2017 IEEE/ACM 39th International Conference on Software Engineering: New Ideas and Emerging Technologies Results Track (ICSE-NIER)最新文献

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On Accelerating Ultra-Large-Scale Mining 加快超大规模采矿
Ganesha Upadhyaya, Hridesh Rajan
{"title":"On Accelerating Ultra-Large-Scale Mining","authors":"Ganesha Upadhyaya, Hridesh Rajan","doi":"10.1109/ICSE-NIER.2017.11","DOIUrl":"https://doi.org/10.1109/ICSE-NIER.2017.11","url":null,"abstract":"Ultra-large-scale mining has been shown to be useful for a number of software engineering tasks e.g. mining specifications, defect prediction. We propose a new research direction for accelerating ultra-large-scale mining that goes beyond parallelization. Our key idea is to analyze the interaction pattern between the mining task and the artifact to cluster artifacts such that running the mining task on one candidate artifact from each cluster is sufficient to produce results for other artifacts in the same cluster. Our artifact clustering criteria go beyond syntactic, semantic, and functional similarities to mining-task-specific similarity, where the interaction pattern between the mining task and the artifact is used for clustering. Our preliminary evaluation demonstrates that our technique significantly reduces the overall mining time.","PeriodicalId":134651,"journal":{"name":"2017 IEEE/ACM 39th International Conference on Software Engineering: New Ideas and Emerging Technologies Results Track (ICSE-NIER)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129912621","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
DevOps in Regulated Software Development: Case Medical Devices 规范软件开发中的DevOps:案例医疗设备
Teemu Laukkarinen, Kati Kuusinen, T. Mikkonen
{"title":"DevOps in Regulated Software Development: Case Medical Devices","authors":"Teemu Laukkarinen, Kati Kuusinen, T. Mikkonen","doi":"10.1109/ICSE-NIER.2017.20","DOIUrl":"https://doi.org/10.1109/ICSE-NIER.2017.20","url":null,"abstract":"DevOps and continuous development are getting popular in the software industry. Adopting these modern approaches in regulatory environments, such as medical device software, is not straightforward because of the demand for regulatory compliance. While DevOps relies on continuous deployment and integration, regulated environments require strict audits and approvals before releases. Therefore, the use of modern development approaches in regulatory environments is rare, as is the research on the topic. However, as software is more and more predominant in medical devices, modern software development approaches become attractive. This paper discusses the fit of DevOps for regulated medical device software development. We examine two related standards, IEC 62304 and IEC 82304-1, for obstacles and benefits of using DevOps for medical device software development. We found these standards to set obstacles for continuous delivery and integration. Respectively, development tools can help fulfilling the requirements of traceability and documentation of these standards.","PeriodicalId":134651,"journal":{"name":"2017 IEEE/ACM 39th International Conference on Software Engineering: New Ideas and Emerging Technologies Results Track (ICSE-NIER)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130232117","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: 39
Accelerating Software Engineering Research Adoption with Analysis Bots 使用分析机器人加速软件工程研究的采用
Ivan Beschastnikh, M. Lungu, Yanyan Zhuang
{"title":"Accelerating Software Engineering Research Adoption with Analysis Bots","authors":"Ivan Beschastnikh, M. Lungu, Yanyan Zhuang","doi":"10.1109/ICSE-NIER.2017.17","DOIUrl":"https://doi.org/10.1109/ICSE-NIER.2017.17","url":null,"abstract":"An important part of software engineering (SE) research is to develop new analysis techniques and to integrate these techniques into software development practice. However, since access to developers is non-trivial and research tool adoption is slow, new analyses are typically evaluated as follows: a prototype tool that embeds the analysis is implemented, a set of projects is identified, their revisions are selected, and the tool is run in a controlled environment, rarely involving the developers of the software. As a result, research artifacts are brittle and it is unclear if an analysis tool would actually be adopted. In this paper, we envision harnessing the rich interfaces provided by popular social coding platforms for automated deployment and evaluation of SE research analysis. We propose that SE analyses can be deployed as analysis bots. We