2017 IEEE/ACM 39th International Conference on Software Engineering (ICSE)最新文献_第3页

Automated Refactoring of Legacy Java Software to Default Methods 遗留Java软件到默认方法的自动重构

2017 IEEE/ACM 39th International Conference on Software Engineering (ICSE) Pub Date : 2017-05-20 DOI: 10.1109/ICSE.2017.16

Raffi Khatchadourian, H. Masuhara

{"title":"Automated Refactoring of Legacy Java Software to Default Methods","authors":"Raffi Khatchadourian, H. Masuhara","doi":"10.1109/ICSE.2017.16","DOIUrl":"https://doi.org/10.1109/ICSE.2017.16","url":null,"abstract":"Java 8 default methods, which allow interfaces to contain (instance) method implementations, are useful for the skeletal implementation software design pattern. However, it is not easy to transform existing software to exploit default methods as it requires analyzing complex type hierarchies, resolving multiple implementation inheritance issues, reconciling differences between class and interface methods, and analyzing tie-breakers (dispatch precedence) with overriding class methods to preserve type-correctness and confirm semantics preservation. In this paper, we present an efficient, fully-automated, type constraint-based refactoring approach that assists developers in taking advantage of enhanced interfaces for their legacy Java software. The approach features an extensive rule set that covers various corner-cases where default methods cannot be used. To demonstrate applicability, we implemented our approach as an Eclipse plug-in and applied it to 19 real-world Java projects, as well as submitted pull requests to popular GitHub repositories. The indication is that it is useful in migrating skeletal implementation methods to interfaces as default methods, sheds light onto the pattern's usage, and provides insight to language designers on how this new construct applies to existing software.","PeriodicalId":6505,"journal":{"name":"2017 IEEE/ACM 39th International Conference on Software Engineering (ICSE)","volume":"16 10 1","pages":"82-93"},"PeriodicalIF":0.0,"publicationDate":"2017-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83497206","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: 15

PEoPL: Projectional Editing of Product Lines 人物:产品线投影编辑

2017 IEEE/ACM 39th International Conference on Software Engineering (ICSE) Pub Date : 2017-05-20 DOI: 10.1109/ICSE.2017.58

B. Behringer, Jochen Palz, T. Berger

{"title":"PEoPL: Projectional Editing of Product Lines","authors":"B. Behringer, Jochen Palz, T. Berger","doi":"10.1109/ICSE.2017.58","DOIUrl":"https://doi.org/10.1109/ICSE.2017.58","url":null,"abstract":"The features of a software product line—a portfolio of system variants—can be realized using various implementation techniques (a. k. a., variability mechanisms). Each technique represents the software artifacts of features differently, typically classified into annotative (e.g., C preprocessor) and modular representations (e.g., feature modules), each with distinct advantages and disadvantages. Annotative representations are easy to realize, but annotations clutter source code and hinder program comprehension. Modular representations support comprehension, but are difficult to realize. Most importantly, to engineer feature artifacts, developers need to choose one representation and adhere to it for evolving and maintaining the same artifacts. We present PEoPL, an approach to combine the advantages of annotative and modular representations. When engineering a feature artifact, developers can choose the most-suited representation and even use different representations in parallel. PEoPL relies on separating a product line into an internal and external representation, the latter by providing editable projections used by the developers. We contribute a programming-language-independent internal representation of variability, five editable projections reflecting different variability representations, a supporting IDE, and a tailoring of PEoPL to Java. We evaluate PEoPL's expressiveness, scalability, and flexibility in eight Java-based product lines, finding that all can be realized, that projections are feasible, and that variant computation is fast (","PeriodicalId":6505,"journal":{"name":"2017 IEEE/ACM 39th International Conference on Software Engineering (ICSE)","volume":"20 1","pages":"563-574"},"PeriodicalIF":0.0,"publicationDate":"2017-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78010615","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: 28

Machine Learning-Based Detection of Open Source License Exceptions 基于机器学习的开源许可证异常检测

2017 IEEE/ACM 39th International Conference on Software Engineering (ICSE) Pub Date : 2017-05-20 DOI: 10.1109/ICSE.2017.19

