2017 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM)最新文献_第6页

Describing What Experimental Software Engineering Experts Do When They Design Their Experiments - A Qualitative Study 描述实验软件工程专家在设计实验时所做的事情——一项定性研究

2017 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM) Pub Date : 2017-11-09 DOI: 10.1109/ESEM.2017.63

Liliane Fonseca, C. Seaman, S. Soares

引用次数: 4

Which Version Should Be Released to App Store? App Store应该发布哪个版本?

2017 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM) Pub Date : 2017-11-09 DOI: 10.1109/ESEM.2017.46

Maleknaz Nayebi, Homayoon Farrahi, G. Ruhe

{"title":"Which Version Should Be Released to App Store?","authors":"Maleknaz Nayebi, Homayoon Farrahi, G. Ruhe","doi":"10.1109/ESEM.2017.46","DOIUrl":"https://doi.org/10.1109/ESEM.2017.46","url":null,"abstract":"Background: Several mobile app releases do not find their way to the end users. Our analysis of 11,514 releases across 917 open source mobile apps revealed that 44.3% of releases created in GitHub never shipped to the app store (market). Aims: We introduce \"marketability\" of open source mobile apps as a new release decision problem. Considering app stores as a complex system with unknown treatments, we evaluate performance of predictive models and analogical reasoning for marketability decisions. Method: We performed a survey with 22 release engineers to identify the importance of marketability release decision. We compared different classifiers to predict release marketability. For guiding the transition of not successfully marketable releases into successful ones, we used analogical reasoning. We evaluated our results both internally (over time) and externally (by developers). Results: Random forest classification performed best with F1 score of 78%. Analyzing 58 releases over time showed that, for 81% of them, analogical reasoning could correctly identify changes in the majority of release attributes. A survey with seven developers showed the usefulness of our method for supporting real world decisions. Conclusions: Marketability decisions of mobile apps can be supported by using predictive analytics and by considering and adopting similar experience from the past.","PeriodicalId":213866,"journal":{"name":"2017 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129120179","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}

引用次数: 27

On the Influence of Human Factors for Identifying Code Smells: A Multi-Trial Empirical Study 人为因素对代码气味识别的影响:多试验实证研究

2017 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM) Pub Date : 2017-11-09 DOI: 10.1109/ESEM.2017.13

R. Mello, R. Oliveira, Alessandro F. Garcia

{"title":"On the Influence of Human Factors for Identifying Code Smells: A Multi-Trial Empirical Study","authors":"R. Mello, R. Oliveira, Alessandro F. Garcia","doi":"10.1109/ESEM.2017.13","DOIUrl":"https://doi.org/10.1109/ESEM.2017.13","url":null,"abstract":"Context: Code smells are symptoms in the source code that represent poor design choices. Professional developers often perceive several types of code smells as indicators of actual design problems. However, the identification of code smells involves multiple steps that are subjective in nature, requiring the engagement of humans. Human factors are likely to play a key role in the precise identification of code smells in industrial settings. Unfortunately, there is limited knowledge about the influence of human factors on smell identification. Goal: We aim at investigating whether the precision of smell identification is influenced by three key human factors, namely reviewer's professional background, reviewer's module knowledge and collaboration of reviewers during the task. We also aim at deriving recommendations for allocating human resources to smell identification tasks. Method: We performed 19 comparisons among different subsamples from two trials of a controlled experiment conducted in the context of an empirical study on code smell identification. One trial was conducted in industrial settings while the other had involved graduate students. The diversity of the samples allowed us to analyze the influence of the three factors in isolation and in conjunction. Results: We found that (i) reviewers' collaboration significantly increases the precision of smell identification, but (ii) some professional background is required from the reviewers to reach high precision. Surprisingly, we also found that: (iii) having previous knowledge of the reviewed module does not affect the precision of reviewers with higher professional background. However, this factor was influential on successful identification of more complex smells. Conclusion: We expect that our findings are helpful to support researchers in conducting proper experimental procedures in the future. Besides, they may also be useful for supporting project managers in allocating resources for smell identification tasks.","PeriodicalId":213866,"journal":{"name":"2017 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127909874","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}

引用次数: 23

Training Data Selection for Cross-Project Defection Prediction: Which Approach Is Better? 跨项目缺陷预测的训练数据选择:哪种方法更好?

