Pub Date : 2013-10-31DOI: 10.1109/VISSOFT.2013.6650540
S. Reiss, A. Tarvo
We consider the problem of understanding locking behavior in large Java programs using a combination of data collection, data analysis, and visualization. Our technique starts by collecting partial information about all locks used in the program. It then analyzes this information to determine sets of locks with common behaviors and to determine, for each set of locks, how that lock is used, e.g. if it is used as a mutex, semaphore, read-write lock, etc. The result of the analysis is then presented to the user who can select specific locks for full analysis during a subsequent run. Visualizing locking information is particularly difficult since the time scale of a lock can be ten or more orders of magnitude different from the time scale of the overall run and locks can be used millions of times. We provide different visualizations and visualization techniques for this purpose. First, we analyze either the partial or full traces and identify patterns of how each lock is used and display just those patterns along with their frequency. Second, we provide a thread-centric view of locking that supports fish-eye views at the microsecond level as well as time compression. Third, we provide a lock-centric view that is based on the specific type of lock to show its particular behavior.
{"title":"Automatic categorization and visualization of lock behavior","authors":"S. Reiss, A. Tarvo","doi":"10.1109/VISSOFT.2013.6650540","DOIUrl":"https://doi.org/10.1109/VISSOFT.2013.6650540","url":null,"abstract":"We consider the problem of understanding locking behavior in large Java programs using a combination of data collection, data analysis, and visualization. Our technique starts by collecting partial information about all locks used in the program. It then analyzes this information to determine sets of locks with common behaviors and to determine, for each set of locks, how that lock is used, e.g. if it is used as a mutex, semaphore, read-write lock, etc. The result of the analysis is then presented to the user who can select specific locks for full analysis during a subsequent run. Visualizing locking information is particularly difficult since the time scale of a lock can be ten or more orders of magnitude different from the time scale of the overall run and locks can be used millions of times. We provide different visualizations and visualization techniques for this purpose. First, we analyze either the partial or full traces and identify patterns of how each lock is used and display just those patterns along with their frequency. Second, we provide a thread-centric view of locking that supports fish-eye views at the microsecond level as well as time compression. Third, we provide a lock-centric view that is based on the specific type of lock to show its particular behavior.","PeriodicalId":392495,"journal":{"name":"2013 First IEEE Working Conference on Software Visualization (VISSOFT)","volume":"433 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116007719","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 : 2013-10-31DOI: 10.1109/VISSOFT.2013.6650526
Junji Zhi, G. Ruhe
During the software development process many technical documents are produced. Such documents and their evolution history contain rich information about the development process. Analyzing these document changes may reveal regularities and anomalies which are helpful to understand the software system and its development process. In this paper, we propose DEVis, an interactive visualization tool to visualize the software documentation evolution and aid the tasks of analyzing software development process. We initially evaluated our tool using the knowledge task-based framework and discuss the challenging aspects and lessons learned during the development of DEVis.
{"title":"DEVis: A tool for visualizing software document evolution","authors":"Junji Zhi, G. Ruhe","doi":"10.1109/VISSOFT.2013.6650526","DOIUrl":"https://doi.org/10.1109/VISSOFT.2013.6650526","url":null,"abstract":"During the software development process many technical documents are produced. Such documents and their evolution history contain rich information about the development process. Analyzing these document changes may reveal regularities and anomalies which are helpful to understand the software system and its development process. In this paper, we propose DEVis, an interactive visualization tool to visualize the software documentation evolution and aid the tasks of analyzing software development process. We initially evaluated our tool using the knowledge task-based framework and discuss the challenging aspects and lessons learned during the development of DEVis.","PeriodicalId":392495,"journal":{"name":"2013 First IEEE Working Conference on Software Visualization (VISSOFT)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128616690","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 : 2013-10-31DOI: 10.1109/VISSOFT.2013.6650537
Vijay Krishna Palepu, James A. Jones
In this New Ideas and Emerging Results paper, we present a novel visualization, THE BRAIN, that reveals clusters of source code that co-execute to produce behavioral features of the program throughout and within executions. We created a clustered visualization of source-code that is informed by dynamic control flow of multiple executions; each cluster represents commonly interacting logic that composes software features. In addition, we render individual executions atop the clustered multiple-execution visualization as user-controlled animations to reveal characteristics of specific executions-these animations may provide exemplars for the clustered features and provide chronology for those behavioral features, or they may reveal anomalous behaviors that do not fit with the overall operational profile of most executions. Both the clustered multiple-execution view and the animated individual-execution view provide insights for the constituent behaviors within executions that compose behaviors of whole executions. Inspired by neural imaging of human brains of people who were subjected to various external stimuli, we designed and implemented THE BRAIN to reveal program activity during execution. The result has revealed the principal behaviors of execution, and those behaviors were revealed to be (in some cases) cohesive, modular source-code structures and (in other cases) cross-cutting, emergent behaviors that involve multiple modules. In this paper, we describe THE BRAIN and envisage the uses to which it can be put, and we provide two example usage scenarios to demonstrate its utility.