Christopher Vendome, M. Vásquez, G. Bavota, M. D. Penta, D. Germán, D. Poshyvanyk

{"title":"Machine Learning-Based Detection of Open Source License Exceptions","authors":"Christopher Vendome, M. Vásquez, G. Bavota, M. D. Penta, D. Germán, D. Poshyvanyk","doi":"10.1109/ICSE.2017.19","DOIUrl":"https://doi.org/10.1109/ICSE.2017.19","url":null,"abstract":"From a legal perspective, software licenses govern the redistribution, reuse, and modification of software as both source and binary code. Free and Open Source Software (FOSS) licenses vary in the degree to which they are permissive or restrictive in allowing redistribution or modification under licenses different from the original one(s). In certain cases, developers may modify the license by appending to it an exception to specifically allow reuse or modification under a particular condition. These exceptions are an important factor to consider for license compliance analysis since they modify the standard (and widely understood) terms of the original license. In this work, we first perform a large-scale empirical study on the change history of over 51K FOSS systems aimed at quantitatively investigating the prevalence of known license exceptions and identifying new ones. Subsequently, we performed a study on the detection of license exceptions by relying on machine learning. We evaluated the license exception classification with four different supervised learners and sensitivity analysis. Finally, we present a categorization of license exceptions and explain their implications.","PeriodicalId":6505,"journal":{"name":"2017 IEEE/ACM 39th International Conference on Software Engineering (ICSE)","volume":"136 1","pages":"118-129"},"PeriodicalIF":0.0,"publicationDate":"2017-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76377096","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: 28

Supporting Software Developers with a Holistic Recommender System 用整体推荐系统支持软件开发人员

2017 IEEE/ACM 39th International Conference on Software Engineering (ICSE) Pub Date : 2017-05-20 DOI: 10.1109/ICSE.2017.17

Luca Ponzanelli, Simone Scalabrino, G. Bavota, Andrea Mocci, R. Oliveto, M. D. Penta, Michele Lanza

{"title":"Supporting Software Developers with a Holistic Recommender System","authors":"Luca Ponzanelli, Simone Scalabrino, G. Bavota, Andrea Mocci, R. Oliveto, M. D. Penta, Michele Lanza","doi":"10.1109/ICSE.2017.17","DOIUrl":"https://doi.org/10.1109/ICSE.2017.17","url":null,"abstract":"The promise of recommender systems is to provide intelligent support to developers during their programming tasks. Such support ranges from suggesting program entities to taking into account pertinent Q&A pages. However, current recommender systems limit the context analysis to change history and developers' activities in the IDE, without considering what a developer has already consulted or perused, e.g., by performing searches from the Web browser. Given the faceted nature of many programming tasks, and the incompleteness of the information provided by a single artifact, several heterogeneous resources are required to obtain the broader picture needed by a developer to accomplish a task. We present Libra, a holistic recommender system. It supports the process of searching and navigating the information needed by constructing a holistic meta-information model of the resources perused by a developer, analyzing their semantic relationships, and augmenting the web browser with a dedicated interactive navigation chart. The quantitative and qualitative evaluation of Libra provides evidence that a holistic analysis of a developer's information context can indeed offer comprehensive and contextualized support to information navigation and retrieval during software development.","PeriodicalId":6505,"journal":{"name":"2017 IEEE/ACM 39th International Conference on Software Engineering (ICSE)","volume":"47 1","pages":"94-105"},"PeriodicalIF":0.0,"publicationDate":"2017-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76381865","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: 41

On Cross-Stack Configuration Errors 关于跨堆栈配置错误

2017 IEEE/ACM 39th International Conference on Software Engineering (ICSE) Pub Date : 2017-05-20 DOI: 10.1109/ICSE.2017.31

