Over the last two decades, developers' daily intake of information has been constantly on the rise and so has the interest of research in investigating the information needs of developers. Knowledge about what information they seek and which sources they rely on is scarce and has to be updated regularly to match the rapid changes in development practices. In this paper, we reflect on the scientific studies published in this field over the last two decades. We present preliminary results of our analysis of a study sample where we particularly focus on the research methods used, the number of recruited participants, and the organisational context in which they emerged. We have investigated a total of 54 studies from 41 publications and found that convenience sampling is the predominant sampling strategy with a prevalence of the industrial organisational context. Moreover, the majority of studies had a reduced sample size and draw participants from a single organisation resulting in high sample homogeneity. Among the studies carried out in industry 51.9% recruited participants from Microsoft.
{"title":"Two Decades of Empirical Research on Developers' Information Needs: A Preliminary Analysis","authors":"Abir Bouraffa, W. Maalej","doi":"10.1145/3387940.3391485","DOIUrl":"https://doi.org/10.1145/3387940.3391485","url":null,"abstract":"Over the last two decades, developers' daily intake of information has been constantly on the rise and so has the interest of research in investigating the information needs of developers. Knowledge about what information they seek and which sources they rely on is scarce and has to be updated regularly to match the rapid changes in development practices. In this paper, we reflect on the scientific studies published in this field over the last two decades. We present preliminary results of our analysis of a study sample where we particularly focus on the research methods used, the number of recruited participants, and the organisational context in which they emerged. We have investigated a total of 54 studies from 41 publications and found that convenience sampling is the predominant sampling strategy with a prevalence of the industrial organisational context. Moreover, the majority of studies had a reduced sample size and draw participants from a single organisation resulting in high sample homogeneity. Among the studies carried out in industry 51.9% recruited participants from Microsoft.","PeriodicalId":309659,"journal":{"name":"Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128705230","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}
Metamorphic testing (MT) is getting increasingly popular by exhibiting test effectiveness for a wide range of subjects, from compilers to machine learning programs. However, the central part of MT, i.e., the derivation of useful metamorphic relations (MRs), still falls behind MT's rapid applications. In this paper, we propose M.R. Hunter, an interactive online game for attracting users, especially those who are not familiar with, or even reluctant to, learning intrinsic complexities behind MT, to participate into the MR derivation process in a puzzle-solving way. The game design carefully considers how to guide users to participate actively, how to present conjectured MRs intuitively, and how to validate MRs effectively. So far, we have built and deployed a preliminary version of the game, and received active feedbacks, suggesting both promising results and useful advices for future improvement.
{"title":"M.R. Hunter: Hunting for Metamorphic Relations by Puzzle Solving","authors":"Yingzhuo Yang, Chang Xu","doi":"10.1145/3387940.3392251","DOIUrl":"https://doi.org/10.1145/3387940.3392251","url":null,"abstract":"Metamorphic testing (MT) is getting increasingly popular by exhibiting test effectiveness for a wide range of subjects, from compilers to machine learning programs. However, the central part of MT, i.e., the derivation of useful metamorphic relations (MRs), still falls behind MT's rapid applications. In this paper, we propose M.R. Hunter, an interactive online game for attracting users, especially those who are not familiar with, or even reluctant to, learning intrinsic complexities behind MT, to participate into the MR derivation process in a puzzle-solving way. The game design carefully considers how to guide users to participate actively, how to present conjectured MRs intuitively, and how to validate MRs effectively. So far, we have built and deployed a preliminary version of the game, and received active feedbacks, suggesting both promising results and useful advices for future improvement.","PeriodicalId":309659,"journal":{"name":"Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134179832","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}
The need to understand signals given by our own body is of great interest to most human beings. This quest for self-knowledge is both shared by academic researchers and businesses who want to bring value to consumers in the society. This paper presents a story of how a software engineering researcher who collaborated with hardware engineers and entrepreneurs in an incubator, Simula Garage, hosted by Simula Research Laboratory to create a wearable startup called Sweetzpot. Sweetzpot developed a respiratory inductance plethysomography sensor called Flow to measure breathing signals from ribcage and/or abdominal movements. The team grew to consist of software engineers, students of machine learning and physics, an industrial/interaction designer, a hardware engineer, a lawyer, and an accountant in addition to external collaborators. We present the sequence of events that led to creation and sustainability of the startup and summarize the lessons learnt from it.
