This paper presents the iMPAcT tool that tests recurring behaviour, i.e., UI Patterns, on mobile applications. This tool is implemented in Java and makes use of Android's APIs UI Automator and UiAutomation. The tool automatically explores a mobile application in order to automatically identify and test UI Patterns. Each UI Pattern has a test strategy, Test Patterns, associated, which is applied when an UI Pattern is found. The approach works on top of a catalogue of UI Patterns, which determines which UI Patterns are to be tested, and what should their correct behaviour be, and may be used for any application.
{"title":"The iMPAcT Tool: Testing UI Patterns on Mobile Applications","authors":"Ines Coimbra Morgado, A. C. Paiva","doi":"10.1109/ASE.2015.96","DOIUrl":"https://doi.org/10.1109/ASE.2015.96","url":null,"abstract":"This paper presents the iMPAcT tool that tests recurring behaviour, i.e., UI Patterns, on mobile applications. This tool is implemented in Java and makes use of Android's APIs UI Automator and UiAutomation. The tool automatically explores a mobile application in order to automatically identify and test UI Patterns. Each UI Pattern has a test strategy, Test Patterns, associated, which is applied when an UI Pattern is found. The approach works on top of a catalogue of UI Patterns, which determines which UI Patterns are to be tested, and what should their correct behaviour be, and may be used for any application.","PeriodicalId":6586,"journal":{"name":"2015 30th IEEE/ACM International Conference on Automated Software Engineering (ASE)","volume":"37 1","pages":"876-881"},"PeriodicalIF":0.0,"publicationDate":"2015-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73191232","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 explore a novel model of computation based on nodes that have no public addresses (ids). We define nodes as concurrent, message-passing computational entities in an abstract communication medium, similar to the Actor model, but with all public node ids elided. Instead, drawing inspiration from biological systems, we postulate a send-to-behavior language construct to enable anonymous one-way communication. A behavior, defined as a function of input to actions, is also an intensional definition of the subset of nodes that express it. Sending to a behavior is defined to deliver the message to one or more nodes that implement that behavior.
{"title":"A Message-Passing Architecture without Public Ids Using Send-to-Behavior","authors":"E. Wang, Z. Dang","doi":"10.1109/ASE.2015.79","DOIUrl":"https://doi.org/10.1109/ASE.2015.79","url":null,"abstract":"We explore a novel model of computation based on nodes that have no public addresses (ids). We define nodes as concurrent, message-passing computational entities in an abstract communication medium, similar to the Actor model, but with all public node ids elided. Instead, drawing inspiration from biological systems, we postulate a send-to-behavior language construct to enable anonymous one-way communication. A behavior, defined as a function of input to actions, is also an intensional definition of the subset of nodes that express it. Sending to a behavior is defined to deliver the message to one or more nodes that implement that behavior.","PeriodicalId":6586,"journal":{"name":"2015 30th IEEE/ACM International Conference on Automated Software Engineering (ASE)","volume":"72 1","pages":"902-905"},"PeriodicalIF":0.0,"publicationDate":"2015-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74065013","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}
Bug localization refers to the automated process of locating the potential buggy files for a given bug report. To help developers focus their attention to those files is crucial. Several existing automated approaches for bug localization from a bug report face a key challenge, called lexical mismatch, in which the terms used in bug reports to describe a bug are different from the terms and code tokens used in source files. This paper presents a novel approach that uses deep neural network (DNN) in combination with rVSM, an information retrieval (IR) technique. rVSM collects the feature on the textual similarity between bug reports and source files. DNN is used to learn to relate the terms in bug reports to potentially different code tokens and terms in source files and documentation if they appear frequently enough in the pairs of reports and buggy files. Our empirical evaluation on real-world projects shows that DNN and IR complement well to each other to achieve higher bug localization accuracy than individual models. Importantly, our new model, HyLoc, with a combination of the features built from DNN, rVSM, and project's bug-fixing history, achieves higher accuracy than the state-of-the-art IR and machine learning techniques. In half of the cases, it is correct with just a single suggested file. Two out of three cases, a correct buggy file is in the list of three suggested files.
