files to specify layout and behavior, the inherent event-driven nature, and the unique Activity lifecycle structure. We also report on an empirical study to evaluate these mutation operators. Results: We have built a tool that uses the novel Android mutation operators to mutate the source code of Android apps, then generates mutants that can be installed and run on Android devices. We evaluated the effectiveness of Android mutation testing through an empirical study on real-world apps. This paper introduces several novel mutation operators based on a fault study of Android apps, presents a significant empirical study with real-world apps, and provides conclusions based on an analysis of the results. Conclusion: The results show that the novel Android mutation operators provide comprehensive testing for Android apps. Additionally, as applying mutation testing to Android apps is still at a preliminary stage, we identify challenges, possibilities, and future research directions to make mutation analysis for mobile apps more effective and efficient. Studies Testing Java Software utilities Offutt, Jeff oth Ammann, Paul oth Mirzaei, Nariman oth Enthalten in Information and software technology London : Butterworth, 1987 81(2017), Seite 154-168 (DE-627)130403393 (DE-600)607616-6 (DE-576)015907074 0950-5849 nnns volume:81 year:2017 pages:154-168 http://dx.doi.org/10.1016/j.infsof.2016.04.012 Volltext http://search.proquest.com/docview/1837894308 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT GBV_ILN_70 54.50 AVZ AR 81 2017 154-168 |
| allfieldsSound |
10.1016/j.infsof.2016.04.012 doi PQ20170501 (DE-627)OLC1987691253 (DE-599)GBVOLC1987691253 (PRQ)c1621-8d56282ee40a288feecc59beb27fffdcdb5deb8fcfe9888d231c03979526b3a60 (KEY)0050086020170000081000000154mutationoperatorsfortestingandroidapps DE-627 ger DE-627 rakwb eng 330 004 DNB 54.50 bkl Deng, Lin verfasserin aut Mutation operators for testing Android apps 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Context: Due to the widespread use of Android devices, Android applications (apps) have more releases, purchases, and downloads than apps for any other mobile devices. The sheer volume of code in these apps creates significant concerns about the quality of the software. However, testing Android apps is different from testing traditional Java programs due to the unique program structure and new features of apps. Simple testing coverage criteria such as statement coverage are insufficient to assure high quality of Android apps. While researchers show significant interest in finding better Android testing approaches, there is still a lack of effective and usable techniques to evaluate their proposed test selection strategies, and to ensure a reasonable number of effective tests. Objective: As mutation analysis has been found to be an effective way to design tests in other software domains, we hypothesize that it is also a viable solution for Android apps. Method: This paper proposes an innovative mutation analysis approach that is specific for Android apps. We define mutation operators specific to the characteristics of Android apps, such as the extensive use of XML files to specify layout and behavior, the inherent event-driven nature, and the unique Activity lifecycle structure. We also report on an empirical study to evaluate these mutation operators. Results: We have built a tool that uses the novel Android mutation operators to mutate the source code of Android apps, then generates mutants that can be installed and run on Android devices. We evaluated the effectiveness of Android mutation testing through an empirical study on real-world apps. This paper introduces several novel mutation operators based on a fault study of Android apps, presents a significant empirical study with real-world apps, and provides conclusions based on an analysis of the results. Conclusion: The results show that the novel Android mutation operators provide comprehensive testing for Android apps. Additionally, as applying mutation testing to Android apps is still at a preliminary stage, we identify challenges, possibilities, and future research directions to make mutation analysis for mobile apps more effective and efficient. Studies Testing Java Software utilities Offutt, Jeff oth Ammann, Paul oth Mirzaei, Nariman oth Enthalten in Information and software technology London : Butterworth, 1987 81(2017), Seite 154-168 (DE-627)130403393 (DE-600)607616-6 (DE-576)015907074 0950-5849 nnns volume:81 year:2017 pages:154-168 http://dx.doi.org/10.1016/j.infsof.2016.04.012 Volltext http://search.proquest.com/docview/1837894308 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT GBV_ILN_70 54.50 AVZ AR 81 2017 154-168 |
| language |
English |
| source |
Enthalten in Information and software technology 81(2017), Seite 154-168 volume:81 year:2017 pages:154-168 |
| sourceStr |
Enthalten in Information and software technology 81(2017), Seite 154-168 volume:81 year:2017 pages:154-168 |
| format_phy_str_mv |
Article |
| institution |
findex.gbv.de |
| topic_facet |
Studies Testing Java Software utilities |
| dewey-raw |