{"title":"Visualizing constituent behaviors within executions","authors":"Vijay Krishna Palepu, James A. Jones","doi":"10.1109/VISSOFT.2013.6650537","DOIUrl":"https://doi.org/10.1109/VISSOFT.2013.6650537","url":null,"abstract":"In this New Ideas and Emerging Results paper, we present a novel visualization, THE BRAIN, that reveals clusters of source code that co-execute to produce behavioral features of the program throughout and within executions. We created a clustered visualization of source-code that is informed by dynamic control flow of multiple executions; each cluster represents commonly interacting logic that composes software features. In addition, we render individual executions atop the clustered multiple-execution visualization as user-controlled animations to reveal characteristics of specific executions-these animations may provide exemplars for the clustered features and provide chronology for those behavioral features, or they may reveal anomalous behaviors that do not fit with the overall operational profile of most executions. Both the clustered multiple-execution view and the animated individual-execution view provide insights for the constituent behaviors within executions that compose behaviors of whole executions. Inspired by neural imaging of human brains of people who were subjected to various external stimuli, we designed and implemented THE BRAIN to reveal program activity during execution. The result has revealed the principal behaviors of execution, and those behaviors were revealed to be (in some cases) cohesive, modular source-code structures and (in other cases) cross-cutting, emergent behaviors that involve multiple modules. In this paper, we describe THE BRAIN and envisage the uses to which it can be put, and we provide two example usage scenarios to demonstrate its utility.","PeriodicalId":392495,"journal":{"name":"2013 First IEEE Working Conference on Software Visualization (VISSOFT)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125215505","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 : 2013-10-31DOI: 10.1109/VISSOFT.2013.6650525
Avdo Hanjalic
We present ClonEvol, a visual analysis tool that assists in obtaining insight into the state and the evolution of a C/C++/Java source code base on project, file and scope level. ClonEvol combines information obtained from the software versioning system and contents of files that change between versions; The tool operates as tool-chain of Subversion (SVN), Doxygen (applied as static analyzer) and Simian as code duplication detector. The consolidated information is presented to the user in an interactive visual manner. The focus of the presented tool lies on scalability (in time and space) concerning data acquisition, data processing and visualization, and ease of use. The visualization is approached by using a (mirrored) radial tree to show the file and scope structures, complemented with hierarchically bundled edges that show clone relations. We demonstrate the use of ClonEvol on a real world code base.
