R. M. Carvalho, A. B. Marques, Rossana Andrade, A. Sousa, R. Dias, Guilherme Campagnoli
It is well known that many problems in software development arise because the software requirements area is neglected. In this way, the quality of requirements is essential to guarantee the acceptance of the software and, thus, the success of the project. Software metrics can be used to assess the quality of products and artifacts. The literature has several metrics for the requirements area. However, to better meet the particularities of a project, the ideal is to define specific metrics. The Goal-Question-Metric (GQM) is an approach for defining metrics oriented to the organization’s goals. This paper aims to present an experience report about applying the GQM approach to define requirements metrics in a software project in the industry. Since we are going through a pandemic, we adopted GQM in the context of remote work. This paper presents the adaptations that were made, as well as the lessons learned about the application of GQM in a remote environment.
{"title":"An Experience of Using the GQM Approach in a Remote Environment to Define Requirements Metrics","authors":"R. M. Carvalho, A. B. Marques, Rossana Andrade, A. Sousa, R. Dias, Guilherme Campagnoli","doi":"10.1145/3571473.3571491","DOIUrl":"https://doi.org/10.1145/3571473.3571491","url":null,"abstract":"It is well known that many problems in software development arise because the software requirements area is neglected. In this way, the quality of requirements is essential to guarantee the acceptance of the software and, thus, the success of the project. Software metrics can be used to assess the quality of products and artifacts. The literature has several metrics for the requirements area. However, to better meet the particularities of a project, the ideal is to define specific metrics. The Goal-Question-Metric (GQM) is an approach for defining metrics oriented to the organization’s goals. This paper aims to present an experience report about applying the GQM approach to define requirements metrics in a software project in the industry. Since we are going through a pandemic, we adopted GQM in the context of remote work. This paper presents the adaptations that were made, as well as the lessons learned about the application of GQM in a remote environment.","PeriodicalId":440784,"journal":{"name":"Proceedings of the XXI Brazilian Symposium on Software Quality","volume":"317 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124497589","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Rodrigo Feitosa Gonçalves, P. Malcher, Luiz Alexandre M. Costa, Rodrigo Pereira dos Santos
In software ecosystems (SECO), requirements engineering (RE) activities and process require the collaboration of several stakeholders such as requirements engineers, users, third-party developers, collaborators etc. Therefore, it is a highly human-dependent process. Identifying how human and social factors can influence RE-related activities and process would improve RE in SECO. In this context, this study aims to identify which human and social factors influence RE activities in SECO. To do, we conducted a rapid review, supplemented with the snowballing technique to retrieve published studies. A total of 673 studies were returned, of which 12 were included and analyzed from three research questions that provided us with an understanding of the human and social factors of RE in SECO. The results indicate that decision making, multiple actors, geographic distance/time, and negotiation skills are important human and social factors when involved in RE activities in SECO. Finally, the results of this study can help practitioners and researchers define mechanisms to enhance the positive and decrease the negative influence of these factors.
