際際滷shows by User: timmenzies / http://www.slideshare.net/images/logo.gif 際際滷shows by User: timmenzies / Wed, 09 Dec 2015 18:35:57 GMT 際際滷Share feed for 際際滷shows by User: timmenzies Talks2015 novdec /slideshow/talks2015-novdec/55987380 talks2015novdec-151209183557-lva1-app6892
Pointers to my google slides]]>
Pointers to my google slides]]> Wed, 09 Dec 2015 18:35:57 GMT /slideshow/talks2015-novdec/55987380 timmenzies@slideshare.net(timmenzies) Talks2015 novdec timmenzies Pointers to my google slides <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/talks2015novdec-151209183557-lva1-app6892-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Pointers to my google slides
Talks2015 novdec from CS, NcState
]]> 1081 7 https://cdn.slidesharecdn.com/ss_thumbnails/talks2015novdec-151209183557-lva1-app6892-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Future se oct15 /slideshow/future-se-oct15/53525093 futurese-oct15-151004220752-lva1-app6891
Science has escaped the lab and is roaming free in the world. People use software to understand the world . What tools are needed to support that work? ]]>
Science has escaped the lab and is roaming free in the world. People use software to understand the world . What tools are needed to support that work? ]]> Sun, 04 Oct 2015 22:07:52 GMT /slideshow/future-se-oct15/53525093 timmenzies@slideshare.net(timmenzies) Future se oct15 timmenzies Science has escaped the lab and is roaming free in the world.鐃 People use software to understand the world . What tools are needed to support that work? <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/futurese-oct15-151004220752-lva1-app6891-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Science has escaped the lab and is roaming free in the world.鐃 People use software to understand the world . What tools are needed to support that work?
Future se oct15 from CS, NcState
]]> 1406 10 https://cdn.slidesharecdn.com/ss_thumbnails/futurese-oct15-151004220752-lva1-app6891-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 GALE: Geometric active learning for Search-Based Software Engineering /slideshow/gale-geometric-active-learning-for-searchbased-software-engineering/52234798 fse15-v2-150831033650-lva1-app6891
Multi-objective evolutionary algorithms (MOEAs) help software engineers find novel solutions to complex problems. When automatic tools explore too many options, they are slow to use and hard to comprehend. GALE is a near-linear time MOEA that builds a piecewise approximation to the surface of best solutions along the Pareto frontier. For each piece, GALE mutates solutions towards the better end. In numerous case studies, GALE finds comparable solutions to standard methods (NSGA-II, SPEA2) using far fewer evaluations (e.g. 20 evaluations, not 1,000). GALE is recommended when a model is expensive to evaluate, or when some audience needs to browse and understand how an MOEA has made its conclusions.]]>
Multi-objective evolutionary algorithms (MOEAs) help software engineers find novel solutions to complex problems. When automatic tools explore too many options, they are slow to use and hard to comprehend. GALE is a near-linear time MOEA that builds a piecewise approximation to the surface of best solutions along the Pareto frontier. For each piece, GALE mutates solutions towards the better end. In numerous case studies, GALE finds comparable solutions to standard methods (NSGA-II, SPEA2) using far fewer evaluations (e.g. 20 evaluations, not 1,000). GALE is recommended when a model is expensive to evaluate, or when some audience needs to browse and understand how an MOEA has made its conclusions.]]> Mon, 31 Aug 2015 03:36:50 GMT /slideshow/gale-geometric-active-learning-for-searchbased-software-engineering/52234798 timmenzies@slideshare.net(timmenzies) GALE: Geometric active learning for Search-Based Software Engineering timmenzies Multi-objective evolutionary algorithms (MOEAs) help software engineers find novel solutions to complex problems. When automatic tools explore too many options, they are slow to use and hard to comprehend. GALE is a near-linear time MOEA that builds a piecewise approximation to the surface of best solutions along the Pareto frontier. For each piece, GALE mutates solutions towards the better end. In numerous case studies, GALE finds comparable solutions to standard methods (NSGA-II, SPEA2) using far fewer evaluations (e.g. 20 evaluations, not 1,000). GALE is recommended when a model is expensive to evaluate, or when some audience needs to browse and understand how an MOEA has made its conclusions. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/fse15-v2-150831033650-lva1-app6891-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Multi-objective evolutionary algorithms (MOEAs) help software engineers find novel solutions to complex problems. When automatic tools explore too many options, they are slow to use and hard to comprehend. GALE is a near-linear time MOEA that builds a piecewise approximation to the surface of best solutions along the Pareto frontier. For each piece, GALE mutates solutions towards the better end. In numerous case studies, GALE finds comparable solutions to standard methods (NSGA-II, SPEA2) using far fewer evaluations (e.g. 20 evaluations, not 1,000). GALE is recommended when a model is expensive to evaluate, or when some audience needs to browse and understand how an MOEA has made its conclusions.