我们介绍了ClonEvol，这是一个可视化的分析工具，可以帮助我们深入了解基于项目、文件和范围级别的C/ c++ /Java源代码的状态和演变。ClonEvol结合了从软件版本控制系统获得的信息和版本之间变化的文件内容;该工具作为Subversion (SVN)的工具链，oxygen(作为静态分析器)和Simian(作为代码复制检测器)运行。合并后的信息以交互式可视化的方式呈现给用户。所介绍的工具的重点在于与数据采集、数据处理和可视化以及易用性相关的可伸缩性(在时间和空间上)。可视化是通过使用(镜像)径向树来显示文件和作用域结构，并辅以显示克隆关系的分层捆绑边来实现的。我们将在真实世界的代码库中演示ClonEvol的使用。
{"title":"ClonEvol: Visualizing software evolution with code clones","authors":"Avdo Hanjalic","doi":"10.1109/VISSOFT.2013.6650525","DOIUrl":"https://doi.org/10.1109/VISSOFT.2013.6650525","url":null,"abstract":"We present ClonEvol, a visual analysis tool that assists in obtaining insight into the state and the evolution of a C/C++/Java source code base on project, file and scope level. ClonEvol combines information obtained from the software versioning system and contents of files that change between versions; The tool operates as tool-chain of Subversion (SVN), Doxygen (applied as static analyzer) and Simian as code duplication detector. The consolidated information is presented to the user in an interactive visual manner. The focus of the presented tool lies on scalability (in time and space) concerning data acquisition, data processing and visualization, and ease of use. The visualization is approached by using a (mirrored) radial tree to show the file and scope structures, complemented with hierarchically bundled edges that show clone relations. We demonstrate the use of ClonEvol on a real world code base.","PeriodicalId":392495,"journal":{"name":"2013 First IEEE Working Conference on Software Visualization (VISSOFT)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124609641","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 : 2013-10-31DOI: 10.1109/VISSOFT.2013.6650519
Bonita Sharif, Grace Jetty, Jairo Aponte, Esteban Parra
A study to assess the effect of SeeIT 3D, a software visualization tool is presented. Six different tasks in three different task categories are assessed in the context of a large open-source system. Ninety-seven subjects were recruited from three different universities to participate in the study. Two methods of data collection: traditional questionnaires and an eye-tracker were used. The main goal was to determine the impact and added benefit of SeeIT 3D while performing typical software tasks within the Eclipse IDE. Results indicate that SeeIT 3D performs significantly better in one task category namely overview tasks but takes significantly longer when completing bug fixing tasks. Scores obtained by the subjects in the SeeIT 3D group are 13% better and 45% faster for overview tasks.
{"title":"An empirical study assessing the effect of seeit 3D on comprehension","authors":"Bonita Sharif, Grace Jetty, Jairo Aponte, Esteban Parra","doi":"10.1109/VISSOFT.2013.6650519","DOIUrl":"https://doi.org/10.1109/VISSOFT.2013.6650519","url":null,"abstract":"A study to assess the effect of SeeIT 3D, a software visualization tool is presented. Six different tasks in three different task categories are assessed in the context of a large open-source system. Ninety-seven subjects were recruited from three different universities to participate in the study. Two methods of data collection: traditional questionnaires and an eye-tracker were used. The main goal was to determine the impact and added benefit of SeeIT 3D while performing typical software tasks within the Eclipse IDE. Results indicate that SeeIT 3D performs significantly better in one task category namely overview tasks but takes significantly longer when completing bug fixing tasks. Scores obtained by the subjects in the SeeIT 3D group are 13% better and 45% faster for overview tasks.","PeriodicalId":392495,"journal":{"name":"2013 First IEEE Working Conference on Software Visualization (VISSOFT)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127240605","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 : 2013-10-31DOI: 10.1109/VISSOFT.2013.6650535
Wim De Pauw, J. Wolf, Andrey Balmin
In this paper we describe a visualization system that shows the behavior of jobs in large, distributed computing clusters. The system has been in use for two years, and is sufficiently generic to be applied in two quite different domains: a Hadoop MapReduce environment and the Watson DeepQA DUCC cluster. Scalable and flexible data processing systems typically run hundreds or more of simultaneous jobs. The creation, termination, expansion and contraction of these jobs can be very dynamic and transient, and it is difficult to understand this behavior without showing its evolution over time. While traditional monitoring tools typically show either snapshots of the current load balancing or aggregate trends over time, our new visualization technique shows the behavior of each of the jobs over time in the context of the cluster, and in either a real-time or post-mortem view. Its new algorithm runs in realtime mode and can make retroactive adjustments to produce smooth layouts. Moreover, our system allows users to drill down to see details about individual jobs. The visualization has been proven useful for administrators to see the overall occupancy, trends and job allocations in the cluster, and for users to spot errors or to monitor how many resources are given to their jobs.