{"title":"Investigating Human and Social Factors in Requirements Engineering in Software Ecosystems","authors":"Rodrigo Feitosa Gonçalves, P. Malcher, Luiz Alexandre M. Costa, Rodrigo Pereira dos Santos","doi":"10.1145/3571473.3571476","DOIUrl":"https://doi.org/10.1145/3571473.3571476","url":null,"abstract":"In software ecosystems (SECO), requirements engineering (RE) activities and process require the collaboration of several stakeholders such as requirements engineers, users, third-party developers, collaborators etc. Therefore, it is a highly human-dependent process. Identifying how human and social factors can influence RE-related activities and process would improve RE in SECO. In this context, this study aims to identify which human and social factors influence RE activities in SECO. To do, we conducted a rapid review, supplemented with the snowballing technique to retrieve published studies. A total of 673 studies were returned, of which 12 were included and analyzed from three research questions that provided us with an understanding of the human and social factors of RE in SECO. The results indicate that decision making, multiple actors, geographic distance/time, and negotiation skills are important human and social factors when involved in RE activities in SECO. Finally, the results of this study can help practitioners and researchers define mechanisms to enhance the positive and decrease the negative influence of these factors.","PeriodicalId":440784,"journal":{"name":"Proceedings of the XXI Brazilian Symposium on Software Quality","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133739779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Barcellos, Gleison Santos, T. Conte, Bianca Trinkenreich, P. Matsubara
Software Quality is a relevant topic that interests both Academy and Industry. Hence, research on this topic should be aligned with the Industry needs, which demands the adoption of research approaches that enable closer interaction between researchers and practitioners. In this context, Design Science Research (DSR) stands out as a way to reduce the gap between theory and practice. DSR is a methodological approach to building innovative artifacts to solve real-world problems and, at the same time, making a scientific contribution. As a problem-oriented research method, DSR seeks to understand the problem, build and evaluate artifacts that allow transforming situations, changing their conditions to better or desirable states. In DSR projects, empirical studies have been usually applied to evaluate the proposed artifact. However, they can also be used to support other activities. Over the last eight years, we have successfully used empirical studies with different purposes in DSR projects. We organized the studies as learning iterations that provide useful knowledge to understand the problem, ground the artifact, develop, evaluate and improve it. As a result, we have experienced a more fluid DSR process and the proposed artifacts have been better grounded and suitable for solving the aimed problem. In this paper, we share our experience by discussing how we have used empirical studies as learning iterations in DSR projects, presenting our approach to organizing empirical studies in a DSR project according to the study purpose and the knowledge it intends to capture, and summarizing two DSR projects that address software quality issues and were developed by using such approach.
{"title":"Organizing Empirical Studies as Learning Iterations in Design Science Research Projects","authors":"M. Barcellos, Gleison Santos, T. Conte, Bianca Trinkenreich, P. Matsubara","doi":"10.1145/3571473.3571474","DOIUrl":"https://doi.org/10.1145/3571473.3571474","url":null,"abstract":"Software Quality is a relevant topic that interests both Academy and Industry. Hence, research on this topic should be aligned with the Industry needs, which demands the adoption of research approaches that enable closer interaction between researchers and practitioners. In this context, Design Science Research (DSR) stands out as a way to reduce the gap between theory and practice. DSR is a methodological approach to building innovative artifacts to solve real-world problems and, at the same time, making a scientific contribution. As a problem-oriented research method, DSR seeks to understand the problem, build and evaluate artifacts that allow transforming situations, changing their conditions to better or desirable states. In DSR projects, empirical studies have been usually applied to evaluate the proposed artifact. However, they can also be used to support other activities. Over the last eight years, we have successfully used empirical studies with different purposes in DSR projects. We organized the studies as learning iterations that provide useful knowledge to understand the problem, ground the artifact, develop, evaluate and improve it. As a result, we have experienced a more fluid DSR process and the proposed artifacts have been better grounded and suitable for solving the aimed problem. In this paper, we share our experience by discussing how we have used empirical studies as learning iterations in DSR projects, presenting our approach to organizing empirical studies in a DSR project according to the study purpose and the knowledge it intends to capture, and summarizing two DSR projects that address software quality issues and were developed by using such approach.","PeriodicalId":440784,"journal":{"name":"Proceedings of the XXI Brazilian Symposium on Software Quality","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123984190","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
S. Souza, Maria A. C. Meireles, J. C. Duarte, J. Maldonado, T. Conte
Context: The Internet of Things (IoT) consists of networks of physical objects embedded with sensors, software, and other technologies to maintain communication and exchange data over a network. These characteristics bring new challenges to the entire development cycle, including requirements engineering (RE). RE practices have been adapted to meet market dynamics and ensure software quality, using a variety of approaches to support this process. One approach for RE is the use of design thinking (DT) techniques, as IoT systems are closely related to product and service innovation. Objective: To analyze the use of DT techniques in the context of IoT systems, evaluating the support for requirements elicitation. Method: An experimental study was carried out in the context of a practical requirements elicitation activity, aiming to obtain results on the support of DT techniques and their ease of use during requirements elicitation for IoT systems. Results: The statistical test did not show significant differences between the groups that used different sets of techniques. In both groups, participants were able to identify requirements related to the IoT paradigm, such as hardware integration, connectivity, mobility, sensing and actuation. The feedback analysis on the ease of use of the techniques pointed out similar difficulties reported by the participants of the two groups, mainly in relation to the terms present in the templates of the techniques. Conclusion: This article aims to contribute to RE in the IoT context, presenting quantitative data and on the ease of use of DT techniques during the requirements elicitation activity.
