Skip to main content

2019 | OriginalPaper | Buchkapitel

Smart Measurements and Analysis for Software Quality Enhancement

verfasst von : Sarah Dahab, Stephane Maag, Wissam Mallouli, Ana Cavalli

Erschienen in: Software Technologies

Verlag: Springer International Publishing

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

Requests to improve the quality of software are increasing due to the competition in software industry and the complexity of software development integrating multiple technology domains (e.g., IoT, Big Data, Cloud, Artificial Intelligence, Security Technologies). Measurements collection and analysis is key activity to assess software quality during its development live-cycle. To optimize this activity, our main idea is to periodically select relevant measures to be executed (among a set of possible measures) and automatize their analysis by using a dedicated tool. The proposed solution is integrated in a whole PaaS platform called MEASURE. The tools supporting this activity are Software Metric Suggester tool that recommends metrics of interest according several software development constraints and based on artificial intelligence and MINT tool that correlates collected measurements and provides near real-time recommendations to software development stakeholders (i.e. DevOps team, project manager, human resources manager etc.) to improve the quality of the development process. To illustrate the efficiency of both tools, we created different scenarios on which both approaches are applied. Results show that both tools are complementary and can be used to improve the software development process and thus the final software quality.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Literatur
3.
Zurück zum Zitat Bagnato, A., da Silva, M.A.A., Abherve, A., Rocheteau, J., Pihery, C., Mabit, P.: Measuring green software engineering in the MEASURE ITEA 3 project. In: Condori-Fernández, N., Procaccianti, G., Calero, C., Bagnato, A. (eds.) Proceedings of the 3rd International Workshop on Measurement and Metrics for Green and Sustainable Software Systems, MeGSuS 2016, Co-Located with 10th International Symposium on Empirical Software Engineering and Measurement (ESEM 2016), Ciudad Real, Spain, 7 September 2016. CEUR Workshop Proceedings, vol. 1708, pp. 33–42. CEUR-WS.org (2016). http://ceur-ws.org/Vol-1708/paper-06.pdf Bagnato, A., da Silva, M.A.A., Abherve, A., Rocheteau, J., Pihery, C., Mabit, P.: Measuring green software engineering in the MEASURE ITEA 3 project. In: Condori-Fernández, N., Procaccianti, G., Calero, C., Bagnato, A. (eds.) Proceedings of the 3rd International Workshop on Measurement and Metrics for Green and Sustainable Software Systems, MeGSuS 2016, Co-Located with 10th International Symposium on Empirical Software Engineering and Measurement (ESEM 2016), Ciudad Real, Spain, 7 September 2016. CEUR Workshop Proceedings, vol. 1708, pp. 33–42. CEUR-WS.org (2016). http://​ceur-ws.​org/​Vol-1708/​paper-06.​pdf
4.
Zurück zum Zitat Bouwers, E., van Deursen, A., Visser, J.: Evaluating usefulness of software metrics: an industrial experience report. In: Notkin, D., Cheng, B.H.C., Pohl, K. (eds.) 35th International Conference on Software Engineering, ICSE 2013, San Francisco, CA, USA, 18–26 May 2013, pp. 921–930. IEEE Computer Society (2013). https://doi.org/10.1109/ICSE.2013.6606641 Bouwers, E., van Deursen, A., Visser, J.: Evaluating usefulness of software metrics: an industrial experience report. In: Notkin, D., Cheng, B.H.C., Pohl, K. (eds.) 35th International Conference on Software Engineering, ICSE 2013, San Francisco, CA, USA, 18–26 May 2013, pp. 921–930. IEEE Computer Society (2013). https://​doi.​org/​10.​1109/​ICSE.​2013.​6606641
