Systems that are assembled from independently developed features suffer from feature interactions, in which features affect one another's behaviour in surprising ways. The Feature Interaction Problem results from trying to implement an appropriate resolution for each interaction within each possible context, because the number of possible contexts to consider increases exponentially with the number of features in the system. Resolution strategies aim to combat the Feature Interaction Problem by offering default strategies that resolve entire classes of interactions, thereby reducing the work needed to resolve lots of interactions. However most such approaches employ coarse-grained resolution strategies (e.g., feature priority) or a centralized arbitrator. Our work focuses on employing variable-specific default-resolution strategies that aim to resolve at runtime features- conflicting actions on a system's outputs. In this paper, we extend prior work to enable co-resolution of interactions on coupled output variables and to promote smooth continuous resolutions over execution paths. We implemented our approach within the PreScan simulator and performed a case study involving 15 automotive features; this entailed our devising and implementing three resolution strategies for three output variables. The results of the case study show that the approach produces smooth and continuous resolutions of interactions throughout interesting scenarios.
{"title":"Continuous variable-specific resolutions of feature interactions","authors":"M. H. Zibaeenejad, Chi Zhang, J. Atlee","doi":"10.1145/3106237.3106302","DOIUrl":"https://doi.org/10.1145/3106237.3106302","url":null,"abstract":"Systems that are assembled from independently developed features suffer from feature interactions, in which features affect one another's behaviour in surprising ways. The Feature Interaction Problem results from trying to implement an appropriate resolution for each interaction within each possible context, because the number of possible contexts to consider increases exponentially with the number of features in the system. Resolution strategies aim to combat the Feature Interaction Problem by offering default strategies that resolve entire classes of interactions, thereby reducing the work needed to resolve lots of interactions. However most such approaches employ coarse-grained resolution strategies (e.g., feature priority) or a centralized arbitrator. Our work focuses on employing variable-specific default-resolution strategies that aim to resolve at runtime features- conflicting actions on a system's outputs. In this paper, we extend prior work to enable co-resolution of interactions on coupled output variables and to promote smooth continuous resolutions over execution paths. We implemented our approach within the PreScan simulator and performed a case study involving 15 automotive features; this entailed our devising and implementing three resolution strategies for three output variables. The results of the case study show that the approach produces smooth and continuous resolutions of interactions throughout interesting scenarios.","PeriodicalId":313494,"journal":{"name":"Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114157242","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}
Wilberto Z. Nunez, Victor J. Marin, Carlos R. Rivero
As software projects evolve, carefully understanding the behavior of a program is mandatory before making any change. Repetitive code snippets also tend to appear throughout the codebase, and developers have to understand similar semantics multiple times. Building on this observation, we present Arcc: an Assistant for Repetitive Code Comprehension. The tool, implemented as an Eclipse plugin, assists developers in leveraging knowledge of a program to understand other programs containing a subset of the semantics in the former. Arcc differs from existing approaches in that it uses an extensible knowledge base of recurrent semantic code snippets, instead of heuristics or salient features, to summarize the behavior of a program. Given a program, we detect the occurrences of such snippets. Developers can create strategies as combinations of the snippets found and search for strategy occurrences in their workspace. Arcc highlights the source code related to every snippet and their interleaving, assisting in getting an intuition of similar programs. Finally, Arcc underlines potential common errors associated with the snippets, assisting in detecting overlooked problems. https://youtube.com/playlist?list=PLmizZtBESdPHDyKXKHMXj13r2pBCKzIoA
{"title":"ARCC: assistant for repetitive code comprehension","authors":"Wilberto Z. Nunez, Victor J. Marin, Carlos R. Rivero","doi":"10.1145/3106237.3122824","DOIUrl":"https://doi.org/10.1145/3106237.3122824","url":null,"abstract":"As software projects evolve, carefully understanding the behavior of a program is mandatory before making any change. Repetitive code snippets also tend to appear throughout the codebase, and developers have to understand similar semantics multiple times. Building on this observation, we present Arcc: an Assistant for Repetitive Code Comprehension. The tool, implemented as an Eclipse plugin, assists developers in leveraging knowledge of a program to understand other programs containing a subset of the semantics in the former. Arcc differs from existing approaches in that it uses an extensible knowledge base of recurrent semantic code snippets, instead of heuristics or salient features, to summarize the behavior of a program. Given a program, we detect the occurrences of such snippets. Developers can create strategies as combinations of the snippets found and search for strategy occurrences in their workspace. Arcc highlights the source code related to every snippet and their interleaving, assisting in getting an intuition of similar programs. Finally, Arcc underlines potential common errors associated with the snippets, assisting in detecting overlooked problems. https://youtube.com/playlist?list=PLmizZtBESdPHDyKXKHMXj13r2pBCKzIoA","PeriodicalId":313494,"journal":{"name":"Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114840275","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 number of vulnerabilities in open source