Context: Most widely used cost models use source lines of code (SLOC) as the software size input measure, due to its quantifiability and high correlation with effort. Estimating the SLOC of a project is very difficult in early stages of the software lifecycle, especially for software maintenance tasks. Depending on the reuse model being used, one would need to size the existing code that needs modifications and the size of the changes being made in SLOC. Functional size measures, such as Function Points (FPs) and the Software Non-functional Assessment Process (SNAP), have been developed to improve the ability to estimate project size early in the lifecycle for both development and maintenance projects. While FPs represent software size by functions; SNAP complements FPs by sizing non-functional requirements, such as data operations and interface design. Goal: SNAP complements Function Points by sizing non-functional requirements, such as data operations and interface design. Through an empirical analysis, the authors want to determine whether SNAP might be an effective software size measure individually or in conjunction with FPs to improve effort estimation accuracy. Method: The empirical analysis will be run on Unified Code Count (UCC)'s dataset, a software tool maintained by University of Southern California (USC). Results: The analyses found that separating projects adding new functions from those modifying existing functions resulted in improved estimation models using SNAP. The effort estimation model for projects modifying functions in UCC had high prediction accuracy statistics, but less impressive results for projects adding existing functions to UCC. The effort estimation accuracy were satisfactory when using SNAP in conjunction with FPs for both groups of projects. Conclusions: SNAP, indeed, complements FPs in terms of the requirements that are considered and sized. Both size metrics should be treated as individual metrics, but can be used together for acceptably accurate cost models in UCC's development environment.
{"title":"Using Software Non-Functional Assessment Process to Complement Function Points for Software Maintenance","authors":"Anandi Hira, B. Boehm","doi":"10.1145/2961111.2962615","DOIUrl":"https://doi.org/10.1145/2961111.2962615","url":null,"abstract":"Context: Most widely used cost models use source lines of code (SLOC) as the software size input measure, due to its quantifiability and high correlation with effort. Estimating the SLOC of a project is very difficult in early stages of the software lifecycle, especially for software maintenance tasks. Depending on the reuse model being used, one would need to size the existing code that needs modifications and the size of the changes being made in SLOC. Functional size measures, such as Function Points (FPs) and the Software Non-functional Assessment Process (SNAP), have been developed to improve the ability to estimate project size early in the lifecycle for both development and maintenance projects. While FPs represent software size by functions; SNAP complements FPs by sizing non-functional requirements, such as data operations and interface design. Goal: SNAP complements Function Points by sizing non-functional requirements, such as data operations and interface design. Through an empirical analysis, the authors want to determine whether SNAP might be an effective software size measure individually or in conjunction with FPs to improve effort estimation accuracy. Method: The empirical analysis will be run on Unified Code Count (UCC)'s dataset, a software tool maintained by University of Southern California (USC). Results: The analyses found that separating projects adding new functions from those modifying existing functions resulted in improved estimation models using SNAP. The effort estimation model for projects modifying functions in UCC had high prediction accuracy statistics, but less impressive results for projects adding existing functions to UCC. The effort estimation accuracy were satisfactory when using SNAP in conjunction with FPs for both groups of projects. Conclusions: SNAP, indeed, complements FPs in terms of the requirements that are considered and sized. Both size metrics should be treated as individual metrics, but can be used together for acceptably accurate cost models in UCC's development environment.","PeriodicalId":208212,"journal":{"name":"Proceedings of the 10th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116630737","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}
Managers need to decide on how they will configure their virtual teams each time a new project starts. So questions such as 'Which countries should be involved in the project?' and 'How large should the team size be?' need to be answered before hand. Project configurations are known to affect communication, coordination and collaboration aspects of a project, and as a consequence, its performance. Therefore, a challenge managers face is knowing which configurations promote better project outcomes when working with virtual software teams. This article reveals a set of configurations that have promoted the quality of software products developed by virtual teams to support the business of a Fortune 500 large IT multinational company. These configurations can be used as a guideline by managers to set up their own virtual teams. Recommendations on how to set up virtual teams based on the study are then suggested.
