Pub Date : 2015-03-02DOI: 10.1109/SANER.2015.7081847
Hayatou Oumarou, N. Anquetil, Anne Etien, Stéphane Ducasse, D. T. Kolyang
We study good programming practices expressed in rules and detected by static analysis checkers such as PMD or FindBugs. To understand how violations to these rules are corrected and whether this can be automated, we need to identify in the source code where they appear and how they were fixed. This presents some similarities with research on understanding software bugs, their causes, their fixes, and how they could be avoided. The traditional method to identify how a bug or a rule violation were fixed consists in finding the commit that contains this fix and identifying what was changed in this commit. If the commit is small, all the lines changed are ascribed to the fixing of the rule violation or the bug. However, commits are not always atomic, and several fixes and even enhancements can be mixed in a single one (a large commit). In this case, it is impossible to detect which modifications contribute to which fix. In this paper, we are proposing a method that identifies precisely the modifications that are related to the correction of a rule violation. The same method could be applied to bug fixes, providing there is a test illustrating this bug. We validate our solution on a real world system and actual rules.
{"title":"Identifying the exact fixing actions of static rule violation","authors":"Hayatou Oumarou, N. Anquetil, Anne Etien, Stéphane Ducasse, D. T. Kolyang","doi":"10.1109/SANER.2015.7081847","DOIUrl":"https://doi.org/10.1109/SANER.2015.7081847","url":null,"abstract":"We study good programming practices expressed in rules and detected by static analysis checkers such as PMD or FindBugs. To understand how violations to these rules are corrected and whether this can be automated, we need to identify in the source code where they appear and how they were fixed. This presents some similarities with research on understanding software bugs, their causes, their fixes, and how they could be avoided. The traditional method to identify how a bug or a rule violation were fixed consists in finding the commit that contains this fix and identifying what was changed in this commit. If the commit is small, all the lines changed are ascribed to the fixing of the rule violation or the bug. However, commits are not always atomic, and several fixes and even enhancements can be mixed in a single one (a large commit). In this case, it is impossible to detect which modifications contribute to which fix. In this paper, we are proposing a method that identifies precisely the modifications that are related to the correction of a rule violation. The same method could be applied to bug fixes, providing there is a test illustrating this bug. We validate our solution on a real world system and actual rules.","PeriodicalId":355949,"journal":{"name":"2015 IEEE 22nd International Conference on Software Analysis, Evolution, and Reengineering (SANER)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132150408","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}
Pub Date : 2015-03-02DOI: 10.1109/SANER.2015.7081863
Miguel Garzón, Hamoud Aljamaan, T. Lethbridge
Huge benefits are gained when Model Driven Engineering are adopted to develop software systems. However, it remains a challenge for software modelers to embrace the MDE approach. In this paper, we present Umple, a framework for Model Driven Development in Object-Oriented Systems that can be used to generate entire software systems (Model Driven Forward Engineering) or to recover the models from existing software systems (Model Driven Reverse Engineering). Umple models are written using a friendly human-readable modeling notation seamlessly integrated with algorithmic code. In other words, we present a model-is-the-code approach, where developers are more likely to maintain and evolve the code as the system matures simply by the fact that both model and code are integrated as aspects of the same system. Finally, we demonstrate how the framework can be used to elaborate on solutions supporting different scenarios such as software modernization and program comprehension.