GALE: Geometric active learning for Search-Based Software Engineering from CS, NcState
]]> 1734 10 https://cdn.slidesharecdn.com/ss_thumbnails/fse15-v2-150831033650-lva1-app6891-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Big Data: 鐃the weakest link /slideshow/big-data-the-weakest-link/51372305 skillpredictor-v1-150807043043-lva1-app6891
Vivek Nair, Tim Menzies {vivekaxl,tim.menzies}@gmail.com HPCC Eng. Summit - Sept 29, 2015]]>
Vivek Nair, Tim Menzies {vivekaxl,tim.menzies}@gmail.com HPCC Eng. Summit - Sept 29, 2015]]> Fri, 07 Aug 2015 04:30:42 GMT /slideshow/big-data-the-weakest-link/51372305 timmenzies@slideshare.net(timmenzies) Big Data: 鐃the weakest link timmenzies Vivek Nair, Tim Menzies {vivekaxl,tim.menzies}@gmail.com鐃 HPCC Eng. Summit - Sept 29, 2015 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/skillpredictor-v1-150807043043-lva1-app6891-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Vivek Nair, Tim Menzies {vivekaxl,tim.menzies}@gmail.com鐃 HPCC Eng. Summit - Sept 29, 2015
Big Data: the weakest link from CS, NcState
]]> 1013 4 https://cdn.slidesharecdn.com/ss_thumbnails/skillpredictor-v1-150807043043-lva1-app6891-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Three Laws of Trusted Data Sharing:鐃(Building a Better Business 鐃Case for Data Sharing) /slideshow/three-laws-of-trusted-data-sharingbuilding-a-better-business-case-for-data-sharing/51328654 ibmaug6-150806015702-lva1-app6892
Discussions about sharing - Too much fear - Not enough about benefits Can we learn more from sharing that hoarding ? - Yes (results from SE) Three laws of trusted data sharing: - For SE quality prediction.. - Better models from shared privatized data that from all raw data Q: does this work for other kinds of data? A: dont know yet]]>
Discussions about sharing - Too much fear - Not enough about benefits Can we learn more from sharing that hoarding ? - Yes (results from SE) Three laws of trusted data sharing: - For SE quality prediction.. - Better models from shared privatized data that from all raw data Q: does this work for other kinds of data? A: dont know yet]]> Thu, 06 Aug 2015 01:57:01 GMT /slideshow/three-laws-of-trusted-data-sharingbuilding-a-better-business-case-for-data-sharing/51328654 timmenzies@slideshare.net(timmenzies) Three Laws of Trusted Data Sharing:鐃(Building a Better Business 鐃Case for Data Sharing) timmenzies Discussions about sharing - Too much fear - Not enough about benefits鐃 Can we learn more from sharing that hoarding ? - Yes (results from SE)鐃 Three laws of trusted data sharing: - For SE quality prediction.. - Better models from shared privatized data that from all raw data 鐃 Q: does this work for other kinds of data? A: dont know yet <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/ibmaug6-150806015702-lva1-app6892-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Discussions about sharing - Too much fear - Not enough about benefits鐃 Can we learn more from sharing that hoarding ? - Yes (results from SE)鐃 Three laws of trusted data sharing: - For SE quality prediction.. - Better models from shared privatized data that from all raw data 鐃 Q: does this work for other kinds of data? A: dont know yet
Three Laws of Trusted Data Sharing: (Building a Better Business Case for Data Sharing) from CS, NcState