330 |
| isfreeaccess_bool |
false |
| container_title |
Information and software technology |
| authorswithroles_txt_mv |
Deng, Lin @@aut@@ Offutt, Jeff @@oth@@ Ammann, Paul @@oth@@ Mirzaei, Nariman @@oth@@ |
| publishDateDaySort_date |
2017-01-01T00:00:00Z |
| hierarchy_top_id |
130403393 |
| dewey-sort |
3330 |
| id |
OLC1987691253 |
| language_de |
englisch |
| fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a2200265 4500</leader><controlfield tag="001">OLC1987691253</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20220216165217.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">170207s2017 xx ||||| 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.infsof.2016.04.012</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">PQ20170501</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC1987691253</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)GBVOLC1987691253</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(PRQ)c1621-8d56282ee40a288feecc59beb27fffdcdb5deb8fcfe9888d231c03979526b3a60</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(KEY)0050086020170000081000000154mutationoperatorsfortestingandroidapps</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">330</subfield><subfield code="a">004</subfield><subfield code="q">DNB</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">54.50</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Deng, Lin</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Mutation operators for testing Android apps</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2017</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Context: Due to the widespread use of Android devices, Android applications (apps) have more releases, purchases, and downloads than apps for any other mobile devices. The sheer volume of code in these apps creates significant concerns about the quality of the software. However, testing Android apps is different from testing traditional Java programs due to the unique program structure and new features of apps. Simple testing coverage criteria such as statement coverage are insufficient to assure high quality of Android apps. While researchers show significant interest in finding better Android testing approaches, there is still a lack of effective and usable techniques to evaluate their proposed test selection strategies, and to ensure a reasonable number of effective tests. Objective: As mutation analysis has been found to be an effective way to design tests in other software domains, we hypothesize that it is also a viable solution for Android apps. Method: This paper proposes an innovative mutation analysis approach that is specific for Android apps. We define mutation operators specific to the characteristics of Android apps, such as the extensive use of XML files to specify layout and behavior, the inherent event-driven nature, and the unique Activity lifecycle structure. We also report on an empirical study to evaluate these mutation operators. Results: We have built a tool that uses the novel Android mutation operators to mutate the source code of Android apps, then generates mutants that can be installed and run on Android devices. We evaluated the effectiveness of Android mutation testing through an empirical study on real-world apps. This paper introduces several novel mutation operators based on a fault study of Android apps, presents a significant empirical study with real-world apps, and provides conclusions based on an analysis of the results. Conclusion: The results show that the novel Android mutation operators provide comprehensive testing for Android apps. Additionally, as applying mutation testing to Android apps is still at a preliminary stage, we identify challenges, possibilities, and future research directions to make mutation analysis for mobile apps more effective and efficient.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Studies</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Testing</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Java</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Software utilities</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Offutt, Jeff</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Ammann, Paul</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Mirzaei, Nariman</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Information and software technology</subfield><subfield code="d">London : Butterworth, 1987</subfield><subfield code="g">81(2017), Seite 154-168</subfield><subfield code="w">(DE-627)130403393</subfield><subfield code="w">(DE-600)607616-6</subfield><subfield code="w">(DE-576)015907074</subfield><subfield code="x">0950-5849</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:81</subfield><subfield code="g">year:2017</subfield><subfield code="g">pages:154-168</subfield></datafield><datafield tag="856" ind1="4" ind2="1"><subfield code="u">http://dx.doi.org/10.1016/j.infsof.2016.04.012</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">http://search.proquest.com/docview/1837894308</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_OLC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-MAT</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">54.50</subfield><subfield code="q">AVZ</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">81</subfield><subfield code="j">2017</subfield><subfield code="h">154-168</subfield></datafield></record></collection>