{"title":"Umple: A framework for Model Driven Development of Object-Oriented Systems","authors":"Miguel Garzón, Hamoud Aljamaan, T. Lethbridge","doi":"10.1109/SANER.2015.7081863","DOIUrl":"https://doi.org/10.1109/SANER.2015.7081863","url":null,"abstract":"Huge benefits are gained when Model Driven Engineering are adopted to develop software systems. However, it remains a challenge for software modelers to embrace the MDE approach. In this paper, we present Umple, a framework for Model Driven Development in Object-Oriented Systems that can be used to generate entire software systems (Model Driven Forward Engineering) or to recover the models from existing software systems (Model Driven Reverse Engineering). Umple models are written using a friendly human-readable modeling notation seamlessly integrated with algorithmic code. In other words, we present a model-is-the-code approach, where developers are more likely to maintain and evolve the code as the system matures simply by the fact that both model and code are integrated as aspects of the same system. Finally, we demonstrate how the framework can be used to elaborate on solutions supporting different scenarios such as software modernization and program comprehension.","PeriodicalId":355949,"journal":{"name":"2015 IEEE 22nd International Conference on Software Analysis, Evolution, and Reengineering (SANER)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124870335","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}
Pub Date : 2015-03-02DOI: 10.1109/SANER.2015.7081823
Tommaso Dal Sasso, Andrea Mocci, Michele Lanza
During software development, exceptions are by no means exceptional: Programmers repeatedly try and test their code to ensure that it works as expected. While doing so, runtime exceptions are raised, pointing out various issues, such as inappropriate usage of an API, convoluted code, as well as defects. Such failures result in stack traces, lists composed of the sequence of method invocations that led to the interruption of the program. Stack traces are useful to debug source code, and if shared also enhance the quality of bug reports. However, they are handled manually and individually, while we argue that they can be leveraged automatically and collectively to enable what we call crowdstacking, the automated collection of stack traces on the scale of a whole development community. We present our crowdstacking approach, supported by Shore-Line Reporter, a tool which seamlessly collects stack traces during program development and execution and stores them on a central repository. We illustrate how thousands of stack traces stemming from the IDEs of several developers can be leveraged to identify common hot spots in the code that are involved in failures, using this knowledge to retrieve relevant and related bug reports and to provide an effective, instant context of the problem to the developer.
{"title":"Misery loves company: CrowdStacking traces to aid problem detection","authors":"Tommaso Dal Sasso, Andrea Mocci, Michele Lanza","doi":"10.1109/SANER.2015.7081823","DOIUrl":"https://doi.org/10.1109/SANER.2015.7081823","url":null,"abstract":"During software development, exceptions are by no means exceptional: Programmers repeatedly try and test their code to ensure that it works as expected. While doing so, runtime exceptions are raised, pointing out various issues, such as inappropriate usage of an API, convoluted code, as well as defects. Such failures result in stack traces, lists composed of the sequence of method invocations that led to the interruption of the program. Stack traces are useful to debug source code, and if shared also enhance the quality of bug reports. However, they are handled manually and individually, while we argue that they can be leveraged automatically and collectively to enable what we call crowdstacking, the automated collection of stack traces on the scale of a whole development community. We present our crowdstacking approach, supported by Shore-Line Reporter, a tool which seamlessly collects stack traces during program development and execution and stores them on a central repository. We illustrate how thousands of stack traces stemming from the IDEs of several developers can be leveraged to identify common hot spots in the code that are involved in failures, using this knowledge to retrieve relevant and related bug reports and to provide an effective, instant context of the problem to the developer.","PeriodicalId":355949,"journal":{"name":"2015 IEEE 22nd International Conference on Software Analysis, Evolution, and Reengineering (SANER)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126077920","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}
Pub Date : 2015-03-02DOI: 10.1109/SANER.2015.7081836
Jing Qiu, Xiaohong Su, Peijun Ma
Library functions identification is a key technique in reverse engineering. Discontinuity and polymorphism of inline and optimized library functions in binary code create a difficult challenge for library functions identification. To solve this problem, a novel approach is developed to identify library functions. First, we introduce execution dependence graphs (EDGs) to describe the behavior characteristics of binary code. Then, by finding similar EDG subgraphs in target functions, we identify both full and inline library functions. Experimental results from the prototype tool show that the proposed method is not only capable of identifying inline functions but is also more efficient and precise than the current methods for identifying full library functions.
{"title":"Library functions identification in binary code by using graph isomorphism testings","authors":"Jing Qiu, Xiaohong Su, Peijun Ma","doi":"10.1109/SANER.2015.7081836","DOIUrl":"https://doi.org/10.1109/SANER.2015.7081836","url":null,"abstract":"Library functions identification is a key technique in reverse engineering. Discontinuity and polymorphism of inline and optimized library functions in binary code create a difficult challenge for library functions identification. To solve this problem, a novel approach is developed to identify library functions. First, we introduce execution dependence graphs (EDGs) to describe the behavior characteristics of binary code. Then, by finding similar EDG subgraphs in target functions, we identify both full and inline library functions. Experimental results from the prototype tool show that the proposed method is not only capable of identifying inline functions but is also more efficient and precise than the current methods for identifying full library functions.","PeriodicalId":355949,"journal":{"name":"2015 IEEE 22nd International Conference on Software Analysis, Evolution, and Reengineering (SANER)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116372355","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}
Pub Date : 2015-03-02DOI: 10.1109/SANER.2015.7081817
Leonardo Humberto Silva, Miguel Ramos, M. T. Valente, Alexandre Bergel, N. Anquetil
JavaScript is the de facto programming language for the Web. It is used to implement mail clients, office applications, or IDEs, that can weight hundreds of thousands of lines of code. The language itself is prototype based, but to master the complexity of their application, practitioners commonly rely on informal class abstractions. This practice has never been the target of empirical research in JavaScript. Yet, understanding it is key to adequately tuning programming environments and structure libraries such that they are accessible to programmers. In this paper we report on a large and in-depth study to understand how class emulation is employed in JavaScript applications. We propose a strategy to statically detect class-based abstractions in the source code of JavaScript systems. We used this strategy in a dataset of 50 popular JavaScript applications available from GitHub. We found four types of JavaScript software: class-free (systems that do not make any usage of classes), class-aware (systems that use classes, but marginally), class-friendly (systems that make a relevant usage of classes), and class-oriented (systems that have most of their data structures implemented as classes). The systems in these categories represent, respectively, 26%, 36%, 30%, and 8% of the systems we studied.