大多数人都对理解自己身体发出的信号非常感兴趣。学术研究人员和希望为社会消费者带来价值的企业都有这种对自我认识的追求。本文介绍了一个软件工程研究人员如何与硬件工程师和企业家在Simula Research Laboratory主持的Simula Garage孵化器中合作，创建了一个名为Sweetzpot的可穿戴初创企业的故事。Sweetzpot开发了一种名为Flow的呼吸感应式胸腺肥大传感器，用于测量来自胸腔和/或腹部运动的呼吸信号。团队成员包括软件工程师、机器学习和物理学专业的学生、一名工业/交互设计师、一名硬件工程师、一名律师和一名会计师，此外还有外部合作者。我们展示了导致创业和可持续发展的一系列事件，并总结了从中吸取的教训。
{"title":"Creation of an Wearable Startup: From a Laboratory Incubator to a Revenue Generating Business","authors":"S. Sen","doi":"10.1145/3387940.3392226","DOIUrl":"https://doi.org/10.1145/3387940.3392226","url":null,"abstract":"The need to understand signals given by our own body is of great interest to most human beings. This quest for self-knowledge is both shared by academic researchers and businesses who want to bring value to consumers in the society. This paper presents a story of how a software engineering researcher who collaborated with hardware engineers and entrepreneurs in an incubator, Simula Garage, hosted by Simula Research Laboratory to create a wearable startup called Sweetzpot. Sweetzpot developed a respiratory inductance plethysomography sensor called Flow to measure breathing signals from ribcage and/or abdominal movements. The team grew to consist of software engineers, students of machine learning and physics, an industrial/interaction designer, a hardware engineer, a lawyer, and an accountant in addition to external collaborators. We present the sequence of events that led to creation and sustainability of the startup and summarize the lessons learnt from it.","PeriodicalId":309659,"journal":{"name":"Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125558149","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}
A. Bagnato, Antonin Abhervé, Silverio Martínez-Fernández, Xavier Franch
In this industry abstract, we describe the challenges and benefits of collecting feedback from customers and systems to support development cycles. In Softeam, we have performed such collection and support in four iterations by means of a software analytics platform. We describe the encountered challenges and the effects of suggested recommendations to improve the software quality of our systems on the metrics of interest.
{"title":"Challenges and Benefits from Using Software Analytics in Softeam","authors":"A. Bagnato, Antonin Abhervé, Silverio Martínez-Fernández, Xavier Franch","doi":"10.1145/3387940.3391537","DOIUrl":"https://doi.org/10.1145/3387940.3391537","url":null,"abstract":"In this industry abstract, we describe the challenges and benefits of collecting feedback from customers and systems to support development cycles. In Softeam, we have performed such collection and support in four iterations by means of a software analytics platform. We describe the encountered challenges and the effects of suggested recommendations to improve the software quality of our systems on the metrics of interest.","PeriodicalId":309659,"journal":{"name":"Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129824074","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}
Metamorphic relations (MRs) are an essential component of metamorphic testing (MT) that highly affects its fault detection effectiveness. MRs are usually identified with the help of a domain expert, which is a labor-intensive task. In this work, we explore the feasibility of a text classification-based machine learning approach to predict MRs using their program documentation as the sole input. We compare our method to our previously developed graph kernelbased machine learning approach and demonstrate that textual features extracted from program documentation are highly effective for predicting metamorphic relations for matrix calculation programs.
{"title":"MRpredT","authors":"Karishma Rahman, Indika Kahanda, Upulee Kanewala","doi":"10.1145/3387940.3392250","DOIUrl":"https://doi.org/10.1145/3387940.3392250","url":null,"abstract":"Metamorphic relations (MRs) are an essential component of metamorphic testing (MT) that highly affects its fault detection effectiveness. MRs are usually identified with the help of a domain expert, which is a labor-intensive task. In this work, we explore the feasibility of a text classification-based machine learning approach to predict MRs using their program documentation as the sole input. We compare our method to our previously developed graph kernelbased machine learning approach and demonstrate that textual features extracted from program documentation are highly effective for predicting metamorphic relations for matrix calculation programs.","PeriodicalId":309659,"journal":{"name":"Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117270283","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. Alomar, Anthony S Peruma, Christian D. Newman, Mohamed Wiem Mkaouer, Ali Ouni
Refactoring is one of the means of managing technical debt and maintaining a healthy software structure through enforcing best design practices, or coping with design defects. Previous refactoring surveys have shown that these code restructurings are mainly executed by developers who have sufficient knowledge of the system's design, and disposing of leadership roles in their development teams. However, these surveys were mainly limited to specific projects and companies. In this paper, we explore the generalizability of the previous results though analyzing 800 open-source projects. We mine their refactoring activities, and we identify their corresponding contributors. Then, we associate an expertise score to each contributor in order to test the hypothesis of whether developers with higher scores tend to perform a higher number of refactoring operations. We found that (1) although refactoring is not restricted to a subset of developers, those with higher experiences score tend to perform more refactorings than others; (2) our qualitative analysis of three randomly sampled projects show that the developers who are responsible for the majority of refactoring activities are typically on advanced positions in their development teams, demonstrating their extensive knowledge of the design of the systems they contribute to.