|
| author |
Deng, Lin |
| spellingShingle |
Deng, Lin ddc 330 bkl 54.50 misc Studies misc Testing misc Java misc Software utilities Mutation operators for testing Android apps |
| authorStr |
Deng, Lin |
| ppnlink_with_tag_str_mv |
@@773@@(DE-627)130403393 |
| format |
Article |
| dewey-ones |
330 - Economics 004 - Data processing & computer science |
| delete_txt_mv |
keep |
| author_role |
aut |
| collection |
OLC |
| remote_str |
false |
| illustrated |
Not Illustrated |
| issn |
0950-5849 |
| topic_title |
330 004 DNB 54.50 bkl Mutation operators for testing Android apps Studies Testing Java Software utilities |
| topic |
ddc 330 bkl 54.50 misc Studies misc Testing misc Java misc Software utilities |
| topic_unstemmed |
ddc 330 bkl 54.50 misc Studies misc Testing misc Java misc Software utilities |
| topic_browse |
ddc 330 bkl 54.50 misc Studies misc Testing misc Java misc Software utilities |
| format_facet |
Aufsätze Gedruckte Aufsätze |
| format_main_str_mv |
Text Zeitschrift/Artikel |
| carriertype_str_mv |
nc |
| author2_variant |
j o jo p a pa n m nm |
| hierarchy_parent_title |
Information and software technology |
| hierarchy_parent_id |
130403393 |
| dewey-tens |
330 - Economics 000 - Computer science, knowledge & systems |
| hierarchy_top_title |
Information and software technology |
| isfreeaccess_txt |
false |
| familylinks_str_mv |
(DE-627)130403393 (DE-600)607616-6 (DE-576)015907074 |
| title |
Mutation operators for testing Android apps |
| ctrlnum |
(DE-627)OLC1987691253 (DE-599)GBVOLC1987691253 (PRQ)c1621-8d56282ee40a288feecc59beb27fffdcdb5deb8fcfe9888d231c03979526b3a60 (KEY)0050086020170000081000000154mutationoperatorsfortestingandroidapps |
| title_full |
Mutation operators for testing Android apps |
| author_sort |
Deng, Lin |
| journal |
Information and software technology |
| journalStr |
Information and software technology |
| lang_code |
eng |
| isOA_bool |
false |
| dewey-hundreds |
300 - Social sciences 000 - Computer science, information & general works |
| recordtype |
marc |
| publishDateSort |
2017 |
| contenttype_str_mv |
txt |
| container_start_page |
154 |
| author_browse |
Deng, Lin |
| container_volume |
81 |
| class |
330 004 DNB 54.50 bkl |
| format_se |
Aufsätze |
| author-letter |
Deng, Lin |
| doi_str_mv |
10.1016/j.infsof.2016.04.012 |
| dewey-full |
330 004 |
| title_sort |
mutation operators for testing android apps |
| title_auth |
Mutation operators for testing Android apps |
| abstract |
Context: Due to the widespread use of Android devices, Android applications (apps) have more releases, purchases, and downloads than apps for any other mobile devices. The sheer volume of code in these apps creates significant concerns about the quality of the software. However, testing Android apps is different from testing traditional Java programs due to the unique program structure and new features of apps. Simple testing coverage criteria such as statement coverage are insufficient to assure high quality of Android apps. While researchers show significant interest in finding better Android testing approaches, there is still a lack of effective and usable techniques to evaluate their proposed test selection strategies, and to ensure a reasonable number of effective tests. Objective: As mutation analysis has been found to be an effective way to design tests in other software domains, we hypothesize that it is also a viable solution for Android apps. Method: This paper proposes an innovative mutation analysis approach that is specific for Android apps. We define mutation operators specific to the characteristics of Android apps, such as the extensive use of XML files to specify layout and behavior, the inherent event-driven nature, and the unique Activity lifecycle structure. We also report on an empirical study to evaluate these mutation operators. Results: We have built a tool that uses the novel Android mutation operators to mutate the source code of Android apps, then generates mutants that can be installed and run on Android devices. We evaluated the effectiveness of Android mutation testing through an empirical study on real-world apps. This paper introduces several novel mutation operators based on a fault study of Android apps, presents a significant empirical study with real-world apps, and provides conclusions based on an analysis of the results. Conclusion: The results show that the novel Android mutation operators provide comprehensive testing for Android apps. Additionally, as applying mutation testing to Android apps is still at a preliminary stage, we identify challenges, possibilities, and future research directions to make mutation analysis for mobile apps more effective and efficient. |
| abstractGer |