{"title":"Virtual Team Configurations that Promote Better Product Quality","authors":"R. Prikladnicki, M. G. Perin, S. Marczak","doi":"10.1145/2961111.2962638","DOIUrl":"https://doi.org/10.1145/2961111.2962638","url":null,"abstract":"Managers need to decide on how they will configure their virtual teams each time a new project starts. So questions such as 'Which countries should be involved in the project?' and 'How large should the team size be?' need to be answered before hand. Project configurations are known to affect communication, coordination and collaboration aspects of a project, and as a consequence, its performance. Therefore, a challenge managers face is knowing which configurations promote better project outcomes when working with virtual software teams. This article reveals a set of configurations that have promoted the quality of software products developed by virtual teams to support the business of a Fortune 500 large IT multinational company. These configurations can be used as a guideline by managers to set up their own virtual teams. Recommendations on how to set up virtual teams based on the study are then suggested.","PeriodicalId":208212,"journal":{"name":"Proceedings of the 10th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement","volume":"352 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122844863","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}
Cleviton V. F. Monteiro, F. Silva, Luiz Fernando Capretz
Context: In the workplace, some individuals engage in the voluntary and intentional generation, promotion, and realization of new ideas for the benefit of individual performance, group effectiveness, or the organization. The literature classifies this phenomenon as innovative behaviour. Despite its importance to the development of innovation, innovative behaviour has not been fully investigated in software engineering. Objective: To understand the factors that support or inhibit innovative behaviour in software engineering practice. Method: We conducted a pilot case study in a Canadian software company using interviews and observations as data collection techniques. Using qualitative analysis, we identified relevant factors and relationships not addressed by studies from other areas. Results: Individual innovative behaviour is influenced by individual attitudes and also by situational factors such as relationships in the workplace, organizational characteristics, and project type. We built a model to express the interacting effects of these factors. Conclusions: Innovative behaviour is dependent on individual and contextual factors. Our results contribute to relevant impacts on research and practice, and to topics that deserve further study.
{"title":"The Innovative Behaviour of Software Engineers: Findings from a Pilot Case Study","authors":"Cleviton V. F. Monteiro, F. Silva, Luiz Fernando Capretz","doi":"10.1145/2961111.2962589","DOIUrl":"https://doi.org/10.1145/2961111.2962589","url":null,"abstract":"Context: In the workplace, some individuals engage in the voluntary and intentional generation, promotion, and realization of new ideas for the benefit of individual performance, group effectiveness, or the organization. The literature classifies this phenomenon as innovative behaviour. Despite its importance to the development of innovation, innovative behaviour has not been fully investigated in software engineering. Objective: To understand the factors that support or inhibit innovative behaviour in software engineering practice. Method: We conducted a pilot case study in a Canadian software company using interviews and observations as data collection techniques. Using qualitative analysis, we identified relevant factors and relationships not addressed by studies from other areas. Results: Individual innovative behaviour is influenced by individual attitudes and also by situational factors such as relationships in the workplace, organizational characteristics, and project type. We built a model to express the interacting effects of these factors. Conclusions: Innovative behaviour is dependent on individual and contextual factors. Our results contribute to relevant impacts on research and practice, and to topics that deserve further study.","PeriodicalId":208212,"journal":{"name":"Proceedings of the 10th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129614638","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}
Context -- Developers' productivity plays an important role in software development organizations; however, in many cases the management of such human capital is mainly based on how project managers perceive productivity. Therefore, it is important to investigate what these perceptions are in practice. Goal -- This study's main goal is to understand project managers' perception regarding developers' productivity. Method -- We employed a qualitative research methodology using semi-structured interviews for data collection. We interviewed 12 managers from three software development organizations in the city of Manaus (Brazil). Results -- We identified that the managers' perceptions about developers' productivity are influenced by four different factors: (1) tasks delivered on time, (2) produced artifacts that do not need rework, (3) products that meet stakeholders' expectations, and (4) personal behavior such as focus and proactivity. Conclusions -- This qualitative study shows a perception of developers' productivity different from that presented in other research papers, and suggests that human factors play an important role in managers' perceptions about productivity. Future work will investigate how these perceptions concretely influence developers' productivity, and how they relate to the existing developers' productivity factors in the literature.