{"title":"Does JavaScript software embrace classes?","authors":"Leonardo Humberto Silva, Miguel Ramos, M. T. Valente, Alexandre Bergel, N. Anquetil","doi":"10.1109/SANER.2015.7081817","DOIUrl":"https://doi.org/10.1109/SANER.2015.7081817","url":null,"abstract":"JavaScript is the de facto programming language for the Web. It is used to implement mail clients, office applications, or IDEs, that can weight hundreds of thousands of lines of code. The language itself is prototype based, but to master the complexity of their application, practitioners commonly rely on informal class abstractions. This practice has never been the target of empirical research in JavaScript. Yet, understanding it is key to adequately tuning programming environments and structure libraries such that they are accessible to programmers. In this paper we report on a large and in-depth study to understand how class emulation is employed in JavaScript applications. We propose a strategy to statically detect class-based abstractions in the source code of JavaScript systems. We used this strategy in a dataset of 50 popular JavaScript applications available from GitHub. We found four types of JavaScript software: class-free (systems that do not make any usage of classes), class-aware (systems that use classes, but marginally), class-friendly (systems that make a relevant usage of classes), and class-oriented (systems that have most of their data structures implemented as classes). The systems in these categories represent, respectively, 26%, 36%, 30%, and 8% of the systems we studied.","PeriodicalId":355949,"journal":{"name":"2015 IEEE 22nd International Conference on Software Analysis, Evolution, and Reengineering (SANER)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116824224","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}
Pub Date : 2015-03-02DOI: 10.1109/SANER.2015.7081891
Rodrigo Morales
One of the biggest concerns in software maintenance is design quality; poor design hinders software maintenance and evolution. One way to improve design quality is to detect and correct anti-patterns (i.e., poor solutions to design and implementation problems), for example through refactorings. There are several approaches to detect anti-patterns, that rely on metrics and structural properties. However, finding a specific solution to remove anti-patterns is a challenging task as candidate refactorings can be conflicting and their number very large, making it costly. Hence, development teams often have to prioritize the refactorings to be applied on a system. In addition to this, refactoring is risky, since non-experienced developers can change the behaviour of a system, without a comprehensive test suite. Therefore, there is a need for tools that can automatically remove anti-patterns. We will apply meta-heuristics to propose a technique for automated refactoring that improves design quality.
{"title":"Towards a framework for automatic correction of anti-patterns","authors":"Rodrigo Morales","doi":"10.1109/SANER.2015.7081891","DOIUrl":"https://doi.org/10.1109/SANER.2015.7081891","url":null,"abstract":"One of the biggest concerns in software maintenance is design quality; poor design hinders software maintenance and evolution. One way to improve design quality is to detect and correct anti-patterns (i.e., poor solutions to design and implementation problems), for example through refactorings. There are several approaches to detect anti-patterns, that rely on metrics and structural properties. However, finding a specific solution to remove anti-patterns is a challenging task as candidate refactorings can be conflicting and their number very large, making it costly. Hence, development teams often have to prioritize the refactorings to be applied on a system. In addition to this, refactoring is risky, since non-experienced developers can change the behaviour of a system, without a comprehensive test suite. Therefore, there is a need for tools that can automatically remove anti-patterns. We will apply meta-heuristics to propose a technique for automated refactoring that improves design quality.","PeriodicalId":355949,"journal":{"name":"2015 IEEE 22nd International Conference on Software Analysis, Evolution, and Reengineering (SANER)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115063053","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}
When performing software maintenance tasks, developers often need to understand a series of background knowledge based on information distributed in different software repositories such as source codes, version control systems and bug tracking systems. An effective way to support developers to understand such knowledge is to provide an integrated knowledge base and allow them to ask questions using natural language. Existing approaches cannot well support natural language questions that involve a series of conceptual relationships and are phrased in a flexible way. In this paper, we propose an interactive approach for understanding developers' natural language queries. The approach can understand a developer's natural language questions phrased in different ways by generating a set of ranked and human-readable candidate questions and getting feedback from the developer. Based on the candidate question confirmed by the developer, the approach can then synthesize an answer by constructing and executing a structural query to the knowledge base. We have implemented a tool following the proposed approach and conducted a user study using the tool. The results show that our approach can help developers get the desired answers more easily and accurately.