Context: Due to the widespread use of Android devices, Android applications (apps) have more releases, purchases, and downloads than apps for any other mobile devices. The sheer volume of code in these apps creates significant concerns about the quality of the software. However, testing Android apps is different from testing traditional Java programs due to the unique program structure and new features of apps. Simple testing coverage criteria such as statement coverage are insufficient to assure high quality of Android apps. While researchers show significant interest in finding better Android testing approaches, there is still a lack of effective and usable techniques to evaluate their proposed test selection strategies, and to ensure a reasonable number of effective tests. Objective: As mutation analysis has been found to be an effective way to design tests in other software domains, we hypothesize that it is also a viable solution for Android apps. Method: This paper proposes an innovative mutation analysis approach that is specific for Android apps. We define mutation operators specific to the characteristics of Android apps, such as the extensive use of XML files to specify layout and behavior, the inherent event-driven nature, and the unique Activity lifecycle structure. We also report on an empirical study to evaluate these mutation operators. Results: We have built a tool that uses the novel Android mutation operators to mutate the source code of Android apps, then generates mutants that can be installed and run on Android devices. We evaluated the effectiveness of Android mutation testing through an empirical study on real-world apps. This paper introduces several novel mutation operators based on a fault study of Android apps, presents a significant empirical study with real-world apps, and provides conclusions based on an analysis of the results. Conclusion: The results show that the novel Android mutation operators provide comprehensive testing for Android apps. Additionally, as applying mutation testing to Android apps is still at a preliminary stage, we identify challenges, possibilities, and future research directions to make mutation analysis for mobile apps more effective and efficient. |
| abstract_unstemmed |
Context: Due to the widespread use of Android devices, Android applications (apps) have more releases, purchases, and downloads than apps for any other mobile devices. The sheer volume of code in these apps creates significant concerns about the quality of the software. However, testing Android apps is different from testing traditional Java programs due to the unique program structure and new features of apps. Simple testing coverage criteria such as statement coverage are insufficient to assure high quality of Android apps. While researchers show significant interest in finding better Android testing approaches, there is still a lack of effective and usable techniques to evaluate their proposed test selection strategies, and to ensure a reasonable number of effective tests. Objective: As mutation analysis has been found to be an effective way to design tests in other software domains, we hypothesize that it is also a viable solution for Android apps. Method: This paper proposes an innovative mutation analysis approach that is specific for Android apps. We define mutation operators specific to the characteristics of Android apps, such as the extensive use of XML files to specify layout and behavior, the inherent event-driven nature, and the unique Activity lifecycle structure. We also report on an empirical study to evaluate these mutation operators. Results: We have built a tool that uses the novel Android mutation operators to mutate the source code of Android apps, then generates mutants that can be installed and run on Android devices. We evaluated the effectiveness of Android mutation testing through an empirical study on real-world apps. This paper introduces several novel mutation operators based on a fault study of Android apps, presents a significant empirical study with real-world apps, and provides conclusions based on an analysis of the results. Conclusion: The results show that the novel Android mutation operators provide comprehensive testing for Android apps. Additionally, as applying mutation testing to Android apps is still at a preliminary stage, we identify challenges, possibilities, and future research directions to make mutation analysis for mobile apps more effective and efficient. |
| collection_details |
GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT GBV_ILN_70 |
| title_short |
Mutation operators for testing Android apps |
| url |
http://dx.doi.org/10.1016/j.infsof.2016.04.012 http://search.proquest.com/docview/1837894308 |
| remote_bool |
false |
| author2 |
Offutt, Jeff Ammann, Paul Mirzaei, Nariman |
| author2Str |
Offutt, Jeff Ammann, Paul Mirzaei, Nariman |
| ppnlink |
130403393 |
| mediatype_str_mv |
n |
| isOA_txt |
false |
| hochschulschrift_bool |
false |
| author2_role |
oth oth oth |
| doi_str |
10.1016/j.infsof.2016.04.012 |
| up_date |
2024-07-03T14:57:26.442Z |
| _version_ |
1803570272213663744 |