{"title":"Software Project Managers' Perceptions of Productivity Factors: Findings from a Qualitative Study","authors":"E. Oliveira, T. Conte, Marco Cristo, E. Mendes","doi":"10.1145/2961111.2962626","DOIUrl":"https://doi.org/10.1145/2961111.2962626","url":null,"abstract":"Context -- Developers' productivity plays an important role in software development organizations; however, in many cases the management of such human capital is mainly based on how project managers perceive productivity. Therefore, it is important to investigate what these perceptions are in practice. Goal -- This study's main goal is to understand project managers' perception regarding developers' productivity. Method -- We employed a qualitative research methodology using semi-structured interviews for data collection. We interviewed 12 managers from three software development organizations in the city of Manaus (Brazil). Results -- We identified that the managers' perceptions about developers' productivity are influenced by four different factors: (1) tasks delivered on time, (2) produced artifacts that do not need rework, (3) products that meet stakeholders' expectations, and (4) personal behavior such as focus and proactivity. Conclusions -- This qualitative study shows a perception of developers' productivity different from that presented in other research papers, and suggests that human factors play an important role in managers' perceptions about productivity. Future work will investigate how these perceptions concretely influence developers' productivity, and how they relate to the existing developers' productivity factors in the literature.","PeriodicalId":208212,"journal":{"name":"Proceedings of the 10th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128466168","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}
Context: Previously, we have defined the notion of diagram size and studied its impact on the understanding of UML diagrams. Subsequently, questions have been raised regarding the reliability and generality of our findings. Also, new questions arose regarding how the quality of diagrams could be defined, and how it interacts with diagram size. Goal: We pursue three goals. First, we want to increase the validity of our research by analyzing a substantially larger data set than before. Second, we broaden the generalizability of our results by including two more diagram types. Our main contribution, though, is our third goal of extending our analysis aspects of diagram quality. Method: We improve our definition of diagram size and add a (provisional) definition of diagram quality as the number of topographic layout flaws. We apply these metrics on 60 diagrams of the five most commonly used types of UML diagram. We carefully analyze the structure of our diagram samples to ensure representativeness. We correlate diagram size and layout quality with modeler performance data obtained in previous experiments. The data set is the largest of its kind (n - 156). Results: We replicate earlier findings, and extend them to two new diagram types. We provide an improved definition of diagram size, and provide a definition of topographic layout quality, which is one more step towards a comprehensive definition of diagram quality as such. Both metrics are shown to be objectively applicable. We quantify the impact of diagram size and quality on diagram understanding. Conclusions: The overall results of previous studies are confirmed, while our previous recommendations for creating better diagrams are revised and refined.
{"title":"Diagram Size vs. Layout Flaws: Understanding Quality Factors of UML Diagrams","authors":"H. Störrle","doi":"10.1145/2961111.2962609","DOIUrl":"https://doi.org/10.1145/2961111.2962609","url":null,"abstract":"Context: Previously, we have defined the notion of diagram size and studied its impact on the understanding of UML diagrams. Subsequently, questions have been raised regarding the reliability and generality of our findings. Also, new questions arose regarding how the quality of diagrams could be defined, and how it interacts with diagram size. Goal: We pursue three goals. First, we want to increase the validity of our research by analyzing a substantially larger data set than before. Second, we broaden the generalizability of our results by including two more diagram types. Our main contribution, though, is our third goal of extending our analysis aspects of diagram quality. Method: We improve our definition of diagram size and add a (provisional) definition of diagram quality as the number of topographic layout flaws. We apply these metrics on 60 diagrams of the five most commonly used types of UML diagram. We carefully analyze the structure of our diagram samples to ensure representativeness. We correlate diagram size and layout quality with modeler performance data obtained in previous experiments. The data set is the largest of its kind (n - 156). Results: We replicate earlier findings, and extend them to two new diagram types. We provide an improved definition of diagram size, and provide a definition of topographic layout quality, which is one more step towards a comprehensive definition of diagram quality as such. Both metrics are shown to be objectively applicable. We quantify the impact of diagram size and quality on diagram understanding. Conclusions: The overall results of previous studies are confirmed, while our previous recommendations for creating better diagrams are revised and refined.","PeriodicalId":208212,"journal":{"name":"Proceedings of the 10th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129684289","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}
E. Knauss, Patrizio Pelliccione, Rogardt Heldal, Magnus Ågren, S. Hellman, Daniel Maniette
The practice of Continuous Integration (CI) has a big impact on how software is developed today. Shortening integration and feedback cycles promises to increase software quality, feature throughput, and customer satisfaction. Thus, it is not a surprise that companies try to embrace CI in domains where it is rather difficult to implement. In this paper we present our findings from two rounds of interviews with a car manufacturer on the use of tools in system engineering and how these tools would support wider adoption of CL Our findings suggest a complex tool landscape with immense requirements that are not easily fulfilled by existing tools; this holds also for tools that well support CI in other domains. From this notion, we further explore what makes the automotive domain challenging when it comes to CI (namely complexity of system and value chain). We hope that our findings will help address such challenges.