]]> 964 8 https://cdn.slidesharecdn.com/ss_thumbnails/ibmaug6-150806015702-lva1-app6892-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Lexisnexis june9 /slideshow/lexisnexis-june9/49151820 lexisnexis-june9-150609031056-lva1-app6891
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Lexisnexis june9 from CS, NcState
]]> 4013 6 https://cdn.slidesharecdn.com/ss_thumbnails/lexisnexis-june9-150609031056-lva1-app6891-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Welcome to ICSE NIER15 鐃(new ideas and emerging results). /slideshow/nier-hello/48247422 nierhello-150517142300-lva1-app6892
Tim Menzies, NC State, USA Abhik Roychoudhury, NUS, Singapore]]>
Tim Menzies, NC State, USA Abhik Roychoudhury, NUS, Singapore]]> Sun, 17 May 2015 14:23:00 GMT /slideshow/nier-hello/48247422 timmenzies@slideshare.net(timmenzies) Welcome to ICSE NIER15 鐃(new ideas and emerging results). timmenzies Tim Menzies, NC State, USA Abhik Roychoudhury, NUS, Singapore <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/nierhello-150517142300-lva1-app6892-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Tim Menzies, NC State, USA Abhik Roychoudhury, NUS, Singapore
Welcome to ICSE NIER15 (new ideas and emerging results). from CS, NcState
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Technical Briefing, ICSE'15, Florence, Italy, May, 2015 Tim Menzies, Leandrom Minku, Fayola Peters]]>
Technical Briefing, ICSE'15, Florence, Italy, May, 2015 Tim Menzies, Leandrom Minku, Fayola Peters]]> Sat, 16 May 2015 12:30:57 GMT /slideshow/icse15-techbriefing-data-science/48222085 timmenzies@slideshare.net(timmenzies) Icse15 Tech-briefing Data Science timmenzies Technical Briefing, ICSE'15, Florence, Italy, May, 2015 Tim Menzies, Leandrom Minku, Fayola Peters <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/icse15techbriefingdatasciencequant-150516123057-lva1-app6891-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Technical Briefing, ICSE&#39;15, Florence, Italy, May, 2015 Tim Menzies, Leandrom Minku, Fayola Peters
Icse15 Tech-briefing Data Science from CS, NcState
]]> 1540 3 https://cdn.slidesharecdn.com/ss_thumbnails/icse15techbriefingdatasciencequant-150516123057-lva1-app6891-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Kits to Find the Bits that Fits /slideshow/kits-to-find-the-bits-that-fits/48215271 sam-v1-150516062108-lva1-app6891
SAM'15 keynote, ICSE 2015, Florence, Italy]]>
SAM'15 keynote, ICSE 2015, Florence, Italy]]> Sat, 16 May 2015 06:21:08 GMT /slideshow/kits-to-find-the-bits-that-fits/48215271 timmenzies@slideshare.net(timmenzies) Kits to Find the Bits that Fits timmenzies SAM'15 keynote, ICSE 2015, Florence, Italy <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/sam-v1-150516062108-lva1-app6891-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> SAM&#39;15 keynote, ICSE 2015, Florence, Italy
Kits to Find the Bits that Fits from CS, NcState
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Ai4se lab template from CS, NcState
]]> 421 2 https://cdn.slidesharecdn.com/ss_thumbnails/ai4se-150412105919-conversion-gate01-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Automated Software Enging, Fall 2015, NCSU /slideshow/automated-software-enging-fall-2015-ncsu/44859494 automated-se-short-150218205510-conversion-gate01
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Automated Software Enging, Fall 2015, NCSU from CS, NcState