{"title":"Combining Deep Learning with Information Retrieval to Localize Buggy Files for Bug Reports (N)","authors":"A. Lam, A. Nguyen, H. Nguyen, T. Nguyen","doi":"10.1109/ASE.2015.73","DOIUrl":"https://doi.org/10.1109/ASE.2015.73","url":null,"abstract":"Bug localization refers to the automated process of locating the potential buggy files for a given bug report. To help developers focus their attention to those files is crucial. Several existing automated approaches for bug localization from a bug report face a key challenge, called lexical mismatch, in which the terms used in bug reports to describe a bug are different from the terms and code tokens used in source files. This paper presents a novel approach that uses deep neural network (DNN) in combination with rVSM, an information retrieval (IR) technique. rVSM collects the feature on the textual similarity between bug reports and source files. DNN is used to learn to relate the terms in bug reports to potentially different code tokens and terms in source files and documentation if they appear frequently enough in the pairs of reports and buggy files. Our empirical evaluation on real-world projects shows that DNN and IR complement well to each other to achieve higher bug localization accuracy than individual models. Importantly, our new model, HyLoc, with a combination of the features built from DNN, rVSM, and project's bug-fixing history, achieves higher accuracy than the state-of-the-art IR and machine learning techniques. In half of the cases, it is correct with just a single suggested file. Two out of three cases, a correct buggy file is in the list of three suggested files.","PeriodicalId":6586,"journal":{"name":"2015 30th IEEE/ACM International Conference on Automated Software Engineering (ASE)","volume":"47 1","pages":"476-481"},"PeriodicalIF":0.0,"publicationDate":"2015-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73519776","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}
Shin Hong, Byeongcheol Lee, Taehoon Kwak, Yiru Jeon, Bongsuk Ko, Yunho Kim, Moonzoo Kim
Programmers maintain and evolve their software in a variety of programming languages to take advantage of various control/data abstractions and legacy libraries. The programming language ecosystem has diversified over the last few decades, and non-trivial programs are likely to be written in more than a single language. Unfortunately, language interfaces such as Java Native Interface and Python/C are difficult to use correctly and the scope of fault localization goes beyond language boundaries, which makes debugging multilingual bugs challenging. To overcome the aforementioned limitations, we propose a mutation-based fault localization technique for real-world multilingual programs. To improve the accuracy of locating multilingual bugs, we have developed and applied new mutation operators as well as conventional mutation operators. The results of the empirical evaluation for six non-trivial real-world multilingual bugs are promising in that the proposed technique identifies the buggy statements as the most suspicious statements for all six bugs.
{"title":"Mutation-Based Fault Localization for Real-World Multilingual Programs (T)","authors":"Shin Hong, Byeongcheol Lee, Taehoon Kwak, Yiru Jeon, Bongsuk Ko, Yunho Kim, Moonzoo Kim","doi":"10.1109/ASE.2015.14","DOIUrl":"https://doi.org/10.1109/ASE.2015.14","url":null,"abstract":"Programmers maintain and evolve their software in a variety of programming languages to take advantage of various control/data abstractions and legacy libraries. The programming language ecosystem has diversified over the last few decades, and non-trivial programs are likely to be written in more than a single language. Unfortunately, language interfaces such as Java Native Interface and Python/C are difficult to use correctly and the scope of fault localization goes beyond language boundaries, which makes debugging multilingual bugs challenging. To overcome the aforementioned limitations, we propose a mutation-based fault localization technique for real-world multilingual programs. To improve the accuracy of locating multilingual bugs, we have developed and applied new mutation operators as well as conventional mutation operators. The results of the empirical evaluation for six non-trivial real-world multilingual bugs are promising in that the proposed technique identifies the buggy statements as the most suspicious statements for all six bugs.","PeriodicalId":6586,"journal":{"name":"2015 30th IEEE/ACM International Conference on Automated Software Engineering (ASE)","volume":"50 1","pages":"464-475"},"PeriodicalIF":0.0,"publicationDate":"2015-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81128724","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}
D. Bozhinoski, D. D. Ruscio, I. Malavolta, Patrizio Pelliccione, Massimo Tivoli
Multicopters are increasingly popular since they promise to simplify a myriad of everyday tasks. Currently, vendors provide low-level APIs and basic primitives to program multicopters, making mission development a task-specific and error-prone activity. As a consequence, current approaches are affordable only for users that have a strong technical expertise. Then, software engineering techniques are needed to support the definition, development, and realization of missions at the right level of abstraction and involving teams of autonomous multicopters that guarantee the safety today's users expect. In this paper we describe a tool that enables end-users with no technical expertise, e.g., firefighters and rescue workers, to specify missions for a team of multicopters. The detailed flight plan that each multicopter must perform to accomplish the specified mission is automatically generated by preventing collisions between multicopters and obstacles, and ensuring the preservation of no-fly zones.
