research-article

Open access

Do Static Analysis Tools Affect Software Quality when Using Test-driven Development?

Authors:

Fiorella Zampetti,

Maria Teresa Baldassarre,

Massimiliano Di Penta, and

Giuseppe ScannielloAuthors Info & Claims

ESEM '22: Proceedings of the 16th ACM / IEEE International Symposium on Empirical Software Engineering and Measurement

September 2022

Pages 80 - 91

https://doi.org/10.1145/3544902.3546233

Published: 19 September 2022 Publication History

All formats PDF

Abstract

Background. Test-Driven Development (TDD) is an agile software development practice, which encourages developers to write “quick-and-dirty” production code to make tests pass, and then apply refactoring to “clean” written code. However, previous studies have found that refactoring is not applied as often as the TDD process requires, potentially affecting software quality.

Aims. We investigated the benefits of leveraging a Static Analysis Tool (SAT)—plugged-in the Integrated Development Environment (IDE)—on software quality, when applying TDD.

Method. We conducted two controlled experiments, in which the participants—92, in total—performed an implementation task by applying TDD with or without a SAT highlighting the presence of code smells in their source code. We then analyzed the effect of the used SAT on software quality.

Results. We found that, overall, the use of a SAT helped the participants to significantly improve software quality, yet the participants perceived TDD more difficult to be performed.

Conclusions. The obtained results may impact: (i) practitioners, helping them improve their TDD practice through the adoption of proper settings and tools; (ii) educators, in better introducing TDD within their courses; and (iii) researchers, interested in developing better tool support for developers, or further studying TDD.

References

[1]

Maurício Aniche. 2015. Java code metrics calculator (CK). Available in https://github.com/mauricioaniche/ck/.

[2]

Mauricio Finavaro Aniche and Marco Aurélio Gerosa. 2010. Most Common Mistakes in Test-Driven Development Practice: Results from an Online Survey with Developers. In 2010 Third International Conference on Software Testing, Verification, and Validation Workshops. 469–478. https://doi.org/10.1109/ICSTW.2010.16

Digital Library

[3]

Vipin Balachandran. 2013. Reducing human effort and improving quality in peer code reviews using automatic static analysis and reviewer recommendation. In 2013 35th International Conference on Software Engineering (ICSE). 931–940. https://doi.org/10.1109/ICSE.2013.6606642

[4]

Maria Teresa Baldassarre, Valentina Lenarduzzi, Simone Romano, and Nyyti Saarimäki. 2020. On the diffuseness of technical debt items and accuracy of remediation time when using sonarqube. Information and Software Technology 128 (2020), 106377.

Digital Library

[5]

Victor Basili, Gianluigi Caldiera, and H. Dieter Rombach. 2002. Goal Question Metric (GQM) Approach. John Wiley & Sons, Ltd, 528–532. https://doi.org/10.1002/0471028959.sof142

[6]

Gabriele Bavota, Rocco Oliveto, Malcom Gethers, Denys Poshyvanyk, and Andrea De Lucia. 2014. Methodbook: Recommending Move Method Refactorings via Relational Topic Models. IEEE Trans. Software Eng. 40, 7 (2014), 671–694. https://doi.org/10.1109/TSE.2013.60

Digital Library

[7]

Kent Beck. 2003. Test-driven development: by example. Addison-Wesley.

Digital Library

[8]

Karin Becker, Bruno de Souza Costa Pedroso, Marcelo Soares Pimenta, and Ricardo Pezzuol Jacobi. 2015. Besouro: A framework for exploring compliance rules in automatic TDD behavior assessment. Information and Software Technology 57 (2015), 494–508.

[9]

Moritz Beller, Radjino Bholanath, Shane McIntosh, and Andy Zaidman. 2016. Analyzing the state of static analysis: A large-scale evaluation in open source software. In 2016 IEEE 23rd International Conference on Software Analysis, Evolution, and Reengineering (SANER), Vol. 1. IEEE, 470–481.

[10]

Moritz Beller, Georgios Gousios, Annibale Panichella, Sebastian Proksch, Sven Amann, and Andy Zaidman. 2019. Developer Testing in the IDE: Patterns, Beliefs, and Behavior. IEEE Transactions on Software Engineering 45, 3 (2019), 261–284. https://doi.org/10.1109/TSE.2017.2776152

Digital Library

[11]

Wilson Bissi, Adolfo Gustavo Serra Seca Neto, and Maria Cláudia Figueiredo Pereira Emer. 2016. The effects of test driven development on internal quality, external quality and productivity: A systematic review. Inf. Softw. Technol. 74(2016), 45–54. https://doi.org/10.1016/j.infsof.2016.02.004

Digital Library

[12]

Michael Borenstein, Larry Hedges, Julian Higgins, and Hannah Rothstein. 2009. An Introduction to Meta-Analysis. John Wiley & Sons.