{"title":"Continuous Integration Beyond the Team: A Tooling Perspective on Challenges in the Automotive Industry","authors":"E. Knauss, Patrizio Pelliccione, Rogardt Heldal, Magnus Ågren, S. Hellman, Daniel Maniette","doi":"10.1145/2961111.2962639","DOIUrl":"https://doi.org/10.1145/2961111.2962639","url":null,"abstract":"The practice of Continuous Integration (CI) has a big impact on how software is developed today. Shortening integration and feedback cycles promises to increase software quality, feature throughput, and customer satisfaction. Thus, it is not a surprise that companies try to embrace CI in domains where it is rather difficult to implement. In this paper we present our findings from two rounds of interviews with a car manufacturer on the use of tools in system engineering and how these tools would support wider adoption of CL Our findings suggest a complex tool landscape with immense requirements that are not easily fulfilled by existing tools; this holds also for tools that well support CI in other domains. From this notion, we further explore what makes the automotive domain challenging when it comes to CI (namely complexity of system and value chain). We hope that our findings will help address such challenges.","PeriodicalId":208212,"journal":{"name":"Proceedings of the 10th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129692394","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}
Bruno Cartaxo, G. Pinto, Elton R. Vieira, S. Soares
Context: Integrate research evidence with practice is one of the main goals of evidence-based software engineering. However, recent studies show that the connection between systematic reviews and practitioners has not fully established. Goal: This paper presents the first steps towards a medium to transfer knowledge acquired from systematic reviews to practitioners. Method: We selected a set of systematic reviews identified by a tertiary study and extracted their findings to generate one-page Evidence Briefings to serve as mediums. A design specialist defined the briefings structure based on information design and gestalt principles. To evaluate the format and content of the briefings we conducted personal opinion surveys based on two groups: StackExchange users that posted questions in topics related to the reviews, and the authors of the selected reviews themselves. The former had a response rate of 21.9% (32 out 146) and the latter 31.8% (7 out of 22). Results: Practitioners rarely use systematic review research papers as mediums to acquire knowledge, since just 9% have told to do so. Both researchers and practitioners positively evaluated the evidence briefings, since 71% and 82% of the StackExchange users and systematic review authors, respectively, agreed or strongly agreed that the briefings' interface is clear. Conclusions: Researchers and practitioners were positive about the content and format of the evidence briefings we proposed. It is also possible to say that there is a gap between practitioners and systematic reviews due to the low percentage of practitioners that consume systematic reviews. The good reception of the evidence briefings from both sides show a possible route to reduce that gap.