{"title":"FLYAQ: Enabling Non-expert Users to Specify and Generate Missions of Autonomous Multicopters","authors":"D. Bozhinoski, D. D. Ruscio, I. Malavolta, Patrizio Pelliccione, Massimo Tivoli","doi":"10.1109/ASE.2015.104","DOIUrl":"https://doi.org/10.1109/ASE.2015.104","url":null,"abstract":"Multicopters are increasingly popular since they promise to simplify a myriad of everyday tasks. Currently, vendors provide low-level APIs and basic primitives to program multicopters, making mission development a task-specific and error-prone activity. As a consequence, current approaches are affordable only for users that have a strong technical expertise. Then, software engineering techniques are needed to support the definition, development, and realization of missions at the right level of abstraction and involving teams of autonomous multicopters that guarantee the safety today's users expect. In this paper we describe a tool that enables end-users with no technical expertise, e.g., firefighters and rescue workers, to specify missions for a team of multicopters. The detailed flight plan that each multicopter must perform to accomplish the specified mission is automatically generated by preventing collisions between multicopters and obstacles, and ensuring the preservation of no-fly zones.","PeriodicalId":6586,"journal":{"name":"2015 30th IEEE/ACM International Conference on Automated Software Engineering (ASE)","volume":"5 5 1","pages":"801-806"},"PeriodicalIF":0.0,"publicationDate":"2015-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81225528","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}
Developers use many software applications to process large amounts of diverse information in their daily work. The information is usually meaningful beyond the context of an application that manages it. However, as different applications function independently, developers have to manually track, correlate and re-find cross-cutting information across separate applications. We refer to this difficulty as information fragmentation problem. In this paper, we present ActivitySpace, an interapplication activity tracking and analysis framework for tackling information fragmentation problem in software development. ActivitySpace can monitor the developer's activity in many applications at a low enough level to obviate application-specific support while accounting for the ways by which low-level activity information can be effectively aggregated to reflect the developer's activity at higher-level of abstraction. A system prototype has been implemented on Microsoft Windows. Our preliminary user study showed that the ActivitySpace system is promising in supporting interapplication information needs in developers' daily work.
{"title":"Tracking and Analyzing Cross-Cutting Activities in Developers' Daily Work (N)","authors":"Lingfeng Bao, Zhenchang Xing, Xinyu Wang, Bo Zhou","doi":"10.1109/ASE.2015.43","DOIUrl":"https://doi.org/10.1109/ASE.2015.43","url":null,"abstract":"Developers use many software applications to process large amounts of diverse information in their daily work. The information is usually meaningful beyond the context of an application that manages it. However, as different applications function independently, developers have to manually track, correlate and re-find cross-cutting information across separate applications. We refer to this difficulty as information fragmentation problem. In this paper, we present ActivitySpace, an interapplication activity tracking and analysis framework for tackling information fragmentation problem in software development. ActivitySpace can monitor the developer's activity in many applications at a low enough level to obviate application-specific support while accounting for the ways by which low-level activity information can be effectively aggregated to reflect the developer's activity at higher-level of abstraction. A system prototype has been implemented on Microsoft Windows. Our preliminary user study showed that the ActivitySpace system is promising in supporting interapplication information needs in developers' daily work.","PeriodicalId":6586,"journal":{"name":"2015 30th IEEE/ACM International Conference on Automated Software Engineering (ASE)","volume":"1 1","pages":"277-282"},"PeriodicalIF":0.0,"publicationDate":"2015-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83866198","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}
Shengqian Yang, Hailong Zhang, Haowei Wu, Yan Wang, Dacong Yan, A. Rountev
This work develops a static analysis to create a model of the behavior of an Android application's GUI. We propose the window transition graph (WTG), a model representing the possible GUI window sequences and their associated events and callbacks. A key component and contribution of our work is the careful modeling of the stack of currently-active windows, the changes to this stack, and the effects of callbacks related to these changes. To the best of our knowledge, this is the first detailed study of this important static analysis problem for Android. We develop novel analysis algorithms for WTG construction and traversal, based on this modeling of the window stack. We also describe an application of the WTG for GUI test generation, using path traversals. The evaluation of the proposed algorithms indicates their effectiveness and practicality.