{"title":"On the Relationship Between Developer Experience and Refactoring: An Exploratory Study and Preliminary Results","authors":"E. Alomar, Anthony S Peruma, Christian D. Newman, Mohamed Wiem Mkaouer, Ali Ouni","doi":"10.1145/3387940.3392193","DOIUrl":"https://doi.org/10.1145/3387940.3392193","url":null,"abstract":"Refactoring is one of the means of managing technical debt and maintaining a healthy software structure through enforcing best design practices, or coping with design defects. Previous refactoring surveys have shown that these code restructurings are mainly executed by developers who have sufficient knowledge of the system's design, and disposing of leadership roles in their development teams. However, these surveys were mainly limited to specific projects and companies. In this paper, we explore the generalizability of the previous results though analyzing 800 open-source projects. We mine their refactoring activities, and we identify their corresponding contributors. Then, we associate an expertise score to each contributor in order to test the hypothesis of whether developers with higher scores tend to perform a higher number of refactoring operations. We found that (1) although refactoring is not restricted to a subset of developers, those with higher experiences score tend to perform more refactorings than others; (2) our qualitative analysis of three randomly sampled projects show that the developers who are responsible for the majority of refactoring activities are typically on advanced positions in their development teams, demonstrating their extensive knowledge of the design of the systems they contribute to.","PeriodicalId":309659,"journal":{"name":"Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115895247","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}
The new European Payments Service Directive (Directive (EU) 2015/2366) introduces a novelty for users of online accounts: the possibility of accessing their own bank statements or making payment transactions directly through software created by Third Party Providers. The new players authorized by the directive represent the real novelty with respect to the previous one (Directive 2007/64/CE), and introduce for the first time a strong risk of disintegration between the Bank and its customers. New authorized parties include the Account Servicing Payment Service Provider, the Payment Initiation Service Provider and the Account Information Service Provider. This new mechanism for accessing information on personal bank statements or for the payment will stimulate a remodeling of the offers for customers. In this work a first attempt to implement a service of account information and a service of account storing through a blockchain oriented software application is presented.
{"title":"A Blockchain Oriented Software Application in the Revised Payments Service Directive context","authors":"L. Cocco, A. Pinna, Giacomo Meloni","doi":"10.1145/3387940.3391498","DOIUrl":"https://doi.org/10.1145/3387940.3391498","url":null,"abstract":"The new European Payments Service Directive (Directive (EU) 2015/2366) introduces a novelty for users of online accounts: the possibility of accessing their own bank statements or making payment transactions directly through software created by Third Party Providers. The new players authorized by the directive represent the real novelty with respect to the previous one (Directive 2007/64/CE), and introduce for the first time a strong risk of disintegration between the Bank and its customers. New authorized parties include the Account Servicing Payment Service Provider, the Payment Initiation Service Provider and the Account Information Service Provider. This new mechanism for accessing information on personal bank statements or for the payment will stimulate a remodeling of the offers for customers. In this work a first attempt to implement a service of account information and a service of account storing through a blockchain oriented software application is presented.","PeriodicalId":309659,"journal":{"name":"Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130897062","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}
Bug reports can be lengthy due to long descriptions and long conversation threads. Automatic summarization of the text in a bug report can reduce the time spent by software project members on understanding the content of a bug report. Quality of the bug report summaries have been historically evaluated using human-created gold-standard summaries. However, we believe this is not a good practice for two reasons. First, we observed high disagreement levels in the annotated summaries and the number of annotators to create gold-standard summaries was lower than the established value for stable annotation. We believe that creating a fixed summary length of 25% of the word count of the corresponding bug report is not suitable for every time when a person refers to a bug report. Therefore, we propose an automatic sentence annotation method and an interface to customize the presented summary.