focus on two specific benefits of such an approach: (1) analysis bots can help evaluate analysis techniques in a less controlled, and more realistic context, and (2) analysis bots provide an interface for developers to \"subscribe\" to new research techniques without needing to trust the implementation, the developer of the new tool, or to install the analysis tool locally. We outline basic requirements for an analysis bots platform, and present research challenges that would need to be resolved for bots to flourish.","PeriodicalId":134651,"journal":{"name":"2017 IEEE/ACM 39th International Conference on Software Engineering: New Ideas and Emerging Technologies Results Track (ICSE-NIER)","volume":"322 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116533415","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: 22
At the End of Synthesis: Narrowing Program Candidates 在综合的最后:缩小项目候选人
David Shriver, Sebastian G. Elbaum, Kathryn T. Stolee
{"title":"At the End of Synthesis: Narrowing Program Candidates","authors":"David Shriver, Sebastian G. Elbaum, Kathryn T. Stolee","doi":"10.1109/ICSE-NIER.2017.7","DOIUrl":"https://doi.org/10.1109/ICSE-NIER.2017.7","url":null,"abstract":"Program synthesis is succeeding in supporting the generation of programs within increasingly complex domains. The use of weaker specifications, such as those consisting of input/output examples or test cases, has helped to fuel the success of program synthesis by lowering adoption barriers. Yet, employing weaker specifications has the side effect of generating a potentially large number of candidate programs. This was not a problem for simpler and smaller program domains, but it is becoming evident that differentiating among many synthesized programs is a challenge that needs addressing. We sketch an approach to mitigate this challenge, requiring less effort from the user while automatically identifying inputs that can differentiate clusters of synthesized programs. The approach has the potential to more cost-effectively narrow the space of candidate programs in a range of synthesis applications.","PeriodicalId":134651,"journal":{"name":"2017 IEEE/ACM 39th International Conference on Software Engineering: New Ideas and Emerging Technologies Results Track (ICSE-NIER)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126791312","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
The Impact of Retrieval Direction on IR-Based Traceability Link Recovery 检索方向对基于ir的可追溯链路恢复的影响
Chris Mills, S. Haiduc
{"title":"The Impact of Retrieval Direction on IR-Based Traceability Link Recovery","authors":"Chris Mills, S. Haiduc","doi":"10.1109/ICSE-NIER.2017.14","DOIUrl":"https://doi.org/10.1109/ICSE-NIER.2017.14","url":null,"abstract":"The application of Information Retrieval (IR) techniquesto software traceability link recovery has been the focusof many studies. These studies have formulated the task ofestablishing valid trace links between two types of softwareartifacts as a retrieval problem, where one type of artifacts isselected as the set of queries and the other as the corpus. Previouswork selected the sets of queries and corpus artifacts for a studyup front, therefore pre-imposing a retrieval direction for findingall trace links. This decision was usually made based on intuitionor previous work. We argue that the choice of the query andcorpus sets (i.e., retrieval direction) can significantly impact theresults of IR-based traceability link recovery and should be madewith context in mind, as the best choice may be dependent onthe properties of each dataset. More than that, we argue thateven within the same system, different traceability links maybe best recovered by using different retrieval directions. In thispaper we provide the first evidence to support these claims, showing that retrieval direction can have a significant impacton IR performance for traceability link recovery at both theproject and individual link level. Moreover, we propose futureresearch directions aimed at predicting the most efficient retrievaldirection, as well as approaches leveraging information from bothretrieval directions simultaneously.","PeriodicalId":134651,"journal":{"name":"2017 IEEE/ACM 39th International Conference on Software Engineering: New Ideas and Emerging Technologies Results Track (ICSE-NIER)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130976777","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
Statistical Learning for Inference between Implementations and Documentation 在实现和文档之间进行推理的统计学习
H. Phan, H. Nguyen, T. Nguyen, Hridesh Rajan
{"title":"Statistical Learning for Inference between Implementations and Documentation","authors":"H. Phan, H. Nguyen, T. Nguyen, Hridesh Rajan","doi":"10.1109/ICSE-NIER.2017.9","DOIUrl":"https://doi.org/10.1109/ICSE-NIER.2017.9","url":null,"abstract":"API documentation is useful for developers to better understand how tocorrectly use the libraries. However, not all libraries provide gooddocumentation on API usages. To provide better documentation, existingtechniques have been proposed including program analysis-based anddata mining-based approaches. In this work, instead of mining, we aimto generate behavioral exception documentation for any given code. Wetreat the problem of automatically generating documentation from anovel perspective: statistical machine translation (SMT). We considerthe documentation and source code for an API method as the twoabstraction levels of the same intention. We use SMT to translatedocumentation from source code and vice versa. Our preliminary resultsshow that the direction of statistical learning for inference betweenimplementations and documentation is very promising.","PeriodicalId":134651,"journal":{"name":"2017 IEEE/ACM 39th International Conference on Software Engineering: New Ideas and Emerging Technologies Results Track (ICSE-NIER)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123234226","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: 18
Production-Driven Patch Generation 生产驱动的补丁生成
Thomas Durieux, Y. Hamadi, Monperrus Martin
{"title":"Production-Driven Patch Generation","authors":"Thomas Durieux, Y. Hamadi, Monperrus Martin","doi":"10.1109/ICSE-NIER.2017.8","DOIUrl":"https://doi.org/10.1109/ICSE-NIER.2017.8","url":null,"abstract":"We present an original concept for patch generation: we propose to do it directly in production. Our idea is to generate patches on-the-fly based on automated analysis of the failure context. By doing this in production, the repair process has complete access to the system state at the point of failure. We propose to perform live regression testing of the generated patches directly on the production traffic, by feeding a sandboxed version of the application with a copy of the production traffic, the 'shadow traffic'. Our concept widens the applicability of program repair, because it removes the requirements of having a failing test case.","PeriodicalId":134651,"journal":{"name":"2017 IEEE/ACM 39th International Conference on Software Engineering: New Ideas and Emerging Technologies Results Track (ICSE-NIER)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125906409","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: 6
Performance Metamorphic Testing: Motivation and Challenges 性能变形测试:动机与挑战
Sergio Segura, J. Troya, Amador Durán Toro, Antonio Ruiz-Cortés
{"title":"Performance Metamorphic Testing: Motivation and Challenges","authors":"Sergio Segura, J. Troya, Amador Durán Toro, Antonio Ruiz-Cortés","doi":"10.1109/ICSE-NIER.2017.16","DOIUrl":"https://doi.org/10.1109/ICSE-NIER.2017.16","url":null,"abstract":"Performance testing is a challenging task mainly due to the lack of test oracles, that is, mechanisms to decide whether the performance of a program under a certain workload is either acceptable or poor due to a performance bug. Metamorphic testing enables the generation of test cases in the absence of an oracle by exploiting the relations (so-called metamorphic relations) between the inputs and outputs of multiple executions of the program under test. In the last two decades, metamorphic testing has been successfully used to detect functional faults in a variety of domains, ranging from web services to simulators. However, the applicability of metamorphic testing to detect performance bugs is a topic that remains unexplored. In this vision paper, we introduce Performance Metamorphic Relations (PMRs) as expected relations between the performance measurements of multiple executions of the program under test. We hypothesize that these relations can be turned into assertions for the automated detection of performance bugs removing the need for complex benchmarks and domain experts guidance. As a further benefit, PMRs can be turned into fitness functions to guide search-based techniques on the generation of test data that violate the relations, revealing bugs. This novel idea is motivated with examples and an overview of some of the challenges in this promising topic.","PeriodicalId":134651,"journal":{"name":"2017 IEEE/ACM 39th International Conference on Software Engineering: New Ideas and Emerging Technologies Results Track (ICSE-NIER)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128426303","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: 25
Mutation Testing Meets Approximate Computing 突变测试满足近似计算
Miloš Gligorić, S. Khurshid, Sasa Misailovic, A. Shi
{"title":"Mutation Testing Meets Approximate Computing","authors":"Miloš Gligorić, S. Khurshid, Sasa Misailovic, A. Shi","doi":"10.1109/ICSE-NIER.2017.15","DOIUrl":"https://doi.org/10.1109/ICSE-NIER.2017.15","url":null,"abstract":"One of the most widely studied techniques in software testing researchis mutation testing - a technique for evaluating the quality of testsuites. Despite over four decades of academic advances in thistechnique, mutation testing has not found its way to mainstreamdevelopment. The key issue with mutation testing is its highcomputational cost: it requires running the test suite against notjust the program under test but against typically thousands ofmutants, i.e., syntactic variants, of the program. Our key insight isthat exciting advances in the upcoming, yet unrelated, area ofapproximate computing allow us to define a principled approach thatprovides the benefits of traditional mutation testing at a fraction ofits usually large cost. This paper introduces the idea of a novel approach, named ApproxiMut, that blends the power of mutation testing with the practicality ofapproximate computing. To demonstrate the potential of our approach, we present a concrete instantiation: rather than executing testsagainst each mutant on the exact program version, ApproxiMut obtainsan approximate test/program version by applying approximatetransformations and runs tests against each mutant on the approximatedversion. Our initial goal is to (1) measure the correlation betweenmutation scores on the exact and approximate program versions, (2)evaluate the relation among mutation operators and approximatetransformations, (3) discover the best way to approximate a test and aprogram, and (4) evaluate the benefits of ApproxiMut. Our preliminaryresults show similar mutation scores on the exact and approximateprogram versions and uncovered a case when an approximated test was, to our surprise, better than the exact test.","PeriodicalId":134651,"journal":{"name":"2017 IEEE/ACM 39th International Conference on Software Engineering: New Ideas and Emerging Technologies Results Track (ICSE-NIER)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126150708","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
DARVIZ: Deep Abstract Representation, Visualization, and Verification of Deep Learning Models 深度学习模型的深度抽象表示、可视化和验证
A. Sankaran, Rahul Aralikatte, Senthil Mani, Shreya Khare, Naveen Panwar, Neelamadhav Gantayat
{"title":"DARVIZ: Deep Abstract Representation, Visualization, and Verification of Deep Learning Models","authors":"A. Sankaran, Rahul Aralikatte, Senthil Mani, Shreya Khare, Naveen Panwar, Neelamadhav Gantayat","doi":"10.1109/ICSE-NIER.2017.13","DOIUrl":"https://doi.org/10.1109/ICSE-NIER.2017.13","url":null,"abstract":"Traditional software engineering programming paradigms are mostly object or procedure oriented, driven by deterministic algorithms. With the advent of deep learning and cognitive sciences there is an emerging trend for data-driven programming, creating a shift in the programming paradigm among the software engineering communities. Visualizing and interpreting the execution of a current large scale data-driven software development is challenging. Further, for deep learning development there are many libraries in multiple programming languages such as TensorFlow (Python), CAFFE (C++), Theano (Python), Torch (Lua), and Deeplearning4j (Java), driving a huge need for interoperability across libraries. We propose a model driven development based solution framework, that facilitates intuitive designing of deep learning models in a platform agnostic fashion. This framework could potentially generate library specific code, perform program translation across languages, and debug the training process of a deep learning model from a fault localization and repair perspective. Further we identify open research problems in this emerging domain, and discuss some new software tooling requirements to serve this new age data-driven programming paradigm.","PeriodicalId":134651,"journal":{"name":"2017 IEEE/ACM 39th International Conference on Software Engineering: New Ideas and Emerging Technologies Results Track (ICSE-NIER)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128388303","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
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