libraries is increasing rapidly. However, the majority of them do not go through public disclosure. These unidentified vulnerabilities put developers' products at risk of being hacked since they are increasingly relying on open source libraries to assemble and build software quickly. To find unidentified vulnerabilities in open source libraries and secure modern software development, we describe an efficient automatic vulnerability identification system geared towards tracking large-scale projects in real time using natural language processing and machine learning techniques. Built upon the latent information underlying commit messages and bug reports in open source projects using GitHub, JIRA, and Bugzilla, our K-fold stacking classifier achieves promising results on vulnerability identification. Compared to the state of the art SVM-based classifier in prior work on vulnerability identification in commit messages, we improve precision by 54.55% while maintaining the same recall rate. For bug reports, we achieve a much higher precision of 0.70 and recall rate of 0.71 compared to existing work. Moreover, observations from running the trained model at SourceClear in production for over 3 months has shown 0.83 precision, 0.74 recall rate, and detected 349 hidden vulnerabilities, proving the effectiveness and generality of the proposed approach.
{"title":"Automated identification of security issues from commit messages and bug reports","authors":"Yaqin Zhou, Asankhaya Sharma","doi":"10.1145/3106237.3117771","DOIUrl":"https://doi.org/10.1145/3106237.3117771","url":null,"abstract":"The number of vulnerabilities in open source libraries is increasing rapidly. However, the majority of them do not go through public disclosure. These unidentified vulnerabilities put developers' products at risk of being hacked since they are increasingly relying on open source libraries to assemble and build software quickly. To find unidentified vulnerabilities in open source libraries and secure modern software development, we describe an efficient automatic vulnerability identification system geared towards tracking large-scale projects in real time using natural language processing and machine learning techniques. Built upon the latent information underlying commit messages and bug reports in open source projects using GitHub, JIRA, and Bugzilla, our K-fold stacking classifier achieves promising results on vulnerability identification. Compared to the state of the art SVM-based classifier in prior work on vulnerability identification in commit messages, we improve precision by 54.55% while maintaining the same recall rate. For bug reports, we achieve a much higher precision of 0.70 and recall rate of 0.71 compared to existing work. Moreover, observations from running the trained model at SourceClear in production for over 3 months has shown 0.83 precision, 0.74 recall rate, and detected 349 hidden vulnerabilities, proving the effectiveness and generality of the proposed approach.","PeriodicalId":313494,"journal":{"name":"Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116060370","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}
Stelios Sidiroglou, Eric Lahtinen, Anthony Eden, Fan Long, M. Rinard
We present CodeCarbonCopy (CCC), a system for transferring code from a donor application into a recipient application. CCC starts with functionality identified by the developer to transfer into an insertion point (again identified by the developer) in the recipient. CCC uses paired executions of the donor and recipient on the same input file to obtain a translation between the data representation and name space of the recipient and the data representation and name space of the donor. It also implements a static analysis that identifies and removes irrelevant functionality useful in the donor but not in the recipient. We evaluate CCC on eight transfers between six applications. Our results show that CCC can successfully transfer donor functionality into recipient applications.
{"title":"CodeCarbonCopy","authors":"Stelios Sidiroglou, Eric Lahtinen, Anthony Eden, Fan Long, M. Rinard","doi":"10.1145/3106237.3106269","DOIUrl":"https://doi.org/10.1145/3106237.3106269","url":null,"abstract":"We present CodeCarbonCopy (CCC), a system for transferring code from a donor application into a recipient application. CCC starts with functionality identified by the developer to transfer into an insertion point (again identified by the developer) in the recipient. CCC uses paired executions of the donor and recipient on the same input file to obtain a translation between the data representation and name space of the recipient and the data representation and name space of the donor. It also implements a static analysis that identifies and removes irrelevant functionality useful in the donor but not in the recipient. We evaluate CCC on eight transfers between six applications. Our results show that CCC can successfully transfer donor functionality into recipient applications.","PeriodicalId":313494,"journal":{"name":"Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering","volume":"52 s35","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132360307","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}
We increasingly live in cyber-physical spaces -- spaces that are both physical and digital, and where the two aspects are intertwined. Such spaces are highly dynamic and typically undergo continuous change. Software engineering can have a profound impact in this domain, by defining suitable modeling and specification notations as well as supporting design-time formal verification. In this paper, we present a methodology and a technical framework which support modeling of evolving cyber-physical spaces and reasoning about their spatio-temporal properties. We utilize a discrete, graph-based formalism for modeling cyber-physical spaces as well as primitives of change, giving rise to a reactive system consisting of rewriting rules with both local and global application conditions. Formal reasoning facilities are implemented adopting logic-based specification of properties and according model checking procedures, in both spatial and temporal fragments. We evaluate our approach using a case study of a disaster scenario in a smart city.