[13]

Raymond P. L. Buse and Westley Weimer. 2010. Learning a Metric for Code Readability. IEEE Trans. Software Eng. 36, 4 (2010), 546–558. https://doi.org/10.1109/TSE.2009.70

Digital Library

[14]

G. Ann Campbell. 2018. Cognitive Complexity: An Overview and Evaluation. In Proceedings of the 2018 International Conference on Technical Debt (Gothenburg, Sweden) (TechDebt ’18). Association for Computing Machinery, 57–58. https://doi.org/10.1145/3194164.3194186

Digital Library

[15]

Jeffrey Carver, Letizia Jaccheri, Sandro Morasca, and Forrest Shull. 2003. Issues in Using Students in Empirical Studies in Software Engineering Education. In Proceedings of International Symposium on Software Metrics. IEEE, 239–249.

[16]

Shyam R. Chidamber and Chris. F. Kemerer. 1994. A metrics suite for object oriented design. IEEE Transactions on Software Engineering 20, 6 (1994), 476–493. https://doi.org/10.1109/32.295895

Digital Library

[17]

Jacob Cohen. 1992. A power primer.Psychological bulletin 112 (1992), 155–9. Issue 1.

[18]

César Couto, João Eduardo Montandon, Christofer Silva, and Marco Tulio Valente. 2013. Static correspondence and correlation between field defects and warnings reported by a bug finding tool. Softw. Qual. J. 21, 2 (2013), 241–257. https://doi.org/10.1007/s11219-011-9172-5

Digital Library

[19]

Hakan Erdogmus, Grigori Melnik, and Ron Jeffries. 2010. Test-Driven Development. In Encyclopedia of Software Engineering. Taylor & Francis, 1211–1229.

[20]

Martin Fowler. 1999. Refactoring: Improving the Design of Existing Code (1st ed.). Addison-Wesley.

Digital Library

[21]

Davide Fucci, Hakan Erdogmus, Burak Turhan, Markku Oivo, and Natalia Juristo. 2017. A Dissection of the Test-Driven Development Process: Does It Really Matter to Test-First or to Test-Last?IEEE Transactions on Software Engineering 43, 7 (2017), 597–614.

[22]

Davide Fucci, Giuseppe Scanniello, Simone Romano, and Natalia Juristo. 2018. Need for Sleep: the Impact of a Night of Sleep Deprivation on Novice Developers’ Performance. IEEE Transactions on Software Engineering(2018), 1–1. https://doi.org/10.1109/TSE.2018.2834900

[23]

Davide Fucci, Giuseppe Scanniello, Simone Romano, Martin J. Shepperd, Boyce Sigweni, Fernando Uyaguari Uyaguari, Burak Turhan, Natalia Juristo, and Markku Oivo. 2016. An External Replication on the Effects of Test-driven Development Using a Multi-site Blind Analysis Approach. In International Symposium on Empirical Software Engineering and Measurement. 3:1–3:10.

Digital Library

[24]

Mohammad Ghafari, Timm Gross, Davide Fucci, and Michael Felderer. 2020. Why Research on Test-Driven Development is Inconclusive?. In Proceedings of the 14th ACM / IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM). Association for Computing Machinery, New York, NY, USA, Article 25, 10 pages. https://doi.org/10.1145/3382494.3410687

Digital Library

[25]

Robert J. Grissom and John J. Kim. 2005. Effect sizes for research: A broad practical approach (2nd edition ed.). Lawrence Earlbaum Associates.

[26]

Julian P.T. Higgins, James Thomas, Jacqueline Chandler, Miranda Cumpston, Tianjing Li, Matthew J. Page, and Vivian A. Welch. 2019. Cochrane Handbook for Systematic Reviews of Interventions. John Wiley & Sons.

[27]

Martin Höst, Björn Regnell, and Claes Wohlin. 2000. Using Students as Subjects—A Comparative Study of Students and Professionals in Lead-Time Impact Assessment. Empir. Softw. Eng. 5, 3 (2000), 201–214.