{"title":"Visualizing jobs with shared resources in distributed environments","authors":"Wim De Pauw, J. Wolf, Andrey Balmin","doi":"10.1109/VISSOFT.2013.6650535","DOIUrl":"https://doi.org/10.1109/VISSOFT.2013.6650535","url":null,"abstract":"In this paper we describe a visualization system that shows the behavior of jobs in large, distributed computing clusters. The system has been in use for two years, and is sufficiently generic to be applied in two quite different domains: a Hadoop MapReduce environment and the Watson DeepQA DUCC cluster. Scalable and flexible data processing systems typically run hundreds or more of simultaneous jobs. The creation, termination, expansion and contraction of these jobs can be very dynamic and transient, and it is difficult to understand this behavior without showing its evolution over time. While traditional monitoring tools typically show either snapshots of the current load balancing or aggregate trends over time, our new visualization technique shows the behavior of each of the jobs over time in the context of the cluster, and in either a real-time or post-mortem view. Its new algorithm runs in realtime mode and can make retroactive adjustments to produce smooth layouts. Moreover, our system allows users to drill down to see details about individual jobs. The visualization has been proven useful for administrators to see the overall occupancy, trends and job allocations in the cluster, and for users to spot errors or to monitor how many resources are given to their jobs.","PeriodicalId":392495,"journal":{"name":"2013 First IEEE Working Conference on Software Visualization (VISSOFT)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123496458","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 : 2013-10-31DOI: 10.1109/VISSOFT.2013.6650534
Benjamin Karran, Jonas Trümper, J. Döllner
In software comprehension, program traces are important to gain insight into certain aspects of concurrent runtime behavior, e.g., thread-interplay. Here, key tasks are finding usages of blocking operations, such as synchronization and I/O operations, assessing temporal order of such operations, and analyzing their effects. This is a hard task for large and complex program traces due to their size and number of threads involved. In this paper, we present SYNCTRACE a new visualization technique based on (bended) activity diagrams and edge bundles that allows for parallel analysis of multiple threads and their inter-thread correspondences. We demonstrate how the technique, implemented as a tool, can be applied on real-world trace datasets to support understanding concurrent behavior.
{"title":"SYNCTRACE: Visual thread-interplay analysis","authors":"Benjamin Karran, Jonas Trümper, J. Döllner","doi":"10.1109/VISSOFT.2013.6650534","DOIUrl":"https://doi.org/10.1109/VISSOFT.2013.6650534","url":null,"abstract":"In software comprehension, program traces are important to gain insight into certain aspects of concurrent runtime behavior, e.g., thread-interplay. Here, key tasks are finding usages of blocking operations, such as synchronization and I/O operations, assessing temporal order of such operations, and analyzing their effects. This is a hard task for large and complex program traces due to their size and number of threads involved. In this paper, we present SYNCTRACE a new visualization technique based on (bended) activity diagrams and edge bundles that allows for parallel analysis of multiple threads and their inter-thread correspondences. We demonstrate how the technique, implemented as a tool, can be applied on real-world trace datasets to support understanding concurrent behavior.","PeriodicalId":392495,"journal":{"name":"2013 First IEEE Working Conference on Software Visualization (VISSOFT)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123814744","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 : 2013-10-31DOI: 10.1109/VISSOFT.2013.6650539
Carlos Gouveia, José Campos, Rui Abreu
Testing and debugging is the most expensive, error-prone phase in the software development life cycle. Automated software fault localization can drastically improve the efficiency of this phase, thus improving the overall quality of the software. Amongst the most well-known techniques, due to its efficiency and effectiveness, is spectrum-based fault localization. In this paper, we propose three dynamic graphical forms using HTML5 to display the diagnostic reports yielded by spectrum-based fault localization. The visualizations proposed, namely Sunburst, Vertical Partition, and Bubble Hierarchy, have been implemented within the GZOLTAR toolset, replacing previous and less-intuitive OpenGL-based visualizations. The GZOLTAR toolset is a plug-and-play plugin for the Eclipse IDE to ease world-wide adoption. Finally, we performed an user study with GZOLTAR and confirmed that the visualizations help to drastically reduce the time needed in debugging (e.g., all participants using the visualizations were able to pinpoint the fault, whereas of those using traditional methods only 35% found the fault). The group that used the visualizations took on average 9 minutes and 17 seconds less than the group that did not use them.