{"title":"Static Window Transition Graphs for Android (T)","authors":"Shengqian Yang, Hailong Zhang, Haowei Wu, Yan Wang, Dacong Yan, A. Rountev","doi":"10.1109/ASE.2015.76","DOIUrl":"https://doi.org/10.1109/ASE.2015.76","url":null,"abstract":"This work develops a static analysis to create a model of the behavior of an Android application's GUI. We propose the window transition graph (WTG), a model representing the possible GUI window sequences and their associated events and callbacks. A key component and contribution of our work is the careful modeling of the stack of currently-active windows, the changes to this stack, and the effects of callbacks related to these changes. To the best of our knowledge, this is the first detailed study of this important static analysis problem for Android. We develop novel analysis algorithms for WTG construction and traversal, based on this modeling of the window stack. We also describe an application of the WTG for GUI test generation, using path traversals. The evaluation of the proposed algorithms indicates their effectiveness and practicality.","PeriodicalId":6586,"journal":{"name":"2015 30th IEEE/ACM International Conference on Automated Software Engineering (ASE)","volume":"16 1","pages":"658-668"},"PeriodicalIF":0.0,"publicationDate":"2015-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88189785","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 engineering meta-data (SE data), such as revision control data, Github project data or test reports, is typically semi-structured, it comprises a mixture of formatted and free-text fields and is often self-describing. Semi-structured SE data cannot be queried in a SQL-like manner because of its lack of structure. Consequently, there are a variety of customized tools built to analyze specific datasets but these do not generalize. We propose to develop a generic framework for exploration and querying of semi-structured SE data. Our approach investigates the use of a formal concept lattice as a universal data structure and a tag cloud as an intuitive interface to support data exploration.
{"title":"A Generic Framework for Concept-Based Exploration of Semi-Structured Software Engineering Data","authors":"Gillian J. Greene","doi":"10.1109/ASE.2015.34","DOIUrl":"https://doi.org/10.1109/ASE.2015.34","url":null,"abstract":"Software engineering meta-data (SE data), such as revision control data, Github project data or test reports, is typically semi-structured, it comprises a mixture of formatted and free-text fields and is often self-describing. Semi-structured SE data cannot be queried in a SQL-like manner because of its lack of structure. Consequently, there are a variety of customized tools built to analyze specific datasets but these do not generalize. We propose to develop a generic framework for exploration and querying of semi-structured SE data. Our approach investigates the use of a formal concept lattice as a universal data structure and a tag cloud as an intuitive interface to support data exploration.","PeriodicalId":6586,"journal":{"name":"2015 30th IEEE/ACM International Conference on Automated Software Engineering (ASE)","volume":"41 1","pages":"894-897"},"PeriodicalIF":0.0,"publicationDate":"2015-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77122921","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}
Prior research shows that directly applying phrase-based SMT on lexical tokens to migrate Java to C# produces much semantically incorrect code. A key limitation is the use of sequences in phrase-based SMT to model and translate source code with well-formed structures. We propose mppSMT, a divide-and-conquer technique to address that with novel training and migration algorithms using phrase-based SMT in three phases. First, mppSMT treats a program as a sequence of syntactic units and maps/translates such sequences in two languages to one another. Second, with a syntax-directed fashion, it deals with the tokens within syntactic units by encoding them with semantic symbols to represent their data and token types. This encoding via semantic symbols helps better migration of API usages. Third, the lexical tokens corresponding to each sememe are mapped or migrated. The resulting sequences of tokens are merged together to form the final migrated code. Such divide-and-conquer and syntax-direction strategies enable phrase-based SMT to adapt well to syntactical structures in source code, thus, improving migration accuracy. Our empirical evaluation on several real-world systems shows that 84.8 -- 97.9% and 70 -- 83% of the migrated methods are syntactically and semantically correct, respectively. 26.3 -- 51.2% of total migrated methods are exactly matched to the human-written C# code in the oracle. Compared to Java2CSharp, a rule-based migration tool, it achieves higher semantic accuracy from 6.6 -- 57.7% relatively. Importantly, it does not require manual labeling for training data or manual definition of rules.