Digital Library

[28]

Andreas Jedlitschka, Marcus Ciolkowski, and Dietmar Pfahl. 2008. Reporting Experiments in Software Engineering. In In Guide to Advanced Empirical Software Engineering. Springer, 201–228.

[29]

Brittany Johnson, Yoonki Song, Emerson Murphy-Hill, and Robert Bowdidge. 2013. Why don’t software developers use static analysis tools to find bugs?. In 2013 35th International Conference on Software Engineering (ICSE). 672–681. https://doi.org/10.1109/ICSE.2013.6606613

[30]

Natalia Juristo and Ana M. Moreno. 2001. Basics of Software Engineering Experimentation. Kluwer Academic Publishers.

Digital Library

[31]

Itir Karac and Burak Turhan. 2018. What Do We (Really) Know about Test-Driven Development?IEEE Softw. 35, 4 (2018), 81–85.

[32]

Itir Karac, Burak Turhan, and Natalia Juristo. 2021. A Controlled Experiment with Novice Developers on the Impact of Task Description Granularity on Software Quality in Test-Driven Development. IEEE Transactions on Software Engineering 47, 7 (2021), 1315–1330. https://doi.org/10.1109/TSE.2019.2920377

[33]

Marouane Kessentini, Troh Josselin Dea, and Ali Ouni. 2017. A Context-Based Refactoring Recommendation Approach Using Simulated Annealing: Two Industrial Case Studies. In Proceedings of the Genetic and Evolutionary Computation Conference (Berlin, Germany) (GECCO ’17). Association for Computing Machinery, New York, NY, USA, 1303–1310. https://doi.org/10.1145/3071178.3071334

Digital Library

[34]

Barbara Kitchenham, Lech Madeyski, and Pearl Brereton. 2020. Meta-analysis for families of experiments in software engineering: a systematic review and reproducibility and validity assessment. Empirical Software Engineering 25, 1 (Jan. 2020), 353–401. https://doi.org/10.1007/s10664-019-09747-0

Digital Library

[35]

Barbara Ann Kitchenham, Lech Madeyski, Giuseppe Scanniello, and Carmine Gravino. 2021. The Importance of the Correlation in Crossover Experiments. IEEE Transactions on Software Engineering(2021), 1–1. https://doi.org/10.1109/TSE.2021.3070480

Digital Library

[36]

Valentina Lenarduzzi, Francesco Lomio, Heikki Huttunen, and Davide Taibi. 2020. Are sonarqube rules inducing bugs?. In 2020 IEEE 27th International Conference on Software Analysis, Evolution and Reengineering (SANER). IEEE, 501–511.

[37]

Jean-Louis Letouzey. 2012. The SQALE method for evaluating Technical Debt. In 2012 Third International Workshop on Managing Technical Debt (MTD). 31–36. https://doi.org/10.1109/MTD.2012.6225997

[38]

Diego Marcilio, Rodrigo Bonifácio, Eduardo Monteiro, Edna Canedo, Welder Luz, and Gustavo Pinto. 2019. Are Static Analysis Violations Really Fixed? A Closer Look at Realistic Usage of SonarQube. In 2019 IEEE/ACM 27th International Conference on Program Comprehension (ICPC). 209–219. https://doi.org/10.1109/ICPC.2019.00040

Digital Library

[39]

Robert C. Martin. 2008. Clean Code: A Handbook of Agile Software Craftsmanship (1st ed.). Prentice Hall.

Digital Library

[40]

Marvin Muñoz Barón, Marvin Wyrich, and Stefan Wagner. 2020. An Empirical Validation of Cognitive Complexity as a Measure of Source Code Understandability. In Proceedings of the 14th ACM / IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM)(ESEM ’20). Association for Computing Machinery, New York, NY, USA, Article 5, 12 pages. https://doi.org/10.1145/3382494.3410636

Digital Library

[41]

Hussan Munir, Misagh Moayyed, and Kai Petersen. 2014. Considering rigor and relevance when evaluating test driven development: A systematic review. Information and Software Technology 56, 4 (2014), 375–394. https://doi.org/10.1016/j.infsof.2014.01.002

Digital Library

[42]

Bram Oppenheim. 1992. Questionnaire Design, Interviewing and Attitude Measurement. Pinter Publishers.