]]> 1288 2 https://cdn.slidesharecdn.com/ss_thumbnails/automated-se-short-150218205510-conversion-gate01-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Requirements Engineering /slideshow/re-44761824/44761824 re-150216201940-conversion-gate01
CSC 510 North Carolina State University Dr. Tim Menzies]]>
CSC 510 North Carolina State University Dr. Tim Menzies]]> Mon, 16 Feb 2015 20:19:40 GMT /slideshow/re-44761824/44761824 timmenzies@slideshare.net(timmenzies) Requirements Engineering timmenzies CSC 510 North Carolina State University Dr. Tim Menzies <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/re-150216201940-conversion-gate01-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> CSC 510 North Carolina State University Dr. Tim Menzies
Requirements Engineering from CS, NcState
]]> 2041 5 https://cdn.slidesharecdn.com/ss_thumbnails/re-150216201940-conversion-gate01-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 172529main ken and_tim_software_assurance_research_at_west_virginia /slideshow/172529main-ken-andtimsoftwareassuranceresearchatwestvirginia/43837580 172529mainkenandtimsoftwareassuranceresearchatwestvirginia-150123151354-conversion-gate02
SA @ WV(software assurance research at West Virginia) Kenneth McGill NASA IV&V Facility Research Lead 304.367.8300 Kenneth.McGill@ivv.nasa.gov Dr. Tim Menzies Ph.D. (WVU) Software Engineering Research Chair tim@menzies.us]]>
SA @ WV(software assurance research at West Virginia) Kenneth McGill NASA IV&V Facility Research Lead 304.367.8300 Kenneth.McGill@ivv.nasa.gov Dr. Tim Menzies Ph.D. (WVU) Software Engineering Research Chair tim@menzies.us]]> Fri, 23 Jan 2015 15:13:53 GMT /slideshow/172529main-ken-andtimsoftwareassuranceresearchatwestvirginia/43837580 timmenzies@slideshare.net(timmenzies) 172529main ken and_tim_software_assurance_research_at_west_virginia timmenzies SA @ WV鐃(software assurance 鐃research at West Virginia)鐃 Kenneth McGill NASA IV&V Facility Research Lead 304.367.8300 Kenneth.McGill@ivv.nasa.gov Dr. Tim Menzies Ph.D. (WVU) Software Engineering Research Chair tim@menzies.us <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/172529mainkenandtimsoftwareassuranceresearchatwestvirginia-150123151354-conversion-gate02-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> SA @ WV鐃(software assurance 鐃research at West Virginia)鐃 Kenneth McGill NASA IV&amp;V Facility Research Lead 304.367.8300 Kenneth.McGill@ivv.nasa.gov Dr. Tim Menzies Ph.D. (WVU) Software Engineering Research Chair tim@menzies.us
172529main ken and_tim_software_assurance_research_at_west_virginia from CS, NcState
]]> 1832 5 https://cdn.slidesharecdn.com/ss_thumbnails/172529mainkenandtimsoftwareassuranceresearchatwestvirginia-150123151354-conversion-gate02-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Automated Software Engineering /slideshow/automated-software-engineering/41839456 ase-141120235239-conversion-gate02
Career advice: learn model-based reasoning (its the next big thing in SE).]]>
Career advice: learn model-based reasoning (its the next big thing in SE).]]> Thu, 20 Nov 2014 23:52:39 GMT /slideshow/automated-software-engineering/41839456 timmenzies@slideshare.net(timmenzies) Automated Software Engineering timmenzies Career advice: learn model-based reasoning (its the next big thing in SE). <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/ase-141120235239-conversion-gate02-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Career advice: learn model-based reasoning (its the next big thing in SE).