2017 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM) Pub Date : 2017-11-09 DOI: 10.1109/ESEM.2017.49

Yi Bin, Kai-Jing Zhou, Hongmin Lu, Yuming Zhou, Baowen Xu

引用次数: 22

Issues and Opportunities for Human Error-Based Requirements Inspections: An Exploratory Study 基于人为错误的需求检查的问题和机会:一项探索性研究

2017 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM) Pub Date : 2017-11-09 DOI: 10.1109/ESEM.2017.62

Vaibhav Anu, G. Walia, Wenhua Hu, Jeffrey C. Carver, Gary L. Bradshaw

引用次数: 4

An Empirical Examination of the Relationship between Code Smells and Merge Conflicts 代码气味与合并冲突关系的实证研究

2017 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM) Pub Date : 2017-11-09 DOI: 10.1109/ESEM.2017.12

Iftekhar Ahmed, Caius Brindescu, Umme Ayda Mannan, Carlos Jensen, A. Sarma

{"title":"An Empirical Examination of the Relationship between Code Smells and Merge Conflicts","authors":"Iftekhar Ahmed, Caius Brindescu, Umme Ayda Mannan, Carlos Jensen, A. Sarma","doi":"10.1109/ESEM.2017.12","DOIUrl":"https://doi.org/10.1109/ESEM.2017.12","url":null,"abstract":"Background: Merge conflicts are a common occurrence in software development. Researchers have shown the negative impact of conflicts on the resulting code quality and the development workflow. Thus far, no one has investigated the effect of bad design (code smells) on merge conflicts. Aims: We posit that entities that exhibit certain types of code smells are more likely to be involved in a merge conflict. We also postulate that code elements that are both \"smelly\" and involved in a merge conflict are associated with other undesirable effects (more likely to be buggy). Method: We mined 143 repositories from GitHub and recreated 6,979 merge conflicts to obtain metrics about code changes and conflicts. We categorized conflicts into semantic or non-semantic, based on whether changes affected the Abstract Syntax Tree. For each conflicting change, we calculate the number of code smells and the number of future bug-fixes associated with the affected lines of code. Results: We found that entities that are smelly are three times more likely to be involved in merge conflicts. Method-level code smells (Blob Operation and Internal Duplication) are highly correlated with semantic conflicts. We also found that code that is smelly and experiences merge conflicts is more likely to be buggy. Conclusion: Bad code design not only impacts maintainability, it also impacts the day to day operations of a project, such as merging contributions, and negatively impacts the quality of the resulting code. Our findings indicate that research is needed to identify better ways to support merge conflict resolution to minimize its effect on code quality.","PeriodicalId":213866,"journal":{"name":"2017 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128132371","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}

引用次数: 49

How Does Machine Translated User Interface Affect User Experience? A Study on Android Apps 机器翻译的用户界面如何影响用户体验?Android应用研究

2017 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM) Pub Date : 2017-11-09 DOI: 10.1109/ESEM.2017.58

Xue Qin, Smitha Holla, Liang Huang, Lymari Montijo, Dylan Aguirre, Xiaoyin Wang

{"title":"How Does Machine Translated User Interface Affect User Experience? A Study on Android Apps","authors":"Xue Qin, Smitha Holla, Liang Huang, Lymari Montijo, Dylan Aguirre, Xiaoyin Wang","doi":"10.1109/ESEM.2017.58","DOIUrl":"https://doi.org/10.1109/ESEM.2017.58","url":null,"abstract":"For global-market-oriented software applications, it is required that their user interface be translated to local languages so that users from different areas in the world can use the software. A long-term practice in software industry is to hire professional translators or translation companies to perform the translation. However, due to the large number of user-interface labels and target languages, this is often too expensive for software providers, especially cost-sensitive providers such as personal developers of mobile apps. As natural language processing and machine techniques advance, more mature machine translation techniques are providing a cheap though imperfect alternative, and the Google Translation service has already been widely used for translating websites and apps. However, the effect of lower translation quality on user experience has not been well studied yet. In this paper, we present a user study on 6 popular Android apps, which involves 24 participants performing tasks on app variants with 4 different translation quality levels and 2 target languages: Spanish and Chinese. From our study, we acquire the following 3 major findings, including (1) compared with original versions, machine translated versions of apps have similar task completion rate and efficiency on most studied apps; (2) machine translated versions have more tasks completed with flaws such unnecessary steps and missed optional steps, and (3) users are not satisfied with the GUI of machine translated versions and the two major complaints are misleading labels of input boxes, and unclear translation of items in option lists.","PeriodicalId":213866,"journal":{"name":"2017 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128406730","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}