[43]

Fabio Palomba, Michele Tufano, Gabriele Bavota, Rocco Oliveto, Andrian Marcus, Denys Poshyvanyk, and Andrea De Lucia. 2015. Extract Package Refactoring in ARIES. In 37th IEEE/ACM International Conference on Software Engineering, ICSE 2015, Florence, Italy, May 16-24, 2015, Volume 2. 669–672. https://doi.org/10.1109/ICSE.2015.219

[44]

Sebastiano Panichella, Venera Arnaoudova, Massimiliano Di Penta, and Giuliano Antoniol. 2015. Would static analysis tools help developers with code reviews?. In 2015 IEEE 22nd International Conference on Software Analysis, Evolution, and Reengineering (SANER). IEEE, 161–170.

[45]

Yahya Rafique and Vojislav B. Mišić. 2013. The Effects of Test-Driven Development on External Quality and Productivity: A Meta-Analysis. IEEE Transactions on Software Engineering 39, 6 (2013), 835–856. https://doi.org/10.1109/TSE.2012.28

Digital Library

[46]

Jeanine Romano, Jeffrey D. Kromrey, Jesse. Coraggio, Jeff Skowronek, and Linda Devine. 2006. Appropriate statistics for ordinal level data: Should we really be using t-test and Cohen’sd for evaluating group differences on the NSSE and other surveys?. In Annual Meeting of the Florida Association of Institutional Research, February. 1–3.

[47]

Simone Romano. 2022. Do Static Analysis Tools Affect Software Quality when Using Test-driven Development? Online Material. (2022). https://doi.org/10.6084/m9.figshare.20197832.v1

[48]

Simone Romano, Davide Fucci, Giuseppe Scanniello, Burak Turhan, and Natalia Juristo. 2017. Findings from a multi-method study on test-driven development. Inf. Softw. Technol. 89(2017), 64–77.

[49]

Simone Romano, Giuseppe Scanniello, Carlo Sartiani, and Michele Risi. 2016. A Graph-based Approach to Detect Unreachable Methods in Java Software. In Proceedings of Symposium on Applied Computing. ACM, 1538–1541.

Digital Library

[50]

Adrian Santos, Sira Vegas, Markku Oivo, and Natalia Juristo. 2019. A Procedure and Guidelines for Analyzing Groups of Software Engineering Replications. IEEE Trans. Softw. Eng.(2019), 1–1.

[51]

Simone Scalabrino, Gabriele Bavota, Christopher Vendome, Mario Linares Vásquez, Denys Poshyvanyk, and Rocco Oliveto. 2017. Automatically assessing code understandability: how far are we?. In Proceedings of the 32nd IEEE/ACM International Conference on Automated Software Engineering, ASE 2017, Urbana, IL, USA, October 30 - November 03, 2017. 417–427. https://doi.org/10.1109/ASE.2017.8115654

[52]

Giuseppe Scanniello, Carmine Gravino, Marcela Genero, José A. Cruz-Lemus, Genoveffa Tortora, Michele Risi, and Gabriella Dodero. 2018. Do software models based on the UML aid in source-code comprehensibility? Aggregating evidence from 12 controlled experiments. Empir. Softw. Eng. 23, 5 (2018), 2695–2733.

Digital Library

[53]

Giuseppe Scanniello, Simone Romano, Davide Fucci, Burak Turhan, and Natalia Juristo. 2016. Students’ and Professionals’ Perceptions of Test-Driven Development: A Focus Group Study. In Proceedings of the 31st Annual ACM Symposium on Applied Computing (Pisa, Italy) (SAC ’16). Association for Computing Machinery, New York, NY, USA, 1422–1427. https://doi.org/10.1145/2851613.2851778

Digital Library

[54]

Forrest Shull, Grigori Melnik, Burak Turhan, Lucas Layman, Madeline Diep, and Hakan Erdogmus. 2010. What Do We Know about Test-Driven Development?IEEE Software 27, 6 (2010), 16–19. https://doi.org/10.1109/MS.2010.152

Digital Library

[55]

Devarshi Singh, Varun Ramachandra Sekar, Kathryn T. Stolee, and Brittany Johnson. 2017. Evaluating how static analysis tools can reduce code review effort. In 2017 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC). 101–105. https://doi.org/10.1109/VLHCC.2017.8103456

[56]

SonarSource SA. 2022. SonarLint. https://www.sonarlint.org. (Last access: 02/05/2022).

[57]

Jaime Spacco, David Hovemeyer, and William Pugh. 2006. Tracking defect warnings across versions. In Proceedings of the 2006 international workshop on Mining software repositories. 133–136.