{"title":"Divide-and-Conquer Approach for Multi-phase Statistical Migration for Source Code (T)","authors":"A. Nguyen, T. Nguyen, T. Nguyen","doi":"10.1109/ASE.2015.74","DOIUrl":"https://doi.org/10.1109/ASE.2015.74","url":null,"abstract":"Prior research shows that directly applying phrase-based SMT on lexical tokens to migrate Java to C# produces much semantically incorrect code. A key limitation is the use of sequences in phrase-based SMT to model and translate source code with well-formed structures. We propose mppSMT, a divide-and-conquer technique to address that with novel training and migration algorithms using phrase-based SMT in three phases. First, mppSMT treats a program as a sequence of syntactic units and maps/translates such sequences in two languages to one another. Second, with a syntax-directed fashion, it deals with the tokens within syntactic units by encoding them with semantic symbols to represent their data and token types. This encoding via semantic symbols helps better migration of API usages. Third, the lexical tokens corresponding to each sememe are mapped or migrated. The resulting sequences of tokens are merged together to form the final migrated code. Such divide-and-conquer and syntax-direction strategies enable phrase-based SMT to adapt well to syntactical structures in source code, thus, improving migration accuracy. Our empirical evaluation on several real-world systems shows that 84.8 -- 97.9% and 70 -- 83% of the migrated methods are syntactically and semantically correct, respectively. 26.3 -- 51.2% of total migrated methods are exactly matched to the human-written C# code in the oracle. Compared to Java2CSharp, a rule-based migration tool, it achieves higher semantic accuracy from 6.6 -- 57.7% relatively. Importantly, it does not require manual labeling for training data or manual definition of rules.","PeriodicalId":6586,"journal":{"name":"2015 30th IEEE/ACM International Conference on Automated Software Engineering (ASE)","volume":"48 1","pages":"585-596"},"PeriodicalIF":0.0,"publicationDate":"2015-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74093855","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}
Jinkun Lin, Chuan Luo, Shaowei Cai, Kaile Su, Dan Hao, Lu Zhang
Covering arrays (CAs) are often used as test suites for combinatorial interaction testing to discover interaction faults of real-world systems. Most real-world systems involve constraints, so improving algorithms for covering array generation (CAG) with constraints is beneficial. Two popular methods for constrained CAG are greedy construction and meta-heuristic search. Recently, a meta-heuristic framework called two-mode local search has shown great success in solving classic NPhard problems. We are interested whether this method is also powerful in solving the constrained CAG problem. This work proposes a two-mode meta-heuristic framework for constrained CAG efficiently and presents a new meta-heuristic algorithm called TCA. Experiments show that TCA significantly outperforms state-of-the-art solvers on 3-way constrained CAG. Further experiments demonstrate that TCA also performs much better than its competitors on 2-way constrained CAG.
{"title":"TCA: An Efficient Two-Mode Meta-Heuristic Algorithm for Combinatorial Test Generation (T)","authors":"Jinkun Lin, Chuan Luo, Shaowei Cai, Kaile Su, Dan Hao, Lu Zhang","doi":"10.1109/ASE.2015.61","DOIUrl":"https://doi.org/10.1109/ASE.2015.61","url":null,"abstract":"Covering arrays (CAs) are often used as test suites for combinatorial interaction testing to discover interaction faults of real-world systems. Most real-world systems involve constraints, so improving algorithms for covering array generation (CAG) with constraints is beneficial. Two popular methods for constrained CAG are greedy construction and meta-heuristic search. Recently, a meta-heuristic framework called two-mode local search has shown great success in solving classic NPhard problems. We are interested whether this method is also powerful in solving the constrained CAG problem. This work proposes a two-mode meta-heuristic framework for constrained CAG efficiently and presents a new meta-heuristic algorithm called TCA. Experiments show that TCA significantly outperforms state-of-the-art solvers on 3-way constrained CAG. Further experiments demonstrate that TCA also performs much better than its competitors on 2-way constrained CAG.","PeriodicalId":6586,"journal":{"name":"2015 30th IEEE/ACM International Conference on Automated Software Engineering (ASE)","volume":"4 1","pages":"494-505"},"PeriodicalIF":0.0,"publicationDate":"2015-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80280013","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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