{"title":"Using HTML5 visualizations in software fault localization","authors":"Carlos Gouveia, José Campos, Rui Abreu","doi":"10.1109/VISSOFT.2013.6650539","DOIUrl":"https://doi.org/10.1109/VISSOFT.2013.6650539","url":null,"abstract":"Testing and debugging is the most expensive, error-prone phase in the software development life cycle. Automated software fault localization can drastically improve the efficiency of this phase, thus improving the overall quality of the software. Amongst the most well-known techniques, due to its efficiency and effectiveness, is spectrum-based fault localization. In this paper, we propose three dynamic graphical forms using HTML5 to display the diagnostic reports yielded by spectrum-based fault localization. The visualizations proposed, namely Sunburst, Vertical Partition, and Bubble Hierarchy, have been implemented within the GZOLTAR toolset, replacing previous and less-intuitive OpenGL-based visualizations. The GZOLTAR toolset is a plug-and-play plugin for the Eclipse IDE to ease world-wide adoption. Finally, we performed an user study with GZOLTAR and confirmed that the visualizations help to drastically reduce the time needed in debugging (e.g., all participants using the visualizations were able to pinpoint the fault, whereas of those using traditional methods only 35% found the fault). The group that used the visualizations took on average 9 minutes and 17 seconds less than the group that did not use them.","PeriodicalId":392495,"journal":{"name":"2013 First IEEE Working Conference on Software Visualization (VISSOFT)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115296666","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 : 2013-10-31DOI: 10.1109/VISSOFT.2013.6650538
Raoul L. Veroy, Nathan P. Ricci, Samuel Z. Guyer
We present memory allocation and death plots, a visualization technique for showing both which method an object is allocated in a Java program, and in which method that object eventually dies. This relates the place in a program's execution where memory is first used to the place it is no longer used, thus helping the programmer to better understand the memory behavior of a program.
{"title":"Visualizing the allocation and death of objects","authors":"Raoul L. Veroy, Nathan P. Ricci, Samuel Z. Guyer","doi":"10.1109/VISSOFT.2013.6650538","DOIUrl":"https://doi.org/10.1109/VISSOFT.2013.6650538","url":null,"abstract":"We present memory allocation and death plots, a visualization technique for showing both which method an object is allocated in a Java program, and in which method that object eventually dies. This relates the place in a program's execution where memory is first used to the place it is no longer used, thus helping the programmer to better understand the memory behavior of a program.","PeriodicalId":392495,"journal":{"name":"2013 First IEEE Working Conference on Software Visualization (VISSOFT)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115715204","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 : 2013-10-31DOI: 10.1109/VISSOFT.2013.6650543
R. Lopez-Herrejon, Alexander Egyed
Software Product Lines (SPLs) are families of related software products. SPL practices have proven substantial technological and economical benefits such as improved software reuse and reduced time to market. Software testing is a key development activity in SPLs, and it is uniquely challenging because of the usually large number of feature combinations present in typical SPLs. Pairwise testing is a combinatorial testing technique that aims at selecting products to test based on the pairs of feature combinations such products provide. Our previous work on evolutionary approaches for SPL testing and their comparative analysis has yielded a large amount of data that prompted us to explore ways by which to convey and represent this information. In this paper we present our early results in this effort. We describe three basic visualization applications to pairwise testing and highlight some of the open questions that we foresee. But most importantly, our driving goal is both to raise the awareness of the visualization problems in this area and to spark the interest of the software visualization community.
{"title":"Towards interactive visualization support for pairwise testing software product lines","authors":"R. Lopez-Herrejon, Alexander Egyed","doi":"10.1109/VISSOFT.2013.6650543","DOIUrl":"https://doi.org/10.1109/VISSOFT.2013.6650543","url":null,"abstract":"Software Product Lines (SPLs) are families of related software products. SPL practices have proven substantial technological and economical benefits such as improved software reuse and reduced time to market. Software testing is a key development activity in SPLs, and it is uniquely challenging because of the usually large number of feature combinations present in typical SPLs. Pairwise testing is a combinatorial testing technique that aims at selecting products to test based on the pairs of feature combinations such products provide. Our previous work on evolutionary approaches for SPL testing and their comparative analysis has yielded a large amount of data that prompted us to explore ways by which to convey and represent this information. In this paper we present our early results in this effort. We describe three basic visualization applications to pairwise testing and highlight some of the open questions that we foresee. But most importantly, our driving goal is both to raise the awareness of the visualization problems in this area and to spark the interest of the software visualization community.","PeriodicalId":392495,"journal":{"name":"2013 First IEEE Working Conference on Software Visualization (VISSOFT)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116414465","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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