Pub Date : 2021-05-01DOI: 10.1109/ICSE-Companion52605.2021.00109
Tapajit Dey, Andrey Karnauch, A. Mockus
This describes the artifact associated with the article "Representation of Developer Expertise in Open Source Software" at the International Conference on Software Engineering 2021. The aim of the original paper was to define afeasible representation of adeveloper's expertise in specific focus areas of software development by gauging their fluency with different sets of APIs. The artifact is made available through Zenodo under the CC-BY-4.0 license at https://doi.org/10.5281/zenodo.4457107. The README file has detailed instructions on how to replicate the results presented in the original paper. The artifact includes the input dataset (with the developers' names and email addresses replaced by their corresponding SHA1 digest values to protect privacy) and all the associated scripts. The trained Doc2Vec models are also included in the artifact. These models can be used to obtain the Skill Space representations of developers, projects, and APIs without having to re-train the model.
{"title":"Replication Package for Representation of Developer Expertise in Open Source Software","authors":"Tapajit Dey, Andrey Karnauch, A. Mockus","doi":"10.1109/ICSE-Companion52605.2021.00109","DOIUrl":"https://doi.org/10.1109/ICSE-Companion52605.2021.00109","url":null,"abstract":"This describes the artifact associated with the article \"Representation of Developer Expertise in Open Source Software\" at the International Conference on Software Engineering 2021. The aim of the original paper was to define afeasible representation of adeveloper's expertise in specific focus areas of software development by gauging their fluency with different sets of APIs. The artifact is made available through Zenodo under the CC-BY-4.0 license at https://doi.org/10.5281/zenodo.4457107. The README file has detailed instructions on how to replicate the results presented in the original paper. The artifact includes the input dataset (with the developers' names and email addresses replaced by their corresponding SHA1 digest values to protect privacy) and all the associated scripts. The trained Doc2Vec models are also included in the artifact. These models can be used to obtain the Skill Space representations of developers, projects, and APIs without having to re-train the model.","PeriodicalId":136929,"journal":{"name":"2021 IEEE/ACM 43rd International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121071810","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}
Pub Date : 2021-05-01DOI: 10.1109/ICSE-Companion52605.2021.00129
R. Toledo
Static analysis results can be overwhelming depending on their complexity and the total number of results. Interactive graph visualization can help engineers explore the connections between different code entities while visually supporting insights about the code's behaviour. In our doctoral research, we aim to investigate how a graphical model of a program and its analysis results can support the engineer's understanding. We expect that a graphical interface can ease the diagnose of faults and reduce the cognitive load required to comprehend reported control and data flows present in the codebase.
{"title":"Interactive Graph Exploration for Comprehension of Static Analysis Results","authors":"R. Toledo","doi":"10.1109/ICSE-Companion52605.2021.00129","DOIUrl":"https://doi.org/10.1109/ICSE-Companion52605.2021.00129","url":null,"abstract":"Static analysis results can be overwhelming depending on their complexity and the total number of results. Interactive graph visualization can help engineers explore the connections between different code entities while visually supporting insights about the code's behaviour. In our doctoral research, we aim to investigate how a graphical model of a program and its analysis results can support the engineer's understanding. We expect that a graphical interface can ease the diagnose of faults and reduce the cognitive load required to comprehend reported control and data flows present in the codebase.","PeriodicalId":136929,"journal":{"name":"2021 IEEE/ACM 43rd International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122026107","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}
Pub Date : 2021-05-01DOI: 10.1109/ICSE-Companion52605.2021.00124
Luciano de Aguiar Monteiro
The software development industry has been evolving with new development standards and service delivery models. Agile methodologies have reached their completion with DevOps, thereby increasing the quality of the software and creating greater speed in delivery. However, a gap regarding the formalization of its adoption and implementation doubts became relevant. My hypothesis is that, by systematizing the introduction of DevOps into the software development process and defining the function of the members of the DevOps team members, may well make it quicker to implement this process, thus reducing conflicts between the teams. As part of the investigation of this hypothesis, the result of the research will be applied in practical development environments i.e. in a Technology Agency of the State of the Brazilian Government and also at the Brazilian Company Neurotech in order to evaluate its effectiveness from metrics appropriate for DevOps environments.
{"title":"A Proposal to Systematize Introducing DevOps into the Software Development Process","authors":"Luciano de Aguiar Monteiro","doi":"10.1109/ICSE-Companion52605.2021.00124","DOIUrl":"https://doi.org/10.1109/ICSE-Companion52605.2021.00124","url":null,"abstract":"The software development industry has been evolving with new development standards and service delivery models. Agile methodologies have reached their completion with DevOps, thereby increasing the quality of the software and creating greater speed in delivery. However, a gap regarding the formalization of its adoption and implementation doubts became relevant. My hypothesis is that, by systematizing the introduction of DevOps into the software development process and defining the function of the members of the DevOps team members, may well make it quicker to implement this process, thus reducing conflicts between the teams. As part of the investigation of this hypothesis, the result of the research will be applied in practical development environments i.e. in a Technology Agency of the State of the Brazilian Government and also at the Brazilian Company Neurotech in order to evaluate its effectiveness from metrics appropriate for DevOps environments.","PeriodicalId":136929,"journal":{"name":"2021 IEEE/ACM 43rd International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127378998","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}
Pub Date : 2021-05-01DOI: 10.1109/ICSE-Companion52605.2021.00044
A. Thapaliya
In this study, I investigate the effect of programming with (without) music on electromagnetic waves in software developers' brain and analyzing how music influences the overall result of their tasks. For this research, I used an EEG device to measure the brain activity of the programmer and analyzed electromagnetic waves by calculating the arousal-valence coefficients & using pre-processing techniques (EEG studio). The experiment was performed with 8 students who were also software developers (5 undergraduates and 3 graduates). As a result, when programming with music, I discovered that the mean valence was greater while the mean arousal was lower. These early results suggest the feasibility of the technique.
{"title":"Effect on Brain Activity while Programming with (without) Music","authors":"A. Thapaliya","doi":"10.1109/ICSE-Companion52605.2021.00044","DOIUrl":"https://doi.org/10.1109/ICSE-Companion52605.2021.00044","url":null,"abstract":"In this study, I investigate the effect of programming with (without) music on electromagnetic waves in software developers' brain and analyzing how music influences the overall result of their tasks. For this research, I used an EEG device to measure the brain activity of the programmer and analyzed electromagnetic waves by calculating the arousal-valence coefficients & using pre-processing techniques (EEG studio). The experiment was performed with 8 students who were also software developers (5 undergraduates and 3 graduates). As a result, when programming with music, I discovered that the mean valence was greater while the mean arousal was lower. These early results suggest the feasibility of the technique.","PeriodicalId":136929,"journal":{"name":"2021 IEEE/ACM 43rd International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130455289","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}
Pub Date : 2021-05-01DOI: 10.1109/ICSE-Companion52605.2021.00073
Sungjae Hwang, Sungho Lee, Jihoon Kim, Sukyoung Ryu
Java Native Interface (JNI) provides a way for Java applications to access native libraries, but it is difficult to develop correct JNI programs. By leveraging native code, the JNI enables Java developers to implement efficient applications and to reuse code written in other programming languages such as C and C++. Besides, the core Java libraries already use the JNI to provide system features like a graphical user interface. As a result, many mainstream Java Virtual Machines (JVMs) support the JNI. However, due to the complex interoperation semantics between different programming languages, implementing correct JNI programs is not trivial. Moreover, because of the performance overhead, JVMs do not validate erroneous JNI interoperations by default, but they validate them only when the debug feature, the -Xcheck:jni option, is enabled. Therefore, the correctness of JNI programs highly relies on the checks by the -Xcheck:jni option of JVMs. Questions remain, however, on the quality of the checks provided by the feature. Are there any properties that the -Xcheck:jni option fails to validate? If so, what potential issues can arise due to the lack of such validation? To the best of our knowledge, no research has explored these questions in-depth. In this paper, we empirically study the validation quality and impacts of the -Xcheck:jni option on mainstream JVMs using unspecified corner cases in the JNI specification. Such unspecified cases may lead to unexpected run-time behaviors because their semantics is not defined in the specification. For a systematic study, we propose JUSTGEN, a semi-automated approach to identify unspecified cases from a specification and generate test programs. JUSTGEN receives the JNI specification written in our domain specific language (DSL), and automatically discovers unspecified cases using an SMT solver. It then generates test programs that trigger the behaviors of unspecified cases. Using the generated tests, we empirically study the validation ability of the -Xcheck:jni option. Our experimental result shows that the JNI debug feature does not validate thousands of unspecified cases on JVMs, and they can cause critical run-time errors such as violation of the Java type system and memory corruption. We reported 792 unspecified cases that are not validated by JVMs to their corresponding JVM vendors. Among them, 563 cases have been fixed and the remaining cases will be fixed in near future. Based on our empirical study, we believe that the JNI specification should specify the semantics of the missing cases clearly and the debug feature should be supported completely.
{"title":"JUSTGen: Effective Test Generation for Unspecified JNI Behaviors on JVMs","authors":"Sungjae Hwang, Sungho Lee, Jihoon Kim, Sukyoung Ryu","doi":"10.1109/ICSE-Companion52605.2021.00073","DOIUrl":"https://doi.org/10.1109/ICSE-Companion52605.2021.00073","url":null,"abstract":"Java Native Interface (JNI) provides a way for Java applications to access native libraries, but it is difficult to develop correct JNI programs. By leveraging native code, the JNI enables Java developers to implement efficient applications and to reuse code written in other programming languages such as C and C++. Besides, the core Java libraries already use the JNI to provide system features like a graphical user interface. As a result, many mainstream Java Virtual Machines (JVMs) support the JNI. However, due to the complex interoperation semantics between different programming languages, implementing correct JNI programs is not trivial. Moreover, because of the performance overhead, JVMs do not validate erroneous JNI interoperations by default, but they validate them only when the debug feature, the -Xcheck:jni option, is enabled. Therefore, the correctness of JNI programs highly relies on the checks by the -Xcheck:jni option of JVMs. Questions remain, however, on the quality of the checks provided by the feature. Are there any properties that the -Xcheck:jni option fails to validate? If so, what potential issues can arise due to the lack of such validation? To the best of our knowledge, no research has explored these questions in-depth. In this paper, we empirically study the validation quality and impacts of the -Xcheck:jni option on mainstream JVMs using unspecified corner cases in the JNI specification. Such unspecified cases may lead to unexpected run-time behaviors because their semantics is not defined in the specification. For a systematic study, we propose JUSTGEN, a semi-automated approach to identify unspecified cases from a specification and generate test programs. JUSTGEN receives the JNI specification written in our domain specific language (DSL), and automatically discovers unspecified cases using an SMT solver. It then generates test programs that trigger the behaviors of unspecified cases. Using the generated tests, we empirically study the validation ability of the -Xcheck:jni option. Our experimental result shows that the JNI debug feature does not validate thousands of unspecified cases on JVMs, and they can cause critical run-time errors such as violation of the Java type system and memory corruption. We reported 792 unspecified cases that are not validated by JVMs to their corresponding JVM vendors. Among them, 563 cases have been fixed and the remaining cases will be fixed in near future. Based on our empirical study, we believe that the JNI specification should specify the semantics of the missing cases clearly and the debug feature should be supported completely.","PeriodicalId":136929,"journal":{"name":"2021 IEEE/ACM 43rd International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124974798","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}
Pub Date : 2021-05-01DOI: 10.1109/ICSE-Companion52605.2021.00049
Jingling Sun
Android, the most popular mobile system, offers a number of app-independent, user-configurable settings (e.g., network, location and permission) for controlling the devices and the apps. However, apps may fail to properly adapt their behaviors when these settings are changed, and thus frustrate users. We name such issues as setting issues, which reside in the apps and are induced by the changes of settings. According to our investigation, the majority of setting issues are non-crash (logic) bugs, which however cannot be detected by existing automated app testing techniques due to the lack of test oracles. To this end, we designed and introduced, setting-wise metamorphic fuzzing, the first automated testing technique to overcome the oracle problem in detecting setting issues. Our key insight is that, in most cases, the app behaviors should keep consistent if a given setting is changed and later properly restored. We realized this technique as an automated GUI testing tool, SetDroid, and applied it on 26 popular, open-source Android apps. SetDroid successfully found 32 unique, previously-unknown setting issues in these apps. So far, 25 have been confirmed and 17 were already fixed. We further applied SetDroid on 4 commercial apps with billions of monthly active users and successfully detected 15 previously unknown setting issues, all of which have been confirmed and under fixing. The majority of all these bugs (37 out of 47) are non-crash bugs, which cannot be detected by any prior testing technique.