M. Sayagh, Noureddine Kerzazi, Bram Adams

{"title":"On Cross-Stack Configuration Errors","authors":"M. Sayagh, Noureddine Kerzazi, Bram Adams","doi":"10.1109/ICSE.2017.31","DOIUrl":"https://doi.org/10.1109/ICSE.2017.31","url":null,"abstract":"Today's web applications are deployed on powerful software stacks such as MEAN (JavaScript) or LAMP (PHP), which consist of multiple layers such as an operating system, web server, database, execution engine and application framework, each of which provide resources to the layer just above it. These powerful software stacks unfortunately are plagued by so-called cross-stack configuration errors (CsCEs), where a higher layer in the stack suddenly starts to behave incorrectly or even crash due to incorrect configuration choices in lower layers. Due to differences in programming languages and lack of explicit links between configuration options of different layers, sysadmins and developers have a hard time identifying the cause of a CsCE, which is why this paper (1) performs a qualitative analysis of 1,082 configuration errors to understand the impact, effort and complexity of dealing with CsCEs, then (2) proposes a modular approach that plugs existing source code analysis (slicing) techniques, in order to recommend the culprit configuration option. Empirical evaluation of this approach on 36 real CsCEs of the top 3 LAMP stack layers shows that our approach reports the misconfigured option with an average rank of 2.18 for 32 of the CsCEs, and takes only few minutes, making it practically useful.","PeriodicalId":6505,"journal":{"name":"2017 IEEE/ACM 39th International Conference on Software Engineering (ICSE)","volume":"243 1","pages":"255-265"},"PeriodicalIF":0.0,"publicationDate":"2017-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73863965","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

Analyzing APIs Documentation and Code to Detect Directive Defects 分析api文档和代码以检测指令缺陷

2017 IEEE/ACM 39th International Conference on Software Engineering (ICSE) Pub Date : 2017-05-20 DOI: 10.1109/ICSE.2017.11

Yu Zhou, Ruihang Gu, Taolue Chen, Zhiqiu Huang, Sebastiano Panichella, H. Gall

{"title":"Analyzing APIs Documentation and Code to Detect Directive Defects","authors":"Yu Zhou, Ruihang Gu, Taolue Chen, Zhiqiu Huang, Sebastiano Panichella, H. Gall","doi":"10.1109/ICSE.2017.11","DOIUrl":"https://doi.org/10.1109/ICSE.2017.11","url":null,"abstract":"Application Programming Interface (API) documents represent one of the most important references for API users. However, it is frequently reported that the documentation is inconsistent with the source code and deviates from the API itself. Such inconsistencies in the documents inevitably confuse the API users hampering considerably their API comprehension and the quality of software built from such APIs. In this paper, we propose an automated approach to detect defects of API documents by leveraging techniques from program comprehension and natural language processing. Particularly, we focus on the directives of the API documents which are related to parameter constraints and exception throwing declarations. A first-order logic based constraint solver is employed to detect such defects based on the obtained analysis results. We evaluate our approach on parts of well documented JDK 1.8 APIs. Experiment results show that, out of around 2000 API usage constraints, our approach can detect 1158 defective document directives, with a precision rate of 81.6%, and a recall rate of 82.0%, which demonstrates its practical feasibility.","PeriodicalId":6505,"journal":{"name":"2017 IEEE/ACM 39th International Conference on Software Engineering (ICSE)","volume":"11 1","pages":"27-37"},"PeriodicalIF":0.0,"publicationDate":"2017-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85431061","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: 101

From Diversity by Numbers to Diversity as Process: Supporting Inclusiveness in Software Development Teams with Brainstorming 从数字多样性到过程多样性:用头脑风暴支持软件开发团队的包容性

2017 IEEE/ACM 39th International Conference on Software Engineering (ICSE) Pub Date : 2017-05-20 DOI: 10.1109/ICSE.2017.22

Anna Filippova, E. Trainer, J. Herbsleb

引用次数: 52

Characterizing and Detecting Anti-Patterns in the Logging Code 日志代码中反模式的表征和检测

2017 IEEE/ACM 39th International Conference on Software Engineering (ICSE) Pub Date : 2017-05-20 DOI: 10.1109/ICSE.2017.15

