@INPROCEEDINGS{Tran21-VISSOFT-NIER-SECO,
   AUTHOR       = {Van Tran, Tuan and Cheng Cheng and Fabio Petrillo and 
      Yann-Ga�l Gu�h�neuc},
   BOOKTITLE    = {Proceedings of the 9<sup>th</sup> Working Conference on Software Visualisation (VISSOFT)},
   TITLE        = {Analyzing and Visualizing Projects and their Relations 
      in Software Ecosystems},
   YEAR         = {2021},
   OPTADDRESS   = {},
   OPTCROSSREF  = {},
   EDITOR       = {Leonel Merino and Juan Pablo Sandoval Alcocer},
   MONTH        = {September},
   NOTE         = {New Ideas and Emerging Results. 5 pages.},
   OPTNUMBER    = {},
   OPTORGANIZATION = {},
   PAGES        = {105--109},
   PUBLISHER    = {IEEE CS Press},
   OPTSERIES    = {},
   OPTVOLUME    = {},
   KEYWORDS     = {Topic: <b>Program comprehension</b>, 
      Venue: <c>VISSOFT</c>},
   URL          = {http://www.ptidej.net/publications/documents/VISSOFT21.doc.pdf},
   PDF          = {http://www.ptidej.net/publications/documents/VISSOFT21.ppt.pdf},
   ABSTRACT     = {More and more software projects are being consolidated 
      into ecosystems to increase their discovery, usability, and 
      usefulness. Some of the most popular ecosystems exist in npmjs, 
      Python Package Indexing, and Apache Maven Repository. It is difficult 
      for developers to relate these projects and use them to their full 
      potential because of their number, the spread and depth of their 
      features, and their intrinsic and accidental complexities. We present 
      a technique---SECO Storms Maker---to capture and present the 
      essential information from projects in an ecosystem to help 
      developers join, use, and contribute to the ecosystem. We generate 
      word-clouds based on the projects' documentation via tokenization and 
      distribution frequency. We identify relations among projects using 
      grammar patterns scanning after part-of-speech tagging. We put these 
      word-clouds into a graph to ease navigation and exploration. We 
      evaluate our technique by manually building a ground truth and 
      comparing a randomly-selected project with SECO to show its benefits.}
}

{"_id":"efNuJH6arYjRzPPGg","bibbaseid":"vantran-cheng-petrillo-guhneuc-analyzingandvisualizingprojectsandtheirrelationsinsoftwareecosystems-2021","author_short":["Van Tran, T.","Cheng, C.","Petrillo, F.","Gu�h�neuc, Y."],"bibdata":{"bibtype":"inproceedings","type":"inproceedings","author":[{"propositions":[],"lastnames":["Van","Tran"],"firstnames":["Tuan"],"suffixes":[]},{"firstnames":["Cheng"],"propositions":[],"lastnames":["Cheng"],"suffixes":[]},{"firstnames":["Fabio"],"propositions":[],"lastnames":["Petrillo"],"suffixes":[]},{"firstnames":["Yann-Ga�l"],"propositions":[],"lastnames":["Gu�h�neuc"],"suffixes":[]}],"booktitle":"Proceedings of the 9^th Working Conference on Software Visualisation (VISSOFT)","title":"Analyzing and Visualizing Projects and their Relations in Software Ecosystems","year":"2021","optaddress":"","optcrossref":"","editor":[{"firstnames":["Leonel"],"propositions":[],"lastnames":["Merino"],"suffixes":[]},{"firstnames":["Juan","Pablo","Sandoval"],"propositions":[],"lastnames":["Alcocer"],"suffixes":[]}],"month":"September","note":"New Ideas and Emerging Results. 5 pages.","optnumber":"","optorganization":"","pages":"105–109","publisher":"IEEE CS Press","optseries":"","optvolume":"","keywords":"Topic: <b>Program comprehension</b>, Venue: <c>VISSOFT</c>","url":"http://www.ptidej.net/publications/documents/VISSOFT21.doc.pdf","pdf":"http://www.ptidej.net/publications/documents/VISSOFT21.ppt.pdf","abstract":"More and more software projects are being consolidated into ecosystems to increase their discovery, usability, and usefulness. Some of the most popular ecosystems exist in npmjs, Python Package Indexing, and Apache Maven Repository. It is difficult for developers to relate these projects and use them to their full potential because of their number, the spread and depth of their features, and their intrinsic and accidental complexities. We present a technique—SECO Storms Maker—to capture and present the essential information from projects in an ecosystem to help developers join, use, and contribute to the ecosystem. We generate word-clouds based on the projects' documentation via tokenization and distribution frequency. We identify relations among projects using grammar patterns scanning after part-of-speech tagging. We put these word-clouds into a graph to ease navigation and exploration. We evaluate our technique by manually building a ground truth and comparing a randomly-selected project with SECO to show its benefits.","bibtex":"@INPROCEEDINGS{Tran21-VISSOFT-NIER-SECO,\r\n AUTHOR = {Van Tran, Tuan and Cheng Cheng and Fabio Petrillo and \r\n Yann-Ga�l Gu�h�neuc},\r\n BOOKTITLE = {Proceedings of the 9^th Working Conference on Software Visualisation (VISSOFT)},\r\n TITLE = {Analyzing and Visualizing Projects and their Relations \r\n in Software Ecosystems},\r\n YEAR = {2021},\r\n OPTADDRESS = {},\r\n OPTCROSSREF = {},\r\n EDITOR = {Leonel Merino and Juan Pablo Sandoval Alcocer},\r\n MONTH = {September},\r\n NOTE = {New Ideas and Emerging Results. 5 pages.},\r\n OPTNUMBER = {},\r\n OPTORGANIZATION = {},\r\n PAGES = {105--109},\r\n PUBLISHER = {IEEE CS Press},\r\n OPTSERIES = {},\r\n OPTVOLUME = {},\r\n KEYWORDS = {Topic: <b>Program comprehension</b>, \r\n Venue: <c>VISSOFT</c>},\r\n URL = {http://www.ptidej.net/publications/documents/VISSOFT21.doc.pdf},\r\n PDF = {http://www.ptidej.net/publications/documents/VISSOFT21.ppt.pdf},\r\n ABSTRACT = {More and more software projects are being consolidated \r\n into ecosystems to increase their discovery, usability, and \r\n usefulness. Some of the most popular ecosystems exist in npmjs, \r\n Python Package Indexing, and Apache Maven Repository. It is difficult \r\n for developers to relate these projects and use them to their full \r\n potential because of their number, the spread and depth of their \r\n features, and their intrinsic and accidental complexities. We present \r\n a technique---SECO Storms Maker---to capture and present the \r\n essential information from projects in an ecosystem to help \r\n developers join, use, and contribute to the ecosystem. We generate \r\n word-clouds based on the projects' documentation via tokenization and \r\n distribution frequency. We identify relations among projects using \r\n grammar patterns scanning after part-of-speech tagging. We put these \r\n word-clouds into a graph to ease navigation and exploration. We \r\n evaluate our technique by manually building a ground truth and \r\n comparing a randomly-selected project with SECO to show its benefits.}\r\n}\r\n\r\n","author_short":["Van Tran, T.","Cheng, C.","Petrillo, F.","Gu�h�neuc, Y."],"editor_short":["Merino, L.","Alcocer, J. P. 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