{"title":"Modeling and verification of evolving cyber-physical spaces","authors":"Christos Tsigkanos, Timo Kehrer, C. Ghezzi","doi":"10.1145/3106237.3106299","DOIUrl":"https://doi.org/10.1145/3106237.3106299","url":null,"abstract":"We increasingly live in cyber-physical spaces -- spaces that are both physical and digital, and where the two aspects are intertwined. Such spaces are highly dynamic and typically undergo continuous change. Software engineering can have a profound impact in this domain, by defining suitable modeling and specification notations as well as supporting design-time formal verification. In this paper, we present a methodology and a technical framework which support modeling of evolving cyber-physical spaces and reasoning about their spatio-temporal properties. We utilize a discrete, graph-based formalism for modeling cyber-physical spaces as well as primitives of change, giving rise to a reactive system consisting of rewriting rules with both local and global application conditions. Formal reasoning facilities are implemented adopting logic-based specification of properties and according model checking procedures, in both spatial and temporal fragments. We evaluate our approach using a case study of a disaster scenario in a smart city.","PeriodicalId":313494,"journal":{"name":"Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133274475","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}
Despite the fact an intelligent tutoring system for programming (ITSP) education has long attracted interest, its widespread use has been hindered by the difficulty of generating personalized feedback automatically. Meanwhile, automated program repair (APR) is an emerging new technology that automatically fixes software bugs, and it has been shown that APR can fix the bugs of large real-world software. In this paper, we study the feasibility of marrying intelligent programming tutoring and APR. We perform our feasibility study with four state-of-the-art APR tools (GenProg, AE, Angelix, and Prophet), and 661 programs written by the students taking an introductory programming course. We found that when APR tools are used out of the box, only about 30% of the programs in our dataset are repaired. This low repair rate is largely due to the student programs often being significantly incorrect - in contrast, professional software for which APR was successfully applied typically fails only a small portion of tests. To bridge this gap, we adopt in APR a new repair policy akin to the hint generation policy employed in the existing ITSP. This new repair policy admits partial repairs that address part of failing tests, which results in 84% improvement of repair rate. We also performed a user study with 263 novice students and 37 graders, and identified an understudied problem; while novice students do not seem to know how to effectively make use of generated repairs as hints, the graders do seem to gain benefits from repairs.
尽管智能编程辅导系统(ITSP)一直以来都引起了人们的兴趣，但由于难以自动生成个性化的反馈，ITSP的广泛应用受到了阻碍。同时，自动程序修复(automated program repair, APR)是一种新兴的自动修复软件缺陷的新技术，并已被证明可以修复现实世界中大型软件的缺陷。在本文中，我们研究了将智能编程辅导与APR结合的可行性。我们使用了四种最先进的APR工具(GenProg, AE, Angelix和Prophet)和661个由参加入门编程课程的学生编写的程序来进行可行性研究。我们发现，当APR工具开箱即用时，我们的数据集中只有大约30%的程序被修复。这种低修复率很大程度上是由于学生程序经常出现严重错误——相比之下，成功应用APR的专业软件通常只会在一小部分测试中失败。为了弥合这一差距，我们在APR中采用了一种新的修复策略，类似于现有ITSP中使用的提示生成策略。这种新的修复策略允许针对部分失败测试进行部分修复，从而使修复率提高84%。我们还对263名新手和37名年级学生进行了用户研究，并发现了一个未被充分研究的问题;虽然新手似乎不知道如何有效地利用生成的修理作为提示，但评分者似乎确实从修理中获益。
{"title":"A feasibility study of using automated program repair for introductory programming assignments","authors":"Jooyong Yi, Umair Z. Ahmed, Amey Karkare, Shin Hwei Tan, Abhik Roychoudhury","doi":"10.1145/3106237.3106262","DOIUrl":"https://doi.org/10.1145/3106237.3106262","url":null,"abstract":"Despite the fact an intelligent tutoring system for programming (ITSP) education has long attracted interest, its widespread use has been hindered by the difficulty of generating personalized feedback automatically. Meanwhile, automated program repair (APR) is an emerging new technology that automatically fixes software bugs, and it has been shown that APR can fix the bugs of large real-world software. In this paper, we study the feasibility of marrying