{"title":"Design for IoT: An Experimental Study to Understand How Design Thinking Can Help in the Elicitation of Requirements for IoT Systems","authors":"S. Souza, Maria A. C. Meireles, J. C. Duarte, J. Maldonado, T. Conte","doi":"10.1145/3571473.3571483","DOIUrl":"https://doi.org/10.1145/3571473.3571483","url":null,"abstract":"Context: The Internet of Things (IoT) consists of networks of physical objects embedded with sensors, software, and other technologies to maintain communication and exchange data over a network. These characteristics bring new challenges to the entire development cycle, including requirements engineering (RE). RE practices have been adapted to meet market dynamics and ensure software quality, using a variety of approaches to support this process. One approach for RE is the use of design thinking (DT) techniques, as IoT systems are closely related to product and service innovation. Objective: To analyze the use of DT techniques in the context of IoT systems, evaluating the support for requirements elicitation. Method: An experimental study was carried out in the context of a practical requirements elicitation activity, aiming to obtain results on the support of DT techniques and their ease of use during requirements elicitation for IoT systems. Results: The statistical test did not show significant differences between the groups that used different sets of techniques. In both groups, participants were able to identify requirements related to the IoT paradigm, such as hardware integration, connectivity, mobility, sensing and actuation. The feedback analysis on the ease of use of the techniques pointed out similar difficulties reported by the participants of the two groups, mainly in relation to the terms present in the templates of the techniques. Conclusion: This article aims to contribute to RE in the IoT context, presenting quantitative data and on the ease of use of DT techniques during the requirements elicitation activity.","PeriodicalId":440784,"journal":{"name":"Proceedings of the XXI Brazilian Symposium on Software Quality","volume":"126 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128846404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Unit tests are artifacts generated during the development process to identify software errors early. Unit tests can be affected by Test Smells (TS), which are defined as poorly designed tests due to bad programming practices implemented in unit test code. Problems caused by TS negatively impact the efficiency of developers and the understanding and maintenance of unit tests. Reducing the problems caused by TS can occur through refactoring activities. Despite the existence of studies that seek to identify the occurrence of TS in unit tests and proposals for semi-automatic refactoring, there are no studies related to the automatic removal of TS from the test repository. In this context, this study presents a method for automatic TS removal called Eager Test, which occurs when a test verifies more than one method of the code. The proposed method was evaluated through experiments, comparing the original version of a unit tests repository with its automatically refactored version. The results are promising, showing an Eager Test removal rate of 99,4% of unit tests in the repository without causing test errors or test fails. However, there was an increase in test execution time and of lines of code, resulting from the quantity of tests that were extracted. The proposed method supports improving the quality of unit tests and reduces the effort required by developers to remove Eager Test.