Automated Software Engineering from CS, NcState
]]> 1260 4 https://cdn.slidesharecdn.com/ss_thumbnails/ase-141120235239-conversion-gate02-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Next Generation Treatment Learning (finding the diamonds in the dust) /timmenzies/talk-v2 talk-v2-141030122647-conversion-gate02
Q: How have dummies (like me) managed to gain (some) control over a (seemingly) complex world? A:The world is simpler than we think. Models contain clumps A few collar variables decide which clumps to use.]]>
Q: How have dummies (like me) managed to gain (some) control over a (seemingly) complex world? A:The world is simpler than we think. Models contain clumps A few collar variables decide which clumps to use.]]> Thu, 30 Oct 2014 12:26:47 GMT /timmenzies/talk-v2 timmenzies@slideshare.net(timmenzies) Next Generation Treatment Learning (finding the diamonds in the dust) timmenzies Q: How have dummies (like me) managed to gain (some) control over a (seemingly) complex world? A:The world is simpler than we think. Models contain clumps A few collar variables decide which clumps to use. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/talk-v2-141030122647-conversion-gate02-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Q: How have dummies (like me) managed to gain (some) control over a (seemingly) complex world? A:The world is simpler than we think. Models contain clumps A few collar variables decide which clumps to use.
Next Generation Treatment Learning (finding the diamonds in the dust) from CS, NcState
]]> 727 4 https://cdn.slidesharecdn.com/ss_thumbnails/talk-v2-141030122647-conversion-gate02-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Tim Menzies, directions in Data Science /slideshow/tim-menzies-directions-in-data-science/39894842 directions-141005130757-conversion-gate02
Perspectives from PROMISE:lessons learned, issues raisedtim.menzies@gmail.com]]>
Perspectives from PROMISE:lessons learned, issues raisedtim.menzies@gmail.com]]> Sun, 05 Oct 2014 13:07:57 GMT /slideshow/tim-menzies-directions-in-data-science/39894842 timmenzies@slideshare.net(timmenzies) Tim Menzies, directions in Data Science timmenzies Perspectives from PROMISE:鐃lessons learned, issues raised鐃tim.menzies@gmail.com <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/directions-141005130757-conversion-gate02-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Perspectives from PROMISE:鐃lessons learned, issues raised鐃tim.menzies@gmail.com
Tim Menzies, directions in Data Science from CS, NcState
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Goldrush from CS, NcState
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]]> Mon, 23 Jun 2014 00:13:34 GMT /slideshow/dagstuhl14-introv1/36179888 timmenzies@slideshare.net(timmenzies) Dagstuhl14 intro-v1 timmenzies <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/dagstuhl14-intro-v1-140623001334-phpapp01-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br>
Dagstuhl14 intro-v1 from CS, NcState
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Recommender workshop, ICSE'14]]>
Recommender workshop, ICSE'14]]> Wed, 28 May 2014 16:03:37 GMT /slideshow/menzies-dataminingrecommendersystems/35233400 timmenzies@slideshare.net(timmenzies) Know thy tools timmenzies Recommender workshop, ICSE'14 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/menziesdataminingrecommendersystems-140528160337-phpapp01-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Recommender workshop, ICSE&#39;14
Know thy tools from CS, NcState
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ICSE14 Tutorial]]>
ICSE14 Tutorial]]> Wed, 28 May 2014 15:05:59 GMT /slideshow/the-art-and-science-of-analyzing-software-data/35231317 timmenzies@slideshare.net(timmenzies) The Art and Science of Analyzing Software Data timmenzies ICSE14 Tutorial <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/icse14-tut-datascience-v2-140528150559-phpapp02-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> ICSE14 Tutorial
The Art and Science of Analyzing Software Data from CS, NcState
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