intelligent programming tutoring and APR. We perform our feasibility study with four state-of-the-art APR tools (GenProg, AE, Angelix, and Prophet), and 661 programs written by the students taking an introductory programming course. We found that when APR tools are used out of the box, only about 30% of the programs in our dataset are repaired. This low repair rate is largely due to the student programs often being significantly incorrect - in contrast, professional software for which APR was successfully applied typically fails only a small portion of tests. To bridge this gap, we adopt in APR a new repair policy akin to the hint generation policy employed in the existing ITSP. This new repair policy admits partial repairs that address part of failing tests, which results in 84% improvement of repair rate. We also performed a user study with 263 novice students and 37 graders, and identified an understudied problem; while novice students do not seem to know how to effectively make use of generated repairs as hints, the graders do seem to gain benefits from repairs.","PeriodicalId":313494,"journal":{"name":"Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133482979","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}
We present the results of applying our approach for testing Simulink controllers to one public and one proprietary model, both industrial. Our approach combines explorative and exploitative search algorithms to visualize the controller behavior over its input space and to identify test scenarios in the controller input space that violate or are likely to violate the controller requirements. The engineers' feedback shows that our approach is easy to use in practice and gives them confidence about the behavior of their models.
{"title":"Automated testing of hybrid Simulink/Stateflow controllers: industrial case studies","authors":"Reza Matinnejad, S. Nejati, L. Briand","doi":"10.1145/3106237.3117770","DOIUrl":"https://doi.org/10.1145/3106237.3117770","url":null,"abstract":"We present the results of applying our approach for testing Simulink controllers to one public and one proprietary model, both industrial. Our approach combines explorative and exploitative search algorithms to visualize the controller behavior over its input space and to identify test scenarios in the controller input space that violate or are likely to violate the controller requirements. The engineers' feedback shows that our approach is easy to use in practice and gives them confidence about the behavior of their models.","PeriodicalId":313494,"journal":{"name":"Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133233671","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}
Vaibhav Rastogi, Drew Davidson, Lorenzo De Carli, S. Jha, P. Mcdaniel
Application containers, such as those provided by Docker, have recently gained popularity as a solution for agile and seamless software deployment. These light-weight virtualization environments run applications that are packed together with their resources and configuration information, and thus can be deployed across various software platforms. Unfortunately, the ease with which containers can be created is oftentimes a double-edged sword, encouraging the packaging of logically distinct applications, and the inclusion of significant amount of unnecessary components, within a single container. These practices needlessly increase the container size-sometimes by orders of magnitude. They also decrease the overall security, as each included component-necessary or not-may bring in security issues of its own, and there is no isolation between multiple applications packaged within the same container image. We propose algorithms and a tool called Cimplifier, which address these concerns: given a container and simple user-defined constraints, our tool partitions it into simpler containers, which (i) are isolated from each other, only communicating as necessary, and (ii) only include enough resources to perform their functionality. Our evaluation on real-world containers demonstrates that Cimplifier preserves the original functionality, leads to reduction in image size of up to 95%, and processes even large containers in under thirty seconds.