{"title":"Automatic Refactoring Method to Remove Eager Test Smell","authors":"Adriano Pizzini, S. Reinehr, A. Malucelli","doi":"10.1145/3571473.3571478","DOIUrl":"https://doi.org/10.1145/3571473.3571478","url":null,"abstract":"Unit tests are artifacts generated during the development process to identify software errors early. Unit tests can be affected by Test Smells (TS), which are defined as poorly designed tests due to bad programming practices implemented in unit test code. Problems caused by TS negatively impact the efficiency of developers and the understanding and maintenance of unit tests. Reducing the problems caused by TS can occur through refactoring activities. Despite the existence of studies that seek to identify the occurrence of TS in unit tests and proposals for semi-automatic refactoring, there are no studies related to the automatic removal of TS from the test repository. In this context, this study presents a method for automatic TS removal called Eager Test, which occurs when a test verifies more than one method of the code. The proposed method was evaluated through experiments, comparing the original version of a unit tests repository with its automatically refactored version. The results are promising, showing an Eager Test removal rate of 99,4% of unit tests in the repository without causing test errors or test fails. However, there was an increase in test execution time and of lines of code, resulting from the quantity of tests that were extracted. The proposed method supports improving the quality of unit tests and reduces the effort required by developers to remove Eager Test.","PeriodicalId":440784,"journal":{"name":"Proceedings of the XXI Brazilian Symposium on Software Quality","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120961164","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
It is common for software projects to incur technical debt (TD) during their development process. It should be no different for IoT software projects, mainly characterized by integrating devices and communication technologies. This work reduces a gap in the technical literature by presenting an investigation of TD in the context of IoT software projects. To this end, it describes how TD has been perceived, identified, and represented when developing two IoT software projects regarding monitoring an individual's oxygenation level (OximetroIoT) and biosafety indicators in classrooms and laboratories (SAFE-UFRJ). By applying a TD management strategy, we identify, monitor, and pay TD items incurred during the development process of those projects. It allowed us to identify 153 TD items grouped into 16 different TD types (three new ones compared with current taxonomies) and 75 effects due to their presence. Overall, the investigated IoT software projects experience TD differently from software projects.
{"title":"Exploring Technical Debt on IoT Software Projects","authors":"Nicolli Rios, R. Spínola, G. Travassos","doi":"10.1145/3571473.3571495","DOIUrl":"https://doi.org/10.1145/3571473.3571495","url":null,"abstract":"It is common for software projects to incur technical debt (TD) during their development process. It should be no different for IoT software projects, mainly characterized by integrating devices and communication technologies. This work reduces a gap in the technical literature by presenting an investigation of TD in the context of IoT software projects. To this end, it describes how TD has been perceived, identified, and represented when developing two IoT software projects regarding monitoring an individual's oxygenation level (OximetroIoT) and biosafety indicators in classrooms and laboratories (SAFE-UFRJ). By applying a TD management strategy, we identify, monitor, and pay TD items incurred during the development process of those projects. It allowed us to identify 153 TD items grouped into 16 different TD types (three new ones compared with current taxonomies) and 75 effects due to their presence. Overall, the investigated IoT software projects experience TD differently from software projects.","PeriodicalId":440784,"journal":{"name":"Proceedings of the XXI Brazilian Symposium on Software Quality","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126066762","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
R. F. Gonçalves, A. Menolli, Gustavo Marcelino Dionisio
The Internet of Things (IoT) is a paradigm that provides an ecosystem for a fast-growing quantity of connected devices, also defined as cyber-physical devices. The creation of Internet of Things solutions is fairly complex, integrating and communicating between sensors, devices, and larger systems. The Model Driven Development (MDD), a software development methodology that allows the generation of software solutions through abstract models, may help to create quality Internet of Things solutions. Thus, this study aims to evaluate the quality of cyber-physical solutions developed from an MDD platform. For this purpose, we performed an quasi-experiment, comparing a well-stable cyber-physical solution with the same solution implemented in an MDD tool. To compare the solutions, we explored several characteristics of ISO/IEC 25010 standard using qualitative and quantitative analysis. The results show the code generated from the MDD tool presented better maintainability and provided the same performance and functional suitability as the original code.