6.
Zurück zum Zitat Dahab, S.A., Maag, S., Hernandez Porras, J.J.: A novel formal approach to automatically suggest metrics in software measurement plans. In: 2018 13th International Conference on Evaluation of Novel Approaches to Software Engineering (ENASE). IEEE (2018) Dahab, S.A., Maag, S., Hernandez Porras, J.J.: A novel formal approach to automatically suggest metrics in software measurement plans. In: 2018 13th International Conference on Evaluation of Novel Approaches to Software Engineering (ENASE). IEEE (2018)
7.
Zurück zum Zitat Dahab, S.A., Silva, E., Maag, S., Cavalli, A.R., Mallouli, W.: Enhancing software development process quality based on metrics correlation and suggestion. In: Proceedings of the 13th International Conference on Software Technologies, ICSOFT 2018, Porto, Portugal, 26–28 July 2018, pp. 154–165 (2018) Dahab, S.A., Silva, E., Maag, S., Cavalli, A.R., Mallouli, W.: Enhancing software development process quality based on metrics correlation and suggestion. In: Proceedings of the 13th International Conference on Software Technologies, ICSOFT 2018, Porto, Portugal, 26–28 July 2018, pp. 154–165 (2018)
8.
Zurück zum Zitat De Maesschalck, R., Jouan-Rimbaud, D., Massart, D.L.: The Mahalanobis distance. Chemometr. Intell. Lab. Syst. 50(1), 1–18 (2000)CrossRef De Maesschalck, R., Jouan-Rimbaud, D., Massart, D.L.: The Mahalanobis distance. Chemometr. Intell. Lab. Syst. 50(1), 1–18 (2000)CrossRef
9.
Zurück zum Zitat Fenton, N., Bieman, J.: Software Metrics: A Rigorous and Practical Approach. CRC Press, Boca Raton (2014)CrossRef Fenton, N., Bieman, J.: Software Metrics: A Rigorous and Practical Approach. CRC Press, Boca Raton (2014)CrossRef
10.
Zurück zum Zitat Fenton, N.E., Pfleeger, S.L.: Software Metrics - A Practical and Rigorous Approach, 2nd edn. International Thomson, Boston (1996) Fenton, N.E., Pfleeger, S.L.: Software Metrics - A Practical and Rigorous Approach, 2nd edn. International Thomson, Boston (1996)
11.
12.
Zurück zum Zitat García-Munoz, J., García-Valls, M., Escribano-Barreno, J.: Improved metrics handling in SonarQube for software quality monitoring. In: Omatu, S., et al. (eds.) Distributed Computing and Artificial Intelligence, 13th International Conference. AISC, vol. 474, pp. 463–470. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-40162-1_50CrossRef García-Munoz, J., García-Valls, M., Escribano-Barreno, J.: Improved metrics handling in SonarQube for software quality monitoring. In: Omatu, S., et al. (eds.) Distributed Computing and Artificial Intelligence, 13th International Conference. AISC, vol. 474, pp. 463–470. Springer, Cham (2016). https://​doi.​org/​10.​1007/​978-3-319-40162-1_​50CrossRef
13.
Zurück zum Zitat Ge, Z., Song, Z., Ding, S.X., Huang, B.: Data mining and analytics in the process industry: the role of machine learning. IEEE Access 5, 20590–20616 (2017)CrossRef Ge, Z., Song, Z., Ding, S.X., Huang, B.: Data mining and analytics in the process industry: the role of machine learning. IEEE Access 5, 20590–20616 (2017)CrossRef
15.
Zurück zum Zitat Group, O.M.: Structured Metrics Metamodel (SMM) (October), pp. 1–110 (2012) Group, O.M.: Structured Metrics Metamodel (SMM) (October), pp. 1–110 (2012)
16.
Zurück zum Zitat Hauser, J., Katz, G.: Metrics: you are what you measure!. Eur. Manag. J. 16, 517–528 (1998)CrossRef Hauser, J., Katz, G.: Metrics: you are what you measure!. Eur. Manag. J. 16, 517–528 (1998)CrossRef
17.
Zurück zum Zitat ISO/IEC: ISO/IEC 25010 - systems and software engineering - systems and software quality requirements and evaluation (square) - system and software quality models. Technical report (2010) ISO/IEC: ISO/IEC 25010 - systems and software engineering - systems and software quality requirements and evaluation (square) - system and software quality models. Technical report (2010)