Digital Library

[58]

Ayse Tosun, Oscar Dieste, Davide Fucci, Sira Vegas, Burak Turhan, Hakan Erdogmus, Adrian Santos, Markku Oivo, Kimmo Toro, Janne Jarvinen, and Natalia Juristo. 2017. An industry experiment on the effects of test-driven development on external quality and productivity. Empirical Software Engineering 22, 6 (2017), 2763–2805.

Digital Library

[59]

Nikolaos Tsantalis and Alexander Chatzigeorgiou. 2009. Identification of Extract Method Refactoring Opportunities. In 13th European Conference on Software Maintenance and Reengineering, CSMR 2009, Architecture-Centric Maintenance of Large-SCale Software Systems, Kaiserslautern, Germany, 24-27 March 2009. 119–128. https://doi.org/10.1109/CSMR.2009.23

Digital Library

[60]

Nikolaos Tsantalis and Alexander Chatzigeorgiou. 2009. Identification of Move Method Refactoring Opportunities. IEEE Trans. Software Eng. 35, 3 (2009), 347–367. https://doi.org/10.1109/TSE.2009.1

Digital Library

[61]

Nikolaos Tsantalis and Alexander Chatzigeorgiou. 2010. Identification of refactoring opportunities introducing polymorphism. J. Syst. Softw. 83, 3 (2010), 391–404. https://doi.org/10.1016/j.jss.2009.09.017

Digital Library

[62]

Nikolaos Tsantalis, Ameya Ketkar, and Danny Dig. 2022. RefactoringMiner 2.0. IEEE Transactions on Software Engineering 48, 03 (2022), 930–950. https://doi.org/10.1109/TSE.2020.3007722

[63]

Carmine Vassallo, Sebastiano Panichella, Fabio Palomba, Sebastian Proksch, Harald C. Gall, and Andy Zaidman. 2020. How developers engage with static analysis tools in different contexts. Empir. Softw. Eng. 25, 2 (2020), 1419–1457. https://doi.org/10.1007/s10664-019-09750-5

[64]

Carmine Vassallo, Sebastiano Panichella, Fabio Palomba, Sebastian Proksch, Andy Zaidman, and Harald C. Gall. 2018. Context is king: The developer perspective on the usage of static analysis tools. In 2018 IEEE 25th International Conference on Software Analysis, Evolution and Reengineering (SANER). 38–49. https://doi.org/10.1109/SANER.2018.8330195

[65]

Sira Vegas, Cecilia Apa, and Natalia Juristo. 2016. Crossover Designs in Software Engineering Experiments: Benefits and Perils. IEEE Transactions on Software Engineering 42, 2 (2016), 120–135. https://doi.org/10.1109/TSE.2015.2467378

Digital Library

[66]

William C. Wake. 2003. Refactoring Workbook(1st ed.). Addison-Wesley.

[67]

Anne Whitehead. 2003. Meta‐Analysis Of Controlled Clinical Trials. John Wiley & Sons.

[68]

Claes Wohlin, Per Runeson, Martin Höst, Magnus C. Ohlsson, Björn Regnell, and Anders Wesslén. 2012. Experimentation in Software Engineering. Springer.

[69]

Sihan Xu, Aishwarya Sivaraman, Siau-Cheng Khoo, and Jing Xu. 2017. GEMS: An Extract Method Refactoring Recommender. In 2017 IEEE 28th International Symposium on Software Reliability Engineering (ISSRE). 24–34. https://doi.org/10.1109/ISSRE.2017.35

[70]

Fiorella Zampetti, Simone Scalabrino, Rocco Oliveto, Gerardo Canfora, and Massimiliano Di Penta. 2017. How open source projects use static code analysis tools in continuous integration pipelines. In Proceedings of the 14th International Conference on Mining Software Repositories, MSR 2017, Buenos Aires, Argentina, May 20-28, 2017. 334–344. https://doi.org/10.1109/MSR.2017.2

Digital Library

[71]

Jiang Zheng, Laurie A. Williams, Nachiappan Nagappan, Will Snipes, John P. Hudepohl, and Mladen A. Vouk. 2006. On the value of static analysis for fault detection in software. IEEE Transactions on Software Engineering 32, 4 (2006), 240–253. https://doi.org/10.1109/TSE.2006.38