{"title":"An Analysis of the Quality of Model Driven Development Solutions Applied to Cyber-Physical Devices","authors":"R. F. Gonçalves, A. Menolli, Gustavo Marcelino Dionisio","doi":"10.1145/3571473.3571484","DOIUrl":"https://doi.org/10.1145/3571473.3571484","url":null,"abstract":"The Internet of Things (IoT) is a paradigm that provides an ecosystem for a fast-growing quantity of connected devices, also defined as cyber-physical devices. The creation of Internet of Things solutions is fairly complex, integrating and communicating between sensors, devices, and larger systems. The Model Driven Development (MDD), a software development methodology that allows the generation of software solutions through abstract models, may help to create quality Internet of Things solutions. Thus, this study aims to evaluate the quality of cyber-physical solutions developed from an MDD platform. For this purpose, we performed an quasi-experiment, comparing a well-stable cyber-physical solution with the same solution implemented in an MDD tool. To compare the solutions, we explored several characteristics of ISO/IEC 25010 standard using qualitative and quantitative analysis. The results show the code generated from the MDD tool presented better maintainability and provided the same performance and functional suitability as the original code.","PeriodicalId":440784,"journal":{"name":"Proceedings of the XXI Brazilian Symposium on Software Quality","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126553909","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Thiciane Couto, S. Marczak, D. Callegari, Michael Móra, Fabio Gomes
BDD supports software development teams in building and delivering user needs. Although the claims that BDD adoption improves product and software processes, there is still no consolidated evidence about its benefits nor have we found quality indicators to measure them. This paper reports on a study that aimed to identify and characterize the benefits of BDD adoption in software teams novice to it. We conducted a multiple case study in teams formed by students working with industry practitioners in active-based learning programs. Perceived benefits are improved communication, faster delivery cycles, better product quality, among others. Each benefit was characterized into aspects that express how the benefit is conceptualized. For instance, improved communication is perceived by sharper conversations with the product owner. Our results might inspire both practitioners and scholars in the pursuit of quality indicators to measure the benefits of adopting BDD.
{"title":"On the Characterization of Behavior-Driven Development Adoption Benefits: A Multiple Case Study","authors":"Thiciane Couto, S. Marczak, D. Callegari, Michael Móra, Fabio Gomes","doi":"10.1145/3571473.3571492","DOIUrl":"https://doi.org/10.1145/3571473.3571492","url":null,"abstract":"BDD supports software development teams in building and delivering user needs. Although the claims that BDD adoption improves product and software processes, there is still no consolidated evidence about its benefits nor have we found quality indicators to measure them. This paper reports on a study that aimed to identify and characterize the benefits of BDD adoption in software teams novice to it. We conducted a multiple case study in teams formed by students working with industry practitioners in active-based learning programs. Perceived benefits are improved communication, faster delivery cycles, better product quality, among others. Each benefit was characterized into aspects that express how the benefit is conceptualized. For instance, improved communication is perceived by sharper conversations with the product owner. Our results might inspire both practitioners and scholars in the pursuit of quality indicators to measure the benefits of adopting BDD.","PeriodicalId":440784,"journal":{"name":"Proceedings of the XXI Brazilian Symposium on Software Quality","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122199728","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Vinícius Camargo Andrade, Rhodrigo Deda Gomes, S. Reinehr, C. O. Freitas, A. Malucelli
Service providers increasingly collect, process, store, and share data from their users to understand their preferences to make better decisions and make accurate estimates for the delivery of advertisements, products, and services. However, the misuse of personal data puts the privacy of the data subjects at risk. In addition, privacy can directly affect the quality of the software product. In an attempt to minimize these problems, the Privacy by Design approach has been proposed to ensure that privacy requirements are incorporated from the early stages of system development and applied to the entire data lifecycles. Meanwhile, Privacy by Design is often criticized due to its lack of specific methodology and tools capable of translating its principles into practical Software Engineering activities. Therefore, this research aims to investigate, through a systematic literature review, how Privacy by Design principles have been applied in the Software Engineering area. The search retrieved 6046 primary articles, published up to May 2022. After applying the inclusion and exclusion criteria, 75 primary studies were selected for analysis. The results show that there is a lack of models, processes, and tools to support Privacy by Design throughout the software development lifecycle and that it has become more relevant considering the requirements of the General Data Protection Regulation (GDPR).
