Slideshows by User: timmenzies http://www.slideshare.net/ http://www.slideshare.net/images/logo.gif SlideShare http://www.slideshare.net/ Sun, 20 Jul 2008 14:15:27 GMT SlideShare feed for Slideshows by User: timmenzies Nearest neighbor, defect prediction http://www.slideshare.net/timmenzies/nearest-neighbor-defect-prediction-520819

from: timmenzies 6 days ago

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from: timmenzies 6 days ago

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]]> Sun, 20 Jul 2008 14:15:27 GMT http://www.slideshare.net/timmenzies/nearest-neighbor-defect-prediction-520819 timmenzies@slideshare.net(timmenzies) Nearest neighbor, defect prediction timmenzies <div class='snap_preview'><img src="http://cdn.slideshare.net/defects08v2-1216563365395118-8-thumbnail-2?1216563327" alt ="" style="border:1px solid #C3E6D8;float:right;" /> <p>from: <a href="http://www.slideshare.net/timmenzies">timmenzies</a> 6 days ago</p><p></p><p>Tags: None</p></div> Nearest neighbor, defect prediction
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]]> 31 0 http://cdn.slideshare.net/defects08v2-1216563365395118-8-thumbnail-2?1216563327 Defects08 V2 http://www.slideshare.net/timmenzies/defects08-v2

from: timmenzies 1 week ago

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from: timmenzies 1 week ago

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]]> Fri, 18 Jul 2008 01:43:32 GMT http://www.slideshare.net/timmenzies/defects08-v2 timmenzies@slideshare.net(timmenzies) Defects08 V2 timmenzies <div class='snap_preview'><img src="http://cdn.slideshare.net/defects08v2-1216345842049115-9-thumbnail-2?1216345416" alt ="" style="border:1px solid #C3E6D8;float:right;" /> <p>from: <a href="http://www.slideshare.net/timmenzies">timmenzies</a> 1 week ago</p><p></p><p>Tags: None</p></div> Defects08 V2
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]]> 0 0 http://cdn.slideshare.net/defects08v2-1216345842049115-9-thumbnail-2?1216345416 AADL http://www.slideshare.net/timmenzies/aadl

from: timmenzies 3 weeks ago

AADL slides

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from: timmenzies 3 weeks ago

AADL slides

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]]> Tue, 01 Jul 2008 16:22:23 GMT http://www.slideshare.net/timmenzies/aadl timmenzies@slideshare.net(timmenzies) AADL timmenzies AADL slides <div class='snap_preview'><img src="http://cdn.slideshare.net/aadlrev1-1214929665537614-9-thumbnail-2?1214929347" alt ="" style="border:1px solid #C3E6D8;float:right;" /> <p>from: <a href="http://www.slideshare.net/timmenzies">timmenzies</a> 3 weeks ago</p><p>AADL slides</p><p>Tags: None</p></div> AADL
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]]> 44 0 http://cdn.slideshare.net/aadlrev1-1214929665537614-9-thumbnail-2?1214929347 Java PathFinder http://www.slideshare.net/timmenzies/jpf-rev4

from: timmenzies 1 month ago

Java PathFinder slides

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from: timmenzies 1 month ago

Java PathFinder slides

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]]> Tue, 24 Jun 2008 16:54:51 GMT http://www.slideshare.net/timmenzies/jpf-rev4 timmenzies@slideshare.net(timmenzies) Java PathFinder timmenzies Java PathFinder slides <div class='snap_preview'><img src="http://cdn.slideshare.net/jpfrev4-1214326436724730-8-thumbnail-2?1214931514" alt ="" style="border:1px solid #C3E6D8;float:right;" /> <p>from: <a href="http://www.slideshare.net/timmenzies">timmenzies</a> 1 month ago</p><p>Java PathFinder slides</p><p>Tags: None</p></div> Java PathFinder
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]]> 51 0 http://cdn.slideshare.net/jpfrev4-1214326436724730-8-thumbnail-2?1214931514 RapidRma http://www.slideshare.net/timmenzies/rapidrma

from: timmenzies 1 month ago

Evaluation of RapidRMA software by ATL Intern Eddie Jesinsky

Tags: rapidrma rma rate monotonic analysis

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from: timmenzies 1 month ago