{"title":"Evidence Briefings: Towards a Medium to Transfer Knowledge from Systematic Reviews to Practitioners","authors":"Bruno Cartaxo, G. Pinto, Elton R. Vieira, S. Soares","doi":"10.1145/2961111.2962603","DOIUrl":"https://doi.org/10.1145/2961111.2962603","url":null,"abstract":"Context: Integrate research evidence with practice is one of the main goals of evidence-based software engineering. However, recent studies show that the connection between systematic reviews and practitioners has not fully established. Goal: This paper presents the first steps towards a medium to transfer knowledge acquired from systematic reviews to practitioners. Method: We selected a set of systematic reviews identified by a tertiary study and extracted their findings to generate one-page Evidence Briefings to serve as mediums. A design specialist defined the briefings structure based on information design and gestalt principles. To evaluate the format and content of the briefings we conducted personal opinion surveys based on two groups: StackExchange users that posted questions in topics related to the reviews, and the authors of the selected reviews themselves. The former had a response rate of 21.9% (32 out 146) and the latter 31.8% (7 out of 22). Results: Practitioners rarely use systematic review research papers as mediums to acquire knowledge, since just 9% have told to do so. Both researchers and practitioners positively evaluated the evidence briefings, since 71% and 82% of the StackExchange users and systematic review authors, respectively, agreed or strongly agreed that the briefings' interface is clear. Conclusions: Researchers and practitioners were positive about the content and format of the evidence briefings we proposed. It is also possible to say that there is a gap between practitioners and systematic reviews due to the low percentage of practitioners that consume systematic reviews. The good reception of the evidence briefings from both sides show a possible route to reduce that gap.","PeriodicalId":208212,"journal":{"name":"Proceedings of the 10th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114077100","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}
Context: Software code review, as an engineering best practice, refers to the inspection of the code change in order to find possible defects and ensure change quality. Code reviews, however, may not guarantee finding the defects. Thus, there is a risk for a defective code change in a given patch, to pass the review process and be submitted. Goal: In this research, we aim to apply different machine learning algorithms in order to predict the defectiveness of a patch after being reviewed, at the time of its submission. Method: We built three models using three different machine learning algorithms: Logistic Regression, NaÃŕve Bayes, and Bayesian Network model. To build the models, we consider different factors involved in review process in terms of Product, Process and People (3P). Results: Our empirical results show that, Bayesian Networks is able to better predict the defectiveness of the changed code with 76% accuracy. Conclusions: Predicting defectiveness of change code is beneficial in making patch release decisions. The Bayesian Network model outperforms the others since it capturs the relationship among the factors in the review process.
{"title":"Predicting Defectiveness of Software Patches","authors":"Behjat Soltanifar, Atakan Erdem, A. Bener","doi":"10.1145/2961111.2962601","DOIUrl":"https://doi.org/10.1145/2961111.2962601","url":null,"abstract":"Context: Software code review, as an engineering best practice, refers to the inspection of the code change in order to find possible defects and ensure change quality. Code reviews, however, may not guarantee finding the defects. Thus, there is a risk for a defective code change in a given patch, to pass the review process and be submitted. Goal: In this research, we aim to apply different machine learning algorithms in order to predict the defectiveness of a patch after being reviewed, at the time of its submission. Method: We built three models using three different machine learning algorithms: Logistic Regression, NaÃŕve Bayes, and Bayesian Network model. To build the models, we consider different factors involved in review process in terms of Product, Process and People (3P). Results: Our empirical results show that, Bayesian Networks is able to better predict the defectiveness of the changed code with 76% accuracy. Conclusions: Predicting defectiveness of change code is beneficial in making patch release decisions. The Bayesian Network model outperforms the others since it capturs the relationship among the factors in the review process.","PeriodicalId":208212,"journal":{"name":"Proceedings of the 10th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126431756","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}
J. Vara, Beatriz Marín, Giovanni Giachetti, Clara Ayora
Context. Many critical systems must meet safety compliance needs from safety standards. These standards are usually large textual documents whose compliance needs can be hard to understand. As a solution, the use of models has been proposed. Goal. We aim to provide evidence of the extent to which models improve the understanding of safety compliance needs. Method. We designed an experiment and ran a pilot to study the effectiveness, efficiency, and perceived benefits of understanding these needs, with the text of standards and with models in the form of UML object diagrams. Results. The overall results from 15 Bachelor students show that the effectiveness of understanding safety compliance needs increases very little with models (2%), and the efficiency even decreases (24%). Nonetheless, the results improve when the potential complexity in navigating the models is taken into account (15% effectiveness increase). The students find benefits in using the models but most consider that the models are hard to understand. Conclusions. The extent to which models improve the understanding of safety compliance needs seems to be lower than what the research community expects. New studies are necessary to confirm our initial insights.