Digital Library

Cited By

Yadav VBotchway RŠenkeřík RKomínková Oplatková Z(2024)A Kafka-Based Robot Automation Testing Using Genetic AlgorithmAETA 2022—Recent Advances in Electrical Engineering and Related Sciences: Theory and Application10.1007/978-981-99-8703-0_25(297-308)Online publication date: 2-Mar-2024
https://doi.org/10.1007/978-981-99-8703-0_25
Nocera SRomano SFrancese RBurlon RScanniello G(2023)Managing Vulnerabilities in Software Projects: the Case of NTT Data2023 49th Euromicro Conference on Software Engineering and Advanced Applications (SEAA)10.1109/SEAA60479.2023.00046(247-253)Online publication date: 6-Sep-2023
https://doi.org/10.1109/SEAA60479.2023.00046
Esposito MRomano SScanniello G(2023)Test-Driven Development and Embedded Systems: An Exploratory Investigation2023 49th Euromicro Conference on Software Engineering and Advanced Applications (SEAA)10.1109/SEAA60479.2023.00045(239-246)Online publication date: 6-Sep-2023
https://doi.org/10.1109/SEAA60479.2023.00045
Show More Cited By

Index Terms

Do Static Analysis Tools Affect Software Quality when Using Test-driven Development?
1. Software and its engineering

Recommendations

Test-Driven Development: Concepts, Taxonomy, and Future Direction

Test-driven development creates software in very short iterations with minimal upfront design. Poised for widespread adoption TDD has become the focus of an increasing number of researchers and developers.

Read More
Test-Driven Development in scientific software: a survey

Scientific software developers are increasingly employing various software engineering practices. Specifically, scientists are beginning to use Test-Driven Development (TDD). Even with this increasing use of TDD, the effect of TDD on scientific software ...
Read More
Driving Software Quality: How Test-Driven Development Impacts Software Quality

Recently, software development teams using agile processes have started widely adopting test-driven development. But does TDD really improve software quality?

Read More

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences

ESEM '22: Proceedings of the 16th ACM / IEEE International Symposium on Empirical Software Engineering and Measurement

September 2022

318 pages

ISBN:9781450394277

DOI:10.1145/3544902

Copyright © 2022 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

SIGSOFT: ACM Special Interest Group on Software Engineering

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 19 September 2022

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article
Research
Refereed limited

Conference

ESEM '22

Sponsor:

SIGSOFT

ESEM '22: ACM / IEEE International Symposium on Empirical Software Engineering and Measurement

September 19 - 23, 2022

Helsinki, Finland

Acceptance Rates

Overall Acceptance Rate 130 of 594 submissions, 22%

Upcoming Conference

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

4
Total Citations
View Citations
598
Total Downloads

Downloads (Last 12 months)356
Downloads (Last 6 weeks)45

Other Metrics

View Author Metrics

Citations

Cited By

Yadav VBotchway RŠenkeřík RKomínková Oplatková Z(2024)A Kafka-Based Robot Automation Testing Using Genetic AlgorithmAETA 2022—Recent Advances in Electrical Engineering and Related Sciences: Theory and Application10.1007/978-981-99-8703-0_25(297-308)Online publication date: 2-Mar-2024
https://doi.org/10.1007/978-981-99-8703-0_25
Nocera SRomano SFrancese RBurlon RScanniello G(2023)Managing Vulnerabilities in Software Projects: the Case of NTT Data2023 49th Euromicro Conference on Software Engineering and Advanced Applications (SEAA)10.1109/SEAA60479.2023.00046(247-253)Online publication date: 6-Sep-2023
https://doi.org/10.1109/SEAA60479.2023.00046
Esposito MRomano SScanniello G(2023)Test-Driven Development and Embedded Systems: An Exploratory Investigation2023 49th Euromicro Conference on Software Engineering and Advanced Applications (SEAA)10.1109/SEAA60479.2023.00045(239-246)Online publication date: 6-Sep-2023
https://doi.org/10.1109/SEAA60479.2023.00045
AlOmar EAlOmar SMkaouer MHaiduc SSchneider J(2023)On the Use of Static Analysis to Engage Students with Software Quality Improvement: An Experience with PMDProceedings of the 45th International Conference on Software Engineering: Software Engineering Education and Training10.1109/ICSE-SEET58685.2023.00023(179-191)Online publication date: 17-May-2023
https://dl.acm.org/doi/10.1109/ICSE-SEET58685.2023.00023

View Options

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

HTML Format

View this article in HTML Format.

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

Media

Figures

Other

Tables

View Table of Contents