| fullrecord_marcxml |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a2200265 4500</leader><controlfield tag="001">OLC1987691253</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20220216165217.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">170207s2017 xx ||||| 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.infsof.2016.04.012</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">PQ20170501</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC1987691253</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)GBVOLC1987691253</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(PRQ)c1621-8d56282ee40a288feecc59beb27fffdcdb5deb8fcfe9888d231c03979526b3a60</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(KEY)0050086020170000081000000154mutationoperatorsfortestingandroidapps</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">330</subfield><subfield code="a">004</subfield><subfield code="q">DNB</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">54.50</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Deng, Lin</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Mutation operators for testing Android apps</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2017</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Context: Due to the widespread use of Android devices, Android applications (apps) have more releases, purchases, and downloads than apps for any other mobile devices. The sheer volume of code in these apps creates significant concerns about the quality of the software. However, testing Android apps is different from testing traditional Java programs due to the unique program structure and new features of apps. Simple testing coverage criteria such as statement coverage are insufficient to assure high quality of Android apps. While researchers show significant interest in finding better Android testing approaches, there is still a lack of effective and usable techniques to evaluate their proposed test selection strategies, and to ensure a reasonable number of effective tests. Objective: As mutation analysis has been found to be an effective way to design tests in other software domains, we hypothesize that it is also a viable solution for Android apps. Method: This paper proposes an innovative mutation analysis approach that is specific for Android apps. We define mutation operators specific to the characteristics of Android apps, such as the extensive use of XML files to specify layout and behavior, the inherent event-driven nature, and the unique Activity lifecycle structure. We also report on an empirical study to evaluate these mutation operators. Results: We have built a tool that uses the novel Android mutation operators to mutate the source code of Android apps, then generates mutants that can be installed and run on Android devices. We evaluated the effectiveness of Android mutation testing through an empirical study on real-world apps. This paper introduces several novel mutation operators based on a fault study of Android apps, presents a significant empirical study with real-world apps, and provides conclusions based on an analysis of the results. Conclusion: The results show that the novel Android mutation operators provide comprehensive testing for Android apps. Additionally, as applying mutation testing to Android apps is still at a preliminary stage, we identify challenges, possibilities, and future research directions to make mutation analysis for mobile apps more effective and efficient.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Studies</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Testing</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Java</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Software utilities</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Offutt, Jeff</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Ammann, Paul</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Mirzaei, Nariman</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Information and software technology</subfield><subfield code="d">London : Butterworth, 1987</subfield><subfield code="g">81(2017), Seite 154-168</subfield><subfield code="w">(DE-627)130403393</subfield><subfield code="w">(DE-600)607616-6</subfield><subfield code="w">(DE-576)015907074</subfield><subfield code="x">0950-5849</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:81</subfield><subfield code="g">year:2017</subfield><subfield code="g">pages:154-168</subfield></datafield><datafield tag="856" ind1="4" ind2="1"><subfield code="u">http://dx.doi.org/10.1016/j.infsof.2016.04.012</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">http://search.proquest.com/docview/1837894308</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_OLC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-MAT</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">54.50</subfield><subfield code="q">AVZ</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">81</subfield><subfield code="j">2017</subfield><subfield code="h">154-168</subfield></datafield></record></collection>
|
| score |
7.3999033 |