Evaluation of RapidRMA software by ATL Intern Eddie Jesinsky

Tags: rapidrma rma rate monotonic analysis

]]> Fri, 13 Jun 2008 18:42:28 GMT http://www.slideshare.net/timmenzies/rapidrma timmenzies@slideshare.net(timmenzies) RapidRma timmenzies Evaluation of RapidRMA software by ATL Intern Eddie Jesinsky <div class='snap_preview'><img src="http://cdn.slideshare.net/rapidrma-1213382650697885-9-thumbnail-2?1213382549" alt ="" style="border:1px solid #C3E6D8;float:right;" /> <p>from: <a href="http://www.slideshare.net/timmenzies">timmenzies</a> 1 month ago</p><p>Evaluation of RapidRMA software by ATL Intern Eddie Jesinsky</p><p>Tags: <a href="/tag/rapidrma" style="" title="" class="" target="" id="" >rapidrma</a> <a href="/tag/rma" style="" title="" class="" target="" id="" >rma</a> <a href="/tag/rate" style="" title="" class="" target="" id="" >rate</a> <a href="/tag/monotonic" style="" title="" class="" target="" id="" >monotonic</a> <a href="/tag/analysis" style="" title="" class="" target="" id="" >analysis</a> </p></div> rapidrma,rma,rate,monotonic,analysis, RapidRma
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]]> 237 0 http://cdn.slideshare.net/rapidrma-1213382650697885-9-thumbnail-2?1213382549 PathMATE http://www.slideshare.net/timmenzies/pathmate

from: timmenzies 1 month ago

Evaluation of PathMATE software by ATL Intern Eddie Jesinsky

Tags: pathmate code generation pathmate code

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from: timmenzies 1 month ago

Evaluation of PathMATE software by ATL Intern Eddie Jesinsky

Tags: pathmate code generation pathmate code

]]> Fri, 13 Jun 2008 18:42:28 GMT http://www.slideshare.net/timmenzies/pathmate timmenzies@slideshare.net(timmenzies) PathMATE timmenzies Evaluation of PathMATE software by ATL Intern Eddie Jesinsky <div class='snap_preview'><img src="http://cdn.slideshare.net/pathmate-1213382385391256-8-thumbnail-2?1213382550" alt ="" style="border:1px solid #C3E6D8;float:right;" /> <p>from: <a href="http://www.slideshare.net/timmenzies">timmenzies</a> 1 month ago</p><p>Evaluation of PathMATE software by ATL Intern Eddie Jesinsky</p><p>Tags: <a href="/tag/pathmate" style="" title="" class="" target="" id="" >pathmate</a> <a href="/tag/code" style="" title="" class="" target="" id="" >code</a> <a href="/tag/generation" style="" title="" class="" target="" id="" >generation</a> <a href="/tag/pathmate" style="" title="" class="" target="" id="" >pathmate</a> <a href="/tag/code" style="" title="" class="" target="" id="" >code</a> </p></div> pathmate,code,generation,pathmate,code, PathMATE
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]]> 280 0 http://cdn.slideshare.net/pathmate-1213382385391256-8-thumbnail-2?1213382550 Learning near optimum inspection policies http://www.slideshare.net/timmenzies/learning-near-optimum-inspection-policies

from: timmenzies 5 months ago

High assurance software requires extensive and expensive assessment. There are many forms of software assessment, ranging from manual inspections to automatic formal methods. These assessment methods differ in their effectiveness and the effort required to apply them. Typically, the more effective methods are more expensive. Hence, project managers often "bias" the assessment resources and apply more effort where they think that extra effort might be most useful. If most of the assessment effort explores project artifacts A,B,C,D, then that leaves a "blind spot" in E,F,G,H,I,.... Blind spots can compromise high assurance software. It is therefore important to discuss the bias introduced by the inspection policy. To but the matter in a nutshell, we need to ask "how blinding is our bias?" This talk contrasts three different kinds of "bias" in selecting what code modules to inspect: 1) manual methods such as "read the biggest thing first/last" 2) traditional data mining methods such as those advocated by author and those deployed in NASA-funded inspection tools. 3) a new data miner called "WHICH" We find that #1 usually outperