{"title":"Internetware 2022: 13th Asia-Pacific Symposium on Internetware, Hohhot, China, June 11 - 12, 2022","authors":"","doi":"10.1145/3545258","DOIUrl":"https://doi.org/10.1145/3545258","url":null,"abstract":"","PeriodicalId":20631,"journal":{"name":"Proceedings of the 8th Asia-Pacific Symposium on Internetware","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82425681","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}
{"title":"Internetware'20: 12th Asia-Pacific Symposium on Internetware, Singapore, November 1-3, 2020","authors":"","doi":"10.1145/3457913","DOIUrl":"https://doi.org/10.1145/3457913","url":null,"abstract":"","PeriodicalId":20631,"journal":{"name":"Proceedings of the 8th Asia-Pacific Symposium on Internetware","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80088175","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}
{"title":"Internetware '19: The 11th Asia-Pacific Symposium on Internetware, Fukuoka, Japan, October 28-29, 2019","authors":"","doi":"10.1145/3361242","DOIUrl":"https://doi.org/10.1145/3361242","url":null,"abstract":"","PeriodicalId":20631,"journal":{"name":"Proceedings of the 8th Asia-Pacific Symposium on Internetware","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72896189","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}
Cheng Yang, Qiang Fan, Tao Wang, Gang Yin, Huaimin Wang
Social coding represents a new style of software production and creation paradigm, and demands for new technologies of software reuse. Many people searching for projects package, we can provide good reuse recommendation. In this paper, we focus on an interesting research topic of recommending software repositories to social developers, which is challenging because of two points: the first is how to get the interest contexts of developers; and the second is how to rank the repository candidates for recommendation properly. We propose RepoLike, a new approach for recommending repositories to developers by predicting their interests. RepoLike explores the developers' historical development activities and the social connections with other programmers, mines the technical features of repositories and the dependencies among them, and then combines both aspects to recommend most interesting and inspiring repositories to developers. The experiment results show that our approach can surprisingly recommend closely correlated repositories to developers, and the critical test results show that the recommendation performance is strongly impacted by the interest context model.
{"title":"RepoLike: personal repositories recommendation in social coding communities","authors":"Cheng Yang, Qiang Fan, Tao Wang, Gang Yin, Huaimin Wang","doi":"10.1145/2993717.2993725","DOIUrl":"https://doi.org/10.1145/2993717.2993725","url":null,"abstract":"Social coding represents a new style of software production and creation paradigm, and demands for new technologies of software reuse. Many people searching for projects package, we can provide good reuse recommendation. In this paper, we focus on an interesting research topic of recommending software repositories to social developers, which is challenging because of two points: the first is how to get the interest contexts of developers; and the second is how to rank the repository candidates for recommendation properly. We propose RepoLike, a new approach for recommending repositories to developers by predicting their interests. RepoLike explores the developers' historical development activities and the social connections with other programmers, mines the technical features of repositories and the dependencies among them, and then combines both aspects to recommend most interesting and inspiring repositories to developers. The experiment results show that our approach can surprisingly recommend closely correlated repositories to developers, and the critical test results show that the recommendation performance is strongly impacted by the interest context model.","PeriodicalId":20631,"journal":{"name":"Proceedings of the 8th Asia-Pacific Symposium on Internetware","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73342699","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}
C programming language never performs automatic bounds checking in order to speed up execution. But bounds checking is absolutely necessary in any program. Because if a variable is out-of-bounds, some serious errors may occur during execution, such as endless loop or buffer overflows. When there are arrays used in a program, the index of an array must be within the boundary of the array. But programmers always miss the array bounds checking or do not perform a correct array bounds checking. In this paper, we perform static analysis based on taint analysis and data flow analysis to detect which arrays do not have correct array bounds checking in the program. And we implement an automatic static tool, Carraybound. And the experimental results show that Carraybound can work effectively and efficiently.
{"title":"Carraybound: static array bounds checking in C programs based on taint analysis","authors":"Fengjuan Gao, Tianjiao Chen, Yu Wang, Lingyun Situ, Linzhang Wang, Xuandong Li","doi":"10.1145/2993717.2993724","DOIUrl":"https://doi.org/10.1145/2993717.2993724","url":null,"abstract":"C programming language never performs automatic bounds checking in order to speed up execution. But bounds checking is absolutely necessary in any program. Because if a variable is out-of-bounds, some serious errors may occur during execution, such as endless loop or buffer overflows. When there are arrays used in a program, the index of an array must be within the boundary of the array. But programmers always miss the array bounds checking or do not perform a correct array bounds checking. In this paper, we perform static analysis based on taint analysis and data flow analysis to detect which arrays do not have correct array bounds checking in the program. And we implement an automatic static tool, Carraybound. And the experimental results show that Carraybound can work effectively and efficiently.","PeriodicalId":20631,"journal":{"name":"Proceedings of the 8th Asia-Pacific Symposium on Internetware","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83485971","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}
Jue Wang, Yepang Liu, Chang Xu, Xiaoxing Ma, Jian Lu
Energy inefficiency of smartphone apps is one of the important non-functional issues. It is common, but difficult to diagnose, and often involves sensor usage. GreenDroid provides a novel approach to systematically diagnose energy inefficiency problems in smartphone apps running on Android platforms. It derives an application execution model (AEM) from Android framework and leverages it to realistically simulate an application's runtime behaviors. It also automatically analyzes an application's sensory data utilization, monitors sensor listener and wake lock usage, and reports actionable information to developers. However, GreenDroid has several limitations. First, other than Android 2.3, it does not support other newer versions of Android. Second, GreenDroid doesn't provide an actionable and reusable state machine based on AEM. Third, its implementation and report generation need optimization. This work focuses on extending GreenDroid's functionality of diagnosing energy inefficiency problems in Android apps. We re-implement GreenDroid on the newest version of Java Pathfinder(JPF), update and optimize the execution simulation process as well as library modeling. Besides, this work adds support to new Android features such as Fragment, and abstracts a separate and reusable state machine out of AEM. With our evaluation, we demonstrate that the extended GreenDroid (E-GreenDroid) can analyze those apps with new Android features while being the same effective as the original version.
{"title":"E-greenDroid: effective energy inefficiency analysis for android applications","authors":"Jue Wang, Yepang Liu, Chang Xu, Xiaoxing Ma, Jian Lu","doi":"10.1145/2993717.2993720","DOIUrl":"https://doi.org/10.1145/2993717.2993720","url":null,"abstract":"Energy inefficiency of smartphone apps is one of the important non-functional issues. It is common, but difficult to diagnose, and often involves sensor usage. GreenDroid provides a novel approach to systematically diagnose energy inefficiency problems in smartphone apps running on Android platforms. It derives an application execution model (AEM) from Android framework and leverages it to realistically simulate an application's runtime behaviors. It also automatically analyzes an application's sensory data utilization, monitors sensor listener and wake lock usage, and reports actionable information to developers. However, GreenDroid has several limitations. First, other than Android 2.3, it does not support other newer versions of Android. Second, GreenDroid doesn't provide an actionable and reusable state machine based on AEM. Third, its implementation and report generation need optimization. This work focuses on extending GreenDroid's functionality of diagnosing energy inefficiency problems in Android apps. We re-implement GreenDroid on the newest version of Java Pathfinder(JPF), update and optimize the execution simulation process as well as library modeling. Besides, this work adds support to new Android features such as Fragment, and abstracts a separate and reusable state machine out of AEM. With our evaluation, we demonstrate that the extended GreenDroid (E-GreenDroid) can analyze those apps with new Android features while being the same effective as the original version.","PeriodicalId":20631,"journal":{"name":"Proceedings of the 8th Asia-Pacific Symposium on Internetware","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90420953","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}
Yi Jiang, Shijun Wang, Kai Fu, Wei Zhang, Haiyan Zhao
The conceptual model captures the key concepts in specific problem domains, as well as the important relationships between them. The quality of the conceptual model plays an important role for the success of software development. AAs restricted by personal knowledge and experience, a single modeler usually lacks of capability to build a high-quality conceptual model, especially when the problem domain has a high complexity. The large number of modelers online could help to solve this problem. However, the crowd modelers are temporal and topographical distributed and lack of interaction, which makes it hard for them modeling collaboratively. To address this problem, we developed a tool based on the stigmergy mechanism, which provides an indirect collaboration for online modelers. In this paper, we firstly introduce the architecture of our tool. Our tool helps to make up collaboration for those distributed online crowd through a merge-feedback process. Secondly, we introduce our entropy-based merging approach which is used to merge the models generated by different modelers. Two experiments are conducted to evaluate the feasibility of the merging approach and the stigmergy-based modeling tool.
{"title":"A collaborative conceptual modeling tool based on stigmergy mechanism","authors":"Yi Jiang, Shijun Wang, Kai Fu, Wei Zhang, Haiyan Zhao","doi":"10.1145/2993717.2993726","DOIUrl":"https://doi.org/10.1145/2993717.2993726","url":null,"abstract":"The conceptual model captures the key concepts in specific problem domains, as well as the important relationships between them. The quality of the conceptual model plays an important role for the success of software development. AAs restricted by personal knowledge and experience, a single modeler usually lacks of capability to build a high-quality conceptual model, especially when the problem domain has a high complexity. The large number of modelers online could help to solve this problem. However, the crowd modelers are temporal and topographical distributed and lack of interaction, which makes it hard for them modeling collaboratively. To address this problem, we developed a tool based on the stigmergy mechanism, which provides an indirect collaboration for online modelers. In this paper, we firstly introduce the architecture of our tool. Our tool helps to make up collaboration for those distributed online crowd through a merge-feedback process. Secondly, we introduce our entropy-based merging approach which is used to merge the models generated by different modelers. Two experiments are conducted to evaluate the feasibility of the merging approach and the stigmergy-based modeling tool.","PeriodicalId":20631,"journal":{"name":"Proceedings of the 8th Asia-Pacific Symposium on Internetware","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90730797","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 Internetware system is a complex and distributed self-adaptive system, which executes in an open, uncertain and dynamic environment, and adapts itself to changes in the environment. We hope that Internetware systems have the ability to automatically evolve in respond to changes. An important problem related to the development of Internetware systems is how to formulate proper adaptation rules. Because of the uncertainty of environment, the adaptation rules may not be suitable to the current system. Adaptation rules always need to be evolved to obtain better results. Some traditional methods can decide adaptation actions in different environmental conditions and evolve adaptation rules. But most of these methods bring about huge computation cost, which are not highly-efficient. To resolve these problems, we propose a method for evolving adaptation rules automatically, based on genetic algorithm and linear regression. We apply this method to evolve adaptation rules for a web application based on a widely used prototype --- RUBiS, which is an auction site similar to eBay. Experiments show that our method can evolve adaptation rules and improve the web application's performance in dynamic environment.
{"title":"A generative genetic algorithm for evolving adaptation rules of software systems","authors":"Yang Liu, Wei Zhang, Wenpin Jiao","doi":"10.1145/2993717.2993731","DOIUrl":"https://doi.org/10.1145/2993717.2993731","url":null,"abstract":"The Internetware system is a complex and distributed self-adaptive system, which executes in an open, uncertain and dynamic environment, and adapts itself to changes in the environment. We hope that Internetware systems have the ability to automatically evolve in respond to changes. An important problem related to the development of Internetware systems is how to formulate proper adaptation rules. Because of the uncertainty of environment, the adaptation rules may not be suitable to the current system. Adaptation rules always need to be evolved to obtain better results. Some traditional methods can decide adaptation actions in different environmental conditions and evolve adaptation rules. But most of these methods bring about huge computation cost, which are not highly-efficient. To resolve these problems, we propose a method for evolving adaptation rules automatically, based on genetic algorithm and linear regression. We apply this method to evolve adaptation rules for a web application based on a widely used prototype --- RUBiS, which is an auction site similar to eBay. Experiments show that our method can evolve adaptation rules and improve the web application's performance in dynamic environment.","PeriodicalId":20631,"journal":{"name":"Proceedings of the 8th Asia-Pacific Symposium on Internetware","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90044638","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 libraries have become more and more complex in recent years. Developers usually have to rely on search engines to find API documents and then select suitable APIs to do relevant development when working on unfamiliar functions. However, the traditional search engines do not focus on searching APIs that make this process inconvenient and time consuming. Although a lot of efforts have been made on API understanding and code search in industry and academia, work and tools that can recommend API methods to users based on their description of API's functionality are still very limited. In this paper, we propose a search-based recommendation algorithm on API methods. We call the algorithm APIBook and implement an API method recommendation tool based on the proposed algorithm. The algorithm can recommend relevant API methods to users based on user input written in natural language. This algorithm combines semantic relevance, type relevance and the extent of degree that API method is used to sort these API methods and rank those that are highly relevant and widely used in the top positions. Examples of codes in real projects are also provided to help users to learn and to understand the API method recommended. The API recommendation tool selects the Java Standard Library as well as 100 popular open source libraries as API recommending material. Users can input the API description via the Web interface, and view the search results with sample codes on screen. The evaluation experiment is performed and the result shows that APIBook is more effective for finding APIs than traditional search models and it takes on average 0.7 seconds for finding relevant API methods which we think to be reasonable for satisfying daily query requirements.