{"title":"Cimplifier: automatically debloating containers","authors":"Vaibhav Rastogi, Drew Davidson, Lorenzo De Carli, S. Jha, P. Mcdaniel","doi":"10.1145/3106237.3106271","DOIUrl":"https://doi.org/10.1145/3106237.3106271","url":null,"abstract":"Application containers, such as those provided by Docker, have recently gained popularity as a solution for agile and seamless software deployment. These light-weight virtualization environments run applications that are packed together with their resources and configuration information, and thus can be deployed across various software platforms. Unfortunately, the ease with which containers can be created is oftentimes a double-edged sword, encouraging the packaging of logically distinct applications, and the inclusion of significant amount of unnecessary components, within a single container. These practices needlessly increase the container size-sometimes by orders of magnitude. They also decrease the overall security, as each included component-necessary or not-may bring in security issues of its own, and there is no isolation between multiple applications packaged within the same container image. We propose algorithms and a tool called Cimplifier, which address these concerns: given a container and simple user-defined constraints, our tool partitions it into simpler containers, which (i) are isolated from each other, only communicating as necessary, and (ii) only include enough resources to perform their functionality. Our evaluation on real-world containers demonstrates that Cimplifier preserves the original functionality, leads to reduction in image size of up to 95%, and processes even large containers in under thirty seconds.","PeriodicalId":313494,"journal":{"name":"Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130343424","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}
Software project scheduling, under uncertain and dynamic environments, is one of the most important challenges in software engineering. Recent studies addressed this challenge in both static and dynamic scenarios for small and medium size software projects. The increasing trend of cloud based software solutions (large scale software projects) needs agility not only for sustainable maintenance but also for in time and within budget completion. Therefore, this paper formulates software project scheduling problem (SPSP) as an optimization problem under uncertainties and dynamics for hybrid scRUmP software model. In this regard, a mathematical model is constructed with five objectives as project duration, task fragmentation, robustness, cost, and stability.
{"title":"Model-based dynamic software project scheduling","authors":"Natasha Nigar","doi":"10.1145/3106237.3119879","DOIUrl":"https://doi.org/10.1145/3106237.3119879","url":null,"abstract":"Software project scheduling, under uncertain and dynamic environments, is one of the most important challenges in software engineering. Recent studies addressed this challenge in both static and dynamic scenarios for small and medium size software projects. The increasing trend of cloud based software solutions (large scale software projects) needs agility not only for sustainable maintenance but also for in time and within budget completion. Therefore, this paper formulates software project scheduling problem (SPSP) as an optimization problem under uncertainties and dynamics for hybrid scRUmP software model. In this regard, a mathematical model is constructed with five objectives as project duration, task fragmentation, robustness, cost, and stability.","PeriodicalId":313494,"journal":{"name":"Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127153203","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}
Germán Regis, César Cornejo, Simón Gutiérrez Brida, M. Politano, Fernando D. Raverta, Pablo Ponzio, Nazareno Aguirre, Juan P. Galeotti, M. Frias
We describe DynAlloy Analyzer, a tool that extends Alloy Analyzer with support for dynamic elements in Alloy models. The tool builds upon Alloy Analyzer in a way that makes it fully compatible with Alloy models, and extends their syntax with a particular idiom, inspired in dynamic logic, for the description of dynamic behaviours, understood as sequences of states over standard Alloy models, in terms of programs. The syntax is broad enough to accommodate abstract dynamic behaviours, e.g., using nondeterministic choice and finite unbounded iteration, as well as more concrete ones, using standard sequential programming constructions. The analysis of DynAlloy models resorts to the analysis of Alloy models, through an optimized translation that often makes the analysis more efficient than that of typical ad-hoc constructions to capture dynamism in Alloy. Tool screencast, binaries and further details available in: http://dc.exa.unrc.edu.ar/tools/dynalloy
{"title":"DynAlloy analyzer: a tool for the specification and analysis of alloy models with dynamic behaviour","authors":"Germán Regis, César Cornejo, Simón Gutiérrez Brida, M. Politano, Fernando D. Raverta, Pablo Ponzio, Nazareno Aguirre, Juan P. Galeotti, M. Frias","doi":"10.1145/3106237.3122826","DOIUrl":"https://doi.org/10.1145/3106237.3122826","url":null,"abstract":"We describe DynAlloy Analyzer, a tool that extends Alloy Analyzer with support for dynamic elements in Alloy models. The tool builds upon Alloy Analyzer in a way that makes it fully compatible with Alloy models, and extends their syntax with a particular idiom, inspired in dynamic logic, for the description of dynamic behaviours, understood as sequences of states over standard Alloy models, in terms of programs. The syntax is broad enough to accommodate abstract dynamic behaviours, e.g., using nondeterministic choice and finite unbounded iteration, as well as more concrete ones, using standard sequential programming constructions. The analysis of DynAlloy models resorts to the analysis of Alloy models, through an optimized translation that often makes the analysis more efficient than that of typical ad-hoc constructions to capture dynamism in Alloy. Tool screencast, binaries and further details available in: http://dc.exa.unrc.edu.ar/tools/dynalloy","PeriodicalId":313494,"journal":{"name":"Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123357979","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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