{"title":"Do Models Improve the Understanding of Safety Compliance Needs?: Insights from a Pilot Experiment","authors":"J. Vara, Beatriz Marín, Giovanni Giachetti, Clara Ayora","doi":"10.1145/2961111.2962621","DOIUrl":"https://doi.org/10.1145/2961111.2962621","url":null,"abstract":"Context. Many critical systems must meet safety compliance needs from safety standards. These standards are usually large textual documents whose compliance needs can be hard to understand. As a solution, the use of models has been proposed. Goal. We aim to provide evidence of the extent to which models improve the understanding of safety compliance needs. Method. We designed an experiment and ran a pilot to study the effectiveness, efficiency, and perceived benefits of understanding these needs, with the text of standards and with models in the form of UML object diagrams. Results. The overall results from 15 Bachelor students show that the effectiveness of understanding safety compliance needs increases very little with models (2%), and the efficiency even decreases (24%). Nonetheless, the results improve when the potential complexity in navigating the models is taken into account (15% effectiveness increase). The students find benefits in using the models but most consider that the models are hard to understand. Conclusions. The extent to which models improve the understanding of safety compliance needs seems to be lower than what the research community expects. New studies are necessary to confirm our initial insights.","PeriodicalId":208212,"journal":{"name":"Proceedings of the 10th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement","volume":"117 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134009470","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}
Context: Recently, more and more developer communities are abandoning their legacy support forums, moving onto Stack Overflow. The motivations are diverse, yet they typically include achieving faster response time and larger visibility through the access to a modern and very successful infrastructure. One downside of migration, however, is that the history and the crowdsourced knowledge hosted at previous sites remain separated or even get lost if a community decides to abandon completely the legacy developer forum. Goal: Adding to the body of evidence of existing research on best-answer prediction, here we show that, from a technical perspective, the content from existing developer forums might be automatically migrated to the Stack Overflow, although most of forums do not allow to mark a question as resolved, a distinctive feature of modern Q&A sites. Method: We trained a binary classifier with data from Stack Overflow and then tested it with data scraped from Docusign, a developer forum that has recently completed the move. Results: Our findings show that best answers can be predicted with a good accuracy, only relying on shallow linguistic (text) features, such as answer length and the number of sentences, combined with other features like answer upvotes and age, which can be easily computed in near real-time. Conclusions: Results provide an initial yet positive evidence towards the automatic migration of crowdsourced knowledge from legacy forums to modern Q&A sites.
{"title":"Moving to Stack Overflow: Best-Answer Prediction in Legacy Developer Forums","authors":"Fabio Calefato, F. Lanubile, Nicole Novielli","doi":"10.1145/2961111.2962585","DOIUrl":"https://doi.org/10.1145/2961111.2962585","url":null,"abstract":"Context: Recently, more and more developer communities are abandoning their legacy support forums, moving onto Stack Overflow. The motivations are diverse, yet they typically include achieving faster response time and larger visibility through the access to a modern and very successful infrastructure. One downside of migration, however, is that the history and the crowdsourced knowledge hosted at previous sites remain separated or even get lost if a community decides to abandon completely the legacy developer forum. Goal: Adding to the body of evidence of existing research on best-answer prediction, here we show that, from a technical perspective, the content from existing developer forums might be automatically migrated to the Stack Overflow, although most of forums do not allow to mark a question as resolved, a distinctive feature of modern Q&A sites. Method: We trained a binary classifier with data from Stack Overflow and then tested it with data scraped from Docusign, a developer forum that has recently completed the move. Results: Our findings show that best answers can be predicted with a good accuracy, only relying on shallow linguistic (text) features, such as answer length and the number of sentences, combined with other features like answer upvotes and age, which can be easily computed in near real-time. Conclusions: Results provide an initial yet positive evidence towards the automatic migration of crowdsourced knowledge from legacy forums to modern Q&A sites.","PeriodicalId":208212,"journal":{"name":"Proceedings of the 10th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement","volume":"312 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132795253","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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