{"title":"Are Automatic Bug Report Summarizers Missing the Target?","authors":"J. Anvik, Akalanka Galappaththi","doi":"10.1145/3387940.3392236","DOIUrl":"https://doi.org/10.1145/3387940.3392236","url":null,"abstract":"Bug reports can be lengthy due to long descriptions and long conversation threads. Automatic summarization of the text in a bug report can reduce the time spent by software project members on understanding the content of a bug report. Quality of the bug report summaries have been historically evaluated using human-created gold-standard summaries. However, we believe this is not a good practice for two reasons. First, we observed high disagreement levels in the annotated summaries and the number of annotators to create gold-standard summaries was lower than the established value for stable annotation. We believe that creating a fixed summary length of 25% of the word count of the corresponding bug report is not suitable for every time when a person refers to a bug report. Therefore, we propose an automatic sentence annotation method and an interface to customize the presented summary.","PeriodicalId":309659,"journal":{"name":"Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131405466","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}
This paper considers sensemaking as it relates to everyday software engineering (SE) work practices and draws on a multi-year ethnographic study of SE projects at a large, global technology company building digital services infused with artificial intelligence (AI) and machine learning (ML) capabilities. Our findings highlight the breadth of sensemaking practices in AI/ML projects, noting developers' efforts to make sense of AI/ML environments (e.g., algorithms/methods and libraries), of AI/ML model ecosystems (e.g., pre-trained models and "upstream" models), and of business-AI relations (e.g., how the AI/ML service relates to the domain context and business problem at hand). This paper builds on recent scholarship drawing attention to the integral role of sensemaking in everyday SE practices by empirically investigating how and in what ways AI/ML projects present software teams with emergent sensemaking requirements and opportunities.
{"title":"Sensemaking Practices in the Everyday Work of AI/ML Software Engineering","authors":"Christine T. Wolf, Drew Paine","doi":"10.1145/3387940.3391496","DOIUrl":"https://doi.org/10.1145/3387940.3391496","url":null,"abstract":"This paper considers sensemaking as it relates to everyday software engineering (SE) work practices and draws on a multi-year ethnographic study of SE projects at a large, global technology company building digital services infused with artificial intelligence (AI) and machine learning (ML) capabilities. Our findings highlight the breadth of sensemaking practices in AI/ML projects, noting developers' efforts to make sense of AI/ML environments (e.g., algorithms/methods and libraries), of AI/ML model ecosystems (e.g., pre-trained models and \"upstream\" models), and of business-AI relations (e.g., how the AI/ML service relates to the domain context and business problem at hand). This paper builds on recent scholarship drawing attention to the integral role of sensemaking in everyday SE practices by empirically investigating how and in what ways AI/ML projects present software teams with emergent sensemaking requirements and opportunities.","PeriodicalId":309659,"journal":{"name":"Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121506521","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}
A hardware/software co-design for AI accelerators such as Neural Processing Unit (NPU) is essential not only to support the required functionality but also to meet primary goals of improved performance and power efficiency. However, their ever-changing requirements often introduce undesirable development costs. Indeed, it is quite challenging for developers from different backgrounds to efficiently work together to construct a full HW/SW stack to develop AI accelerators. This paper addresses these challenges, and proposes a centralized collaboration methodology for efficient full-stack development, especially targeting NPU HW. The proposal is inspired based on the observations from our experiences, presented later as a case study. As not all of the involved developers have enough knowledge of software engineering, this approach suggests making a central development group (e.g., runtime system software) have a higher priority to organize and devise common interfaces including APIs for each layer in the full-stack. This aims to minimize unnecessary discussions between development groups and hide any minor updates introduced with each new design, reducing the overall development costs and improving the quality of products. More importantly, each development group can focus on their work as much as possible with this approach.
{"title":"Centralized Generic Interfaces in Hardware/Software Co-design for AI Accelerators","authors":"Dongju Chae, Parichay Kapoor","doi":"10.1145/3387940.3392225","DOIUrl":"https://doi.org/10.1145/3387940.3392225","url":null,"abstract":"A hardware/software co-design for AI accelerators such as Neural Processing Unit (NPU) is essential not only to support the required functionality but also to meet primary goals of improved performance and power efficiency. However, their ever-changing requirements often introduce undesirable development costs. Indeed, it is quite challenging for developers from different backgrounds to efficiently work together to construct a full HW/SW stack to develop AI accelerators. This paper addresses these challenges, and proposes a centralized collaboration methodology for efficient full-stack development, especially targeting NPU HW. The proposal is inspired based on the observations from our experiences, presented later as a case study. As not all of the involved developers have enough knowledge of software engineering, this approach suggests making a central development group (e.g., runtime system software) have a higher priority to organize and devise common interfaces including APIs for each layer in the full-stack. This aims to minimize unnecessary discussions between development groups and hide any minor updates introduced with each new design, reducing the overall development costs and improving the quality of products. More importantly, each development group can focus on their work as much as possible with this approach.","PeriodicalId":309659,"journal":{"name":"Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115120187","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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