Boyuan Chen, Z. Jiang

{"title":"Characterizing and Detecting Anti-Patterns in the Logging Code","authors":"Boyuan Chen, Z. Jiang","doi":"10.1109/ICSE.2017.15","DOIUrl":"https://doi.org/10.1109/ICSE.2017.15","url":null,"abstract":"Snippets of logging code are output statements (e.g., LOG.info or System.out.println) that developers insert into a software system. Although more logging code can provide more execution context of the system's behavior during runtime, it is undesirable to instrument the system with too much logging code due to maintenance overhead. Furthermore, excessive logging may cause unexpected side-effects like performance slow-down or high disk I/O bandwidth. Recent studies show that there are no well-defined coding guidelines for performing effective logging. Previous research on the logging code mainly tackles the problems of where-to-log and what-to-log. There are very few works trying to address the problem of how-to-log (developing and maintaining high-quality logging code). In this paper, we study the problem of how-to-log by characterizing and detecting the anti-patterns in the logging code. As the majority of the logging code is evolved together with the feature code, the remaining set of logging code changes usually contains the fixes to the anti-patterns. We have manually examined 352 pairs of independently changed logging code snippets from three well-maintenance open source systems: ActiveMQ, Hadoop and Maven. Our analysis has resulted in six different anti-patterns in the logging code. To demonstrate the value of our findings, we have encoded these anti-patterns into a static code analysis tool, LCAnalyzer. Case studies show that LCAnalyzer has an average recall of 95% and precision of 60% and can be used to automatically detect previously unknown anti-patterns in the source code. To gather feedback, we have filed 64 representative instances of the logging code anti-patterns from the most recent releases of ten open source software systems. Among them, 46 instances (72%) have already been accepted by their developers.","PeriodicalId":6505,"journal":{"name":"2017 IEEE/ACM 39th International Conference on Software Engineering (ICSE)","volume":"53 1","pages":"71-81"},"PeriodicalIF":0.0,"publicationDate":"2017-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91009200","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: 90

Performance Diagnosis for Inefficient Loops 无效率循环的性能诊断

2017 IEEE/ACM 39th International Conference on Software Engineering (ICSE) Pub Date : 2017-05-20 DOI: 10.1109/ICSE.2017.41

Linhai Song, Shan Lu

引用次数: 47

An Empirical Study on Mutation, Statement and Branch Coverage Fault Revelation That Avoids the Unreliable Clean Program Assumption 避免不可靠干净程序假设的突变、声明和分支覆盖故障揭示的实证研究

2017 IEEE/ACM 39th International Conference on Software Engineering (ICSE) Pub Date : 2017-05-20 DOI: 10.1109/ICSE.2017.61

T. Chekam, Mike Papadakis, Yves Le Traon, M. Harman

{"title":"An Empirical Study on Mutation, Statement and Branch Coverage Fault Revelation That Avoids the Unreliable Clean Program Assumption","authors":"T. Chekam, Mike Papadakis, Yves Le Traon, M. Harman","doi":"10.1109/ICSE.2017.61","DOIUrl":"https://doi.org/10.1109/ICSE.2017.61","url":null,"abstract":"Many studies suggest using coverage concepts, such as branch coverage, as the starting point of testing, while others as the most prominent test quality indicator. Yet the relationship between coverage and fault-revelation remains unknown, yielding uncertainty and controversy. Most previous studies rely on the Clean Program Assumption, that a test suite will obtain similar coverage for both faulty and fixed ('clean') program versions. This assumption may appear intuitive, especially for bugs that denote small semantic deviations. However, we present evidence that the Clean Program Assumption does not always hold, thereby raising a critical threat to the validity of previous results. We then conducted a study using a robust experimental methodology that avoids this threat to validity, from which our primary finding is that strong mutation testing has the highest fault revelation of four widely-used criteria. Our findings also revealed that fault revelation starts to increase significantly only once relatively high levels of coverage are attained.","PeriodicalId":6505,"journal":{"name":"2017 IEEE/ACM 39th International Conference on Software Engineering (ICSE)","volume":"20 1","pages":"597-608"},"PeriodicalIF":0.0,"publicationDate":"2017-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79577770","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: 128