{"title":"Understanding developers' natural language queries with interactive clarification","authors":"Shihai Jiang, Liwei Shen, Xin Peng, Zhaojin Lv, Wenyun Zhao","doi":"10.1109/SANER.2015.7081811","DOIUrl":"https://doi.org/10.1109/SANER.2015.7081811","url":null,"abstract":"When performing software maintenance tasks, developers often need to understand a series of background knowledge based on information distributed in different software repositories such as source codes, version control systems and bug tracking systems. An effective way to support developers to understand such knowledge is to provide an integrated knowledge base and allow them to ask questions using natural language. Existing approaches cannot well support natural language questions that involve a series of conceptual relationships and are phrased in a flexible way. In this paper, we propose an interactive approach for understanding developers' natural language queries. The approach can understand a developer's natural language questions phrased in different ways by generating a set of ranked and human-readable candidate questions and getting feedback from the developer. Based on the candidate question confirmed by the developer, the approach can then synthesize an answer by constructing and executing a structural query to the knowledge base. We have implemented a tool following the proposed approach and conducted a user study using the tool. The results show that our approach can help developers get the desired answers more easily and accurately.","PeriodicalId":355949,"journal":{"name":"2015 IEEE 22nd International Conference on Software Analysis, Evolution, and Reengineering (SANER)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124409994","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}
Pub Date : 2015-03-02DOI: 10.1109/SANER.2015.7081869
R. Kula, D. Germán, T. Ishio, Katsuro Inoue
With the popularity of open source library (re)use in both industrial and open source settings, `trust' plays vital role in third-party library adoption. Trust involves the assumption of both functional and non-functional correctness. Even with the aid of dependency management build tools such as Maven and Gradle, research have still found a latency to trust the latest release of a library. In this paper, we investigate the trust of OSS libraries. Our study of 6,374 systems in Maven Super Repository suggests that 82% of systems are more trusting of adopting the latest library release to existing systems. We uncover the impact of maven on latent and trusted library adoptions.
{"title":"Trusting a library: A study of the latency to adopt the latest Maven release","authors":"R. Kula, D. Germán, T. Ishio, Katsuro Inoue","doi":"10.1109/SANER.2015.7081869","DOIUrl":"https://doi.org/10.1109/SANER.2015.7081869","url":null,"abstract":"With the popularity of open source library (re)use in both industrial and open source settings, `trust' plays vital role in third-party library adoption. Trust involves the assumption of both functional and non-functional correctness. Even with the aid of dependency management build tools such as Maven and Gradle, research have still found a latency to trust the latest release of a library. In this paper, we investigate the trust of OSS libraries. Our study of 6,374 systems in Maven Super Repository suggests that 82% of systems are more trusting of adopting the latest library release to existing systems. We uncover the impact of maven on latent and trusted library adoptions.","PeriodicalId":355949,"journal":{"name":"2015 IEEE 22nd International Conference on Software Analysis, Evolution, and Reengineering (SANER)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133062242","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}
Pub Date : 2015-03-02DOI: 10.1109/SANER.2015.7081820
Mathieu Nayrolles, A. Hamou-Lhadj, S. Tahar, Alf Larsson
Due to their inherent complexity, software systems are pledged to be released with bugs. These bugs manifest themselves on client's computers, causing crashes and undesired behaviors. Field crashes, in particular, are challenging to understand and fix as the information provided by the impacted customers are often scarce and inaccurate. To address this issue, there is a need to find ways for automatically reproducing the crash in a lab environment in order to fully understand its root causes. Crash reproduction is also an important step towards developing adequate patches. In this paper, we propose a novel crash reproduction approach, called JCHARMING (Java CrasH Automatic Reproduction by directed Model checkING). JCHARMING uses crash traces and model checking to identify program statements needed to reproduce a crash. Our approach takes advantage of the completeness provided by model checking while ignoring unneeded system states by means of information found in crash traces combined with static slices. We show the effectiveness of JCHARMING by applying it to seven different open source programs cumulating more than one million lines of code scattered in around 7000 classes. Overall, JCHARMING was able to reproduce 85% of the submitted bugs.