引用次数: 1

Predicting the Vector Impact of Change - An Industrial Case Study at Brightsquid 预测变化的矢量影响- Brightsquid的一个工业案例研究

2017 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM) Pub Date : 2017-11-09 DOI: 10.1109/ESEM.2017.20

S. Kabeer, Maleknaz Nayebi, G. Ruhe, Chris Carlson, Francis Chew

{"title":"Predicting the Vector Impact of Change - An Industrial Case Study at Brightsquid","authors":"S. Kabeer, Maleknaz Nayebi, G. Ruhe, Chris Carlson, Francis Chew","doi":"10.1109/ESEM.2017.20","DOIUrl":"https://doi.org/10.1109/ESEM.2017.20","url":null,"abstract":"Background: Understanding and controlling the impact of change decides about the success or failure of evolving products. The problem magnifies for start-ups operating with limited resources. Their usual focus is on Minimum Viable Product (MVP's) providing specialized functionality, thus have little expense available for handling changes. Aims: Change Impact Analysis (CIA) refers to the identification of source code files impacted when implementing a change request. We extend this question to predict not only affected files, but also the effort needed for implementing the change, and the duration necessary for that. Method: This study evaluates the performance of three textual similarity techniques for CIA based on Bag of words in combination with either topic modeling or file coupling. Results: The approaches are applied on data from two industrial projects. The data comes as part of an industrial collaboration project with Brightsquid, a Canadian start-up company specializing in secure communication solutions. Performance analysis shows that combining textual similarity with file coupling improves impact prediction, resulting in Recall of 67%. Effort and duration can be predicted with 84% and 72% accuracy using textual similarity only. Conclusions: The relative effort invested into CIA for predicting impacted files can be reduced by extending its applicability to multiple dimensions which include impacted files, effort, and duration.","PeriodicalId":213866,"journal":{"name":"2017 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125396002","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}

引用次数: 9

Understanding the Heterogeneity of Contributors in Bug Bounty Programs 了解Bug赏金计划中贡献者的异质性

2017 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM) Pub Date : 2017-09-19 DOI: 10.1109/ESEM.2017.34

Hideaki Hata, M. Guo, M. Babar

引用次数: 25

Graphical vs. Tabular Notations for Risk Models: On the Role of Textual Labels and Complexity 风险模型的图形与表格符号:关于文本标签和复杂性的作用

2017 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM) Pub Date : 2017-08-22 DOI: 10.1109/ESEM.2017.40

Katsiaryna Labunets, F. Massacci, A. Tedeschi

{"title":"Graphical vs. Tabular Notations for Risk Models: On the Role of Textual Labels and Complexity","authors":"Katsiaryna Labunets, F. Massacci, A. Tedeschi","doi":"10.1109/ESEM.2017.40","DOIUrl":"https://doi.org/10.1109/ESEM.2017.40","url":null,"abstract":"[Background] Security risk assessment methods in industry mostly use a tabular notation to represent the assessment results whilst academic works advocate graphical methods. Experiments with MSc students showed that the tabular notation is better than an iconic graphical notation for the comprehension of security risks. [Aim] We investigate whether the availability of textual labels and terse UML-style notation could improve comprehensibility. [Method] We report the results of an online comprehensibility experiment involving 61 professionals with an average of 9 years of working experience, in which we compared the ability to comprehend security risk assessments represented in tabular, UML-style with textual labels, and iconic graphical modeling notations. [Results] Tabular notation are still the most comprehensible notion in both recall and precision. However, the presence of textual labels does improve the precision and recall of participants over iconic graphical models. [Conclusion] Tabular representation better supports extraction of correct information of both simple and complex comprehensibility questions about security risks than the graphical notation but textual labels help.","PeriodicalId":213866,"journal":{"name":"2017 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130539142","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}

引用次数: 7