{"title":"Privacy by Design and Software Engineering: a Systematic Literature Review","authors":"Vinícius Camargo Andrade, Rhodrigo Deda Gomes, S. Reinehr, C. O. Freitas, A. Malucelli","doi":"10.1145/3571473.3571480","DOIUrl":"https://doi.org/10.1145/3571473.3571480","url":null,"abstract":"Service providers increasingly collect, process, store, and share data from their users to understand their preferences to make better decisions and make accurate estimates for the delivery of advertisements, products, and services. However, the misuse of personal data puts the privacy of the data subjects at risk. In addition, privacy can directly affect the quality of the software product. In an attempt to minimize these problems, the Privacy by Design approach has been proposed to ensure that privacy requirements are incorporated from the early stages of system development and applied to the entire data lifecycles. Meanwhile, Privacy by Design is often criticized due to its lack of specific methodology and tools capable of translating its principles into practical Software Engineering activities. Therefore, this research aims to investigate, through a systematic literature review, how Privacy by Design principles have been applied in the Software Engineering area. The search retrieved 6046 primary articles, published up to May 2022. After applying the inclusion and exclusion criteria, 75 primary studies were selected for analysis. The results show that there is a lack of models, processes, and tools to support Privacy by Design throughout the software development lifecycle and that it has become more relevant considering the requirements of the General Data Protection Regulation (GDPR).","PeriodicalId":440784,"journal":{"name":"Proceedings of the XXI Brazilian Symposium on Software Quality","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122261455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Érica Miranda Sousa, Andreia Rodrigues, Nityananda Teixeira, I. Santos, Mariana Salamoni Francisco, Rossana Andrade, D. R. Vasconcelos
It’s common to face errors during the process of software development. Be it an agile or traditional methodology, those errors are documented and registered in tools that allow us to manage and trace them. This data is rich in information about the product we are developing and the processes being used. Therefore, the analysis of this data can give us a better view of the product’s characteristics, its faults and how they affect it’s quality. Having said that, this article relates the use of Machine Learning techniques in a software’s error data base, to identify and classify critical areas in the system, in order to support decision making from the test team, the evolution process and production code maintenance by the developers. Overall, a set of 1045 software defects registries were collected, and we could identify that: (i) 63% of the defects are concentraded in 10 of the 71 existing functionalities, (ii) a functionality has a tendecy to show defects in the last versions of our software, (iii) the software have 4 critical functionalites that concentrate 52% of the reported defects and show recurrent defects.
{"title":"From past to future: An experience using data mining to guide tests.","authors":"Érica Miranda Sousa, Andreia Rodrigues, Nityananda Teixeira, I. Santos, Mariana Salamoni Francisco, Rossana Andrade, D. R. Vasconcelos","doi":"10.1145/3571473.3571493","DOIUrl":"https://doi.org/10.1145/3571473.3571493","url":null,"abstract":"It’s common to face errors during the process of software development. Be it an agile or traditional methodology, those errors are documented and registered in tools that allow us to manage and trace them. This data is rich in information about the product we are developing and the processes being used. Therefore, the analysis of this data can give us a better view of the product’s characteristics, its faults and how they affect it’s quality. Having said that, this article relates the use of Machine Learning techniques in a software’s error data base, to identify and classify critical areas in the system, in order to support decision making from the test team, the evolution process and production code maintenance by the developers. Overall, a set of 1045 software defects registries were collected, and we could identify that: (i) 63% of the defects are concentraded in 10 of the 71 existing functionalities, (ii) a functionality has a tendecy to show defects in the last versions of our software, (iii) the software have 4 critical functionalites that concentrate 52% of the reported defects and show recurrent defects.","PeriodicalId":440784,"journal":{"name":"Proceedings of the XXI Brazilian Symposium on Software Quality","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129480943","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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