{"title":"JCHARMING: A bug reproduction approach using crash traces and directed model checking","authors":"Mathieu Nayrolles, A. Hamou-Lhadj, S. Tahar, Alf Larsson","doi":"10.1109/SANER.2015.7081820","DOIUrl":"https://doi.org/10.1109/SANER.2015.7081820","url":null,"abstract":"Due to their inherent complexity, software systems are pledged to be released with bugs. These bugs manifest themselves on client's computers, causing crashes and undesired behaviors. Field crashes, in particular, are challenging to understand and fix as the information provided by the impacted customers are often scarce and inaccurate. To address this issue, there is a need to find ways for automatically reproducing the crash in a lab environment in order to fully understand its root causes. Crash reproduction is also an important step towards developing adequate patches. In this paper, we propose a novel crash reproduction approach, called JCHARMING (Java CrasH Automatic Reproduction by directed Model checkING). JCHARMING uses crash traces and model checking to identify program statements needed to reproduce a crash. Our approach takes advantage of the completeness provided by model checking while ignoring unneeded system states by means of information found in crash traces combined with static slices. We show the effectiveness of JCHARMING by applying it to seven different open source programs cumulating more than one million lines of code scattered in around 7000 classes. Overall, JCHARMING was able to reproduce 85% of the submitted bugs.","PeriodicalId":355949,"journal":{"name":"2015 IEEE 22nd International Conference on Software Analysis, Evolution, and Reengineering (SANER)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132873379","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 work in the IDE, but search online resources in the web browser. The separation of the working and search context often cause the ignorance of the working context during online search. Several tools have been proposed to integrate the web browser into the IDE so that developers can search and use online resources directly in the IDE. These tools enable only the shallow integration of the web browser and the IDE. Some tools allow the developer to augment search queries with program entities in the current snapshot of the code. In this paper, we present an in-IDE ambient search agent to bridge the separation of the developer's working context and search context. Our approach considers the developers' working context in the IDE as a time-series stream of programming event observed from the developer's interaction with the IDE over time. It supports the deeper integration of the working context in the entire search process from query formulation, custom search, to search results refinement and representation. We have implemented our ambient search agent and integrate it into the Eclipse IDE. We conducted a user study to evaluate our approach and the tool support. Our evaluation shows that our ambient search agent can better aid developers in searching and using online programming resources while working in the IDE.
{"title":"amAssist: In-IDE ambient search of online programming resources","authors":"HongWei Li, Xuejiao Zhao, Zhenchang Xing, Lingfeng Bao, Xin Peng, Dongjing Gao, Wenyun Zhao","doi":"10.1109/SANER.2015.7081849","DOIUrl":"https://doi.org/10.1109/SANER.2015.7081849","url":null,"abstract":"Developers work in the IDE, but search online resources in the web browser. The separation of the working and search context often cause the ignorance of the working context during online search. Several tools have been proposed to integrate the web browser into the IDE so that developers can search and use online resources directly in the IDE. These tools enable only the shallow integration of the web browser and the IDE. Some tools allow the developer to augment search queries with program entities in the current snapshot of the code. In this paper, we present an in-IDE ambient search agent to bridge the separation of the developer's working context and search context. Our approach considers the developers' working context in the IDE as a time-series stream of programming event observed from the developer's interaction with the IDE over time. It supports the deeper integration of the working context in the entire search process from query formulation, custom search, to search results refinement and representation. We have implemented our ambient search agent and integrate it into the Eclipse IDE. We conducted a user study to evaluate our approach and the tool support. Our evaluation shows that our ambient search agent can better aid developers in searching and using online programming resources while working in the IDE.","PeriodicalId":355949,"journal":{"name":"2015 IEEE 22nd International Conference on Software Analysis, Evolution, and Reengineering (SANER)","volume":"194 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114737447","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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