{"title":"APIBook: an effective approach for finding APIs","authors":"Haibo Yu, Wen Song, Tsunenori Mine","doi":"10.1145/2993717.2993727","DOIUrl":"https://doi.org/10.1145/2993717.2993727","url":null,"abstract":"Software libraries have become more and more complex in recent years. Developers usually have to rely on search engines to find API documents and then select suitable APIs to do relevant development when working on unfamiliar functions. However, the traditional search engines do not focus on searching APIs that make this process inconvenient and time consuming. Although a lot of efforts have been made on API understanding and code search in industry and academia, work and tools that can recommend API methods to users based on their description of API's functionality are still very limited. In this paper, we propose a search-based recommendation algorithm on API methods. We call the algorithm APIBook and implement an API method recommendation tool based on the proposed algorithm. The algorithm can recommend relevant API methods to users based on user input written in natural language. This algorithm combines semantic relevance, type relevance and the extent of degree that API method is used to sort these API methods and rank those that are highly relevant and widely used in the top positions. Examples of codes in real projects are also provided to help users to learn and to understand the API method recommended. The API recommendation tool selects the Java Standard Library as well as 100 popular open source libraries as API recommending material. Users can input the API description via the Web interface, and view the search results with sample codes on screen. The evaluation experiment is performed and the result shows that APIBook is more effective for finding APIs than traditional search models and it takes on average 0.7 seconds for finding relevant API methods which we think to be reasonable for satisfying daily query requirements.","PeriodicalId":20631,"journal":{"name":"Proceedings of the 8th Asia-Pacific Symposium on Internetware","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84132262","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}
While event logs generated by business processes play an increasingly significant role in business analysis, the quality of data remains a serious problem. Automatic recovery of dirty event logs is desirable and thus receives more attention. However, existing methods only focus on missing event recovery, or fall short of efficiency. To this end, we present Effa, a ProM plugin, to automatically recover event logs in the light of process specifications. Based on advanced heuristics including process decomposition and trace replaying to search the minimum recovery, Effa achieves a balance between repairing accuracy and efficiency.
{"title":"Effa: a proM plugin for recovering event logs","authors":"Xiaoxu Xia, Wei Song, Fangfei Chen, Xuansong Li, Pengcheng Zhang","doi":"10.1145/2993717.2993732","DOIUrl":"https://doi.org/10.1145/2993717.2993732","url":null,"abstract":"While event logs generated by business processes play an increasingly significant role in business analysis, the quality of data remains a serious problem. Automatic recovery of dirty event logs is desirable and thus receives more attention. However, existing methods only focus on missing event recovery, or fall short of efficiency. To this end, we present Effa, a ProM plugin, to automatically recover event logs in the light of process specifications. Based on advanced heuristics including process decomposition and trace replaying to search the minimum recovery, Effa achieves a balance between repairing accuracy and efficiency.","PeriodicalId":20631,"journal":{"name":"Proceedings of the 8th Asia-Pacific Symposium on Internetware","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81462475","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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