{"title":"SetDroid: Detecting User-Configurable Setting Issues of Android Apps via Metamorphic Fuzzing","authors":"Jingling Sun","doi":"10.1109/ICSE-Companion52605.2021.00049","DOIUrl":"https://doi.org/10.1109/ICSE-Companion52605.2021.00049","url":null,"abstract":"Android, the most popular mobile system, offers a number of app-independent, user-configurable settings (e.g., network, location and permission) for controlling the devices and the apps. However, apps may fail to properly adapt their behaviors when these settings are changed, and thus frustrate users. We name such issues as setting issues, which reside in the apps and are induced by the changes of settings. According to our investigation, the majority of setting issues are non-crash (logic) bugs, which however cannot be detected by existing automated app testing techniques due to the lack of test oracles. To this end, we designed and introduced, setting-wise metamorphic fuzzing, the first automated testing technique to overcome the oracle problem in detecting setting issues. Our key insight is that, in most cases, the app behaviors should keep consistent if a given setting is changed and later properly restored. We realized this technique as an automated GUI testing tool, SetDroid, and applied it on 26 popular, open-source Android apps. SetDroid successfully found 32 unique, previously-unknown setting issues in these apps. So far, 25 have been confirmed and 17 were already fixed. We further applied SetDroid on 4 commercial apps with billions of monthly active users and successfully detected 15 previously unknown setting issues, all of which have been confirmed and under fixing. The majority of all these bugs (37 out of 47) are non-crash bugs, which cannot be detected by any prior testing technique.","PeriodicalId":136929,"journal":{"name":"2021 IEEE/ACM 43rd International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125120831","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}
Pub Date : 2021-05-01DOI: 10.1109/ICSE-Companion52605.2021.00086
Gemma Catolino, Fabio Palomba, D. Tamburri, Alexander Serebrenik
In this document, we present the replication package of the paper "Understanding Community Smells Variability: A Statistical Approach" accepted at the 43rd International Conference on Software Engineering - Software Engineering in Society Track (ICSE '21).
{"title":"Understanding Community Smells Variability: A Statistical Approach: Replication Package Instructions","authors":"Gemma Catolino, Fabio Palomba, D. Tamburri, Alexander Serebrenik","doi":"10.1109/ICSE-Companion52605.2021.00086","DOIUrl":"https://doi.org/10.1109/ICSE-Companion52605.2021.00086","url":null,"abstract":"In this document, we present the replication package of the paper \"Understanding Community Smells Variability: A Statistical Approach\" accepted at the 43rd International Conference on Software Engineering - Software Engineering in Society Track (ICSE '21).","PeriodicalId":136929,"journal":{"name":"2021 IEEE/ACM 43rd International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127216105","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}
Pub Date : 2021-05-01DOI: 10.1109/ICSE-Companion52605.2021.00105
Benjamin Barslev Nielsen, Martin Toldam Torp, Anders Møller
The artifact contains the JSFIX tool along with instructions for how to replicate all of the experiments from the paper. The purpose of the artifact is to allow the the reader to check that the results presented in the paper are correct.