18.
Zurück zum Zitat Jain, A.K.: Data clustering: 50 years beyond k-means. Pattern Recogn. Lett. 31(8), 651–666 (2010)CrossRef Jain, A.K.: Data clustering: 50 years beyond k-means. Pattern Recogn. Lett. 31(8), 651–666 (2010)CrossRef
19.
Zurück zum Zitat Kevrekidis, K., et al.: Software complexity and testing effectiveness: an empirical study. In: 2009 Annual Reliability and Maintainability Symposium, RAMS 2009. IEEE (2009) Kevrekidis, K., et al.: Software complexity and testing effectiveness: an empirical study. In: 2009 Annual Reliability and Maintainability Symposium, RAMS 2009. IEEE (2009)
20.
Zurück zum Zitat Khalid, S., Khalil, T., Nasreen, S.: A survey of feature selection and feature extraction techniques in machine learning. In: Science and Information Conference (SAI), pp. 372–378. IEEE (2014) Khalid, S., Khalil, T., Nasreen, S.: A survey of feature selection and feature extraction techniques in machine learning. In: Science and Information Conference (SAI), pp. 372–378. IEEE (2014)
24.
Zurück zum Zitat van der Meulen, M., Revilla, M.A.: Correlations between internal software metrics and software dependability in a large population of small C/C++ programs. In: ISSRE 2007, The 18th IEEE International Symposium on Software Reliability, Trollhättan, Sweden, 5–9 November 2007, pp. 203–208 (2007) van der Meulen, M., Revilla, M.A.: Correlations between internal software metrics and software dependability in a large population of small C/C++ programs. In: ISSRE 2007, The 18th IEEE International Symposium on Software Reliability, Trollhättan, Sweden, 5–9 November 2007, pp. 203–208 (2007)
25.
Zurück zum Zitat Papadopoulos, L., Marantos, C., Digkas, G., Ampatzoglou, A., Chatzigeorgiou, A., Soudris, D.: Interrelations between software quality metrics, performance and energy consumption in embedded applications. In: Stuijk, S. (ed.) Proceedings of the 21st International Workshop on Software and Compilers for Embedded Systems, SCOPES 2018, Sankt Goar, Germany, 28–30 May 2018, pp. 62–65. ACM (2018). https://doi.org/10.1145/3207719.3207736 Papadopoulos, L., Marantos, C., Digkas, G., Ampatzoglou, A., Chatzigeorgiou, A., Soudris, D.: Interrelations between software quality metrics, performance and energy consumption in embedded applications. In: Stuijk, S. (ed.) Proceedings of the 21st International Workshop on Software and Compilers for Embedded Systems, SCOPES 2018, Sankt Goar, Germany, 28–30 May 2018, pp. 62–65. ACM (2018). https://​doi.​org/​10.​1145/​3207719.​3207736
26.
Zurück zum Zitat Pelleg, D., Moore, A.W., et al.: X-means: extending k-means with efficient estimation of the number of clusters. In: ICML, vol. 1, pp. 727–734 (2000) Pelleg, D., Moore, A.W., et al.: X-means: extending k-means with efficient estimation of the number of clusters. In: ICML, vol. 1, pp. 727–734 (2000)
28.
Zurück zum Zitat Shweta, S.S., Singh, R.: Analysis of correlation between software complexity metrics. IJISET Int. J. Innovative Sci. Eng. Technol. 2(8), 902–905 (2015) Shweta, S.S., Singh, R.: Analysis of correlation between software complexity metrics. IJISET Int. J. Innovative Sci. Eng. Technol. 2(8), 902–905 (2015)
29.
Zurück zum Zitat Vapnik, V.N., Vapnik, V.: Statistical Learning Theory, vol. 1. Wiley, New York (1998)MATH Vapnik, V.N., Vapnik, V.: Statistical Learning Theory, vol. 1. Wiley, New York (1998)MATH
Metadaten
Titel
Smart Measurements and Analysis for Software Quality Enhancement
verfasst von
Sarah Dahab
Stephane Maag
Wissam Mallouli
Ana Cavalli
Copyright-Jahr
2019
DOI
https://doi.org/10.1007/978-3-030-29157-0_9