{"title":"Semantic Patches for Adaptation of JavaScript Programs to Evolving Libraries","authors":"Benjamin Barslev Nielsen, Martin Toldam Torp, Anders Møller","doi":"10.1109/ICSE-Companion52605.2021.00105","DOIUrl":"https://doi.org/10.1109/ICSE-Companion52605.2021.00105","url":null,"abstract":"The artifact contains the JSFIX tool along with instructions for how to replicate all of the experiments from the paper. The purpose of the artifact is to allow the the reader to check that the results presented in the paper are correct.","PeriodicalId":136929,"journal":{"name":"2021 IEEE/ACM 43rd International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125438414","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}
Pub Date : 2021-05-01DOI: 10.1109/ICSE-Companion52605.2021.00084
Hideaki Hata, R. Kula, T. Ishio, Christoph Treude
This is a research artifact for the paper “Same File, Different Changes: The Potential of Meta-Maintenance on GitHub”. This artifact is a data repository including a list of studied 32,007 repositories on GitHub, a list of targeted 401,610,677 files, the results of the qualitative analysis for RQ2, RQ3, and RQ4, the results of the quantitative analysis for RQ5, and survey material for RQ6. The purpose of this artifact is enabling researchers to replicate our mixed-methods results of the paper, and to reuse the results of our exploratory study for further software engineering research. This research artifact is available at https://github.com/NAIST-SE/MetaMaintenancePotential and https://doi.org/10.5281/zenodo.4456668.
{"title":"Research Artifact: The Potential of Meta-Maintenance on GitHub","authors":"Hideaki Hata, R. Kula, T. Ishio, Christoph Treude","doi":"10.1109/ICSE-Companion52605.2021.00084","DOIUrl":"https://doi.org/10.1109/ICSE-Companion52605.2021.00084","url":null,"abstract":"This is a research artifact for the paper “Same File, Different Changes: The Potential of Meta-Maintenance on GitHub”. This artifact is a data repository including a list of studied 32,007 repositories on GitHub, a list of targeted 401,610,677 files, the results of the qualitative analysis for RQ2, RQ3, and RQ4, the results of the quantitative analysis for RQ5, and survey material for RQ6. The purpose of this artifact is enabling researchers to replicate our mixed-methods results of the paper, and to reuse the results of our exploratory study for further software engineering research. This research artifact is available at https://github.com/NAIST-SE/MetaMaintenancePotential and https://doi.org/10.5281/zenodo.4456668.","PeriodicalId":136929,"journal":{"name":"2021 IEEE/ACM 43rd International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116770887","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}
Pub Date : 2021-05-01DOI: 10.1109/ICSE-Companion52605.2021.00137
Alessio Ferrari, Liping Zhao, Waad Alhoshan
Requirements engineering (RE) is one of the most natural language-intensive fields within the software engineering area. Therefore, several works have been developed across the years to automate the analysis of natural language artifacts that are relevant for RE, including requirements documents, but also app reviews, privacy policies, and social media content related to software products. Furthermore, the recent diffusion of game-changing natural language processing (NLP) techniques and plat-forms has also boosted the interest of RE researchers. However, a reference framework to provide a holistic understanding of the field of NLP for RE is currently missing. Based on the results of a recent systematic mapping study, and stemming from a previous ICSE tutorial by one of the authors, this technical briefing gives an overview of NLP for RE tasks, available techniques, supporting tools and NLP technologies. It is oriented to both researchers and practitioners, and will gently guide the audience towards a clearer view of how NLP can empower RE, providing pointers to representative works and specialised tools.
{"title":"NLP for Requirements Engineering: Tasks, Techniques, Tools, and Technologies","authors":"Alessio Ferrari, Liping Zhao, Waad Alhoshan","doi":"10.1109/ICSE-Companion52605.2021.00137","DOIUrl":"https://doi.org/10.1109/ICSE-Companion52605.2021.00137","url":null,"abstract":"Requirements engineering (RE) is one of the most natural language-intensive fields within the software engineering area. Therefore, several works have been developed across the years to automate the analysis of natural language artifacts that are relevant for RE, including requirements documents, but also app reviews, privacy policies, and social media content related to software products. Furthermore, the recent diffusion of game-changing natural language processing (NLP) techniques and plat-forms has also boosted the interest of RE researchers. However, a reference framework to provide a holistic understanding of the field of NLP for RE is currently missing. Based on the results of a recent systematic mapping study, and stemming from a previous ICSE tutorial by one of the authors, this technical briefing gives an overview of NLP for RE tasks, available techniques, supporting tools and NLP technologies. It is oriented to both researchers and practitioners, and will gently guide the audience towards a clearer view of how NLP can empower RE, providing pointers to representative works and specialised tools.","PeriodicalId":136929,"journal":{"name":"2021 IEEE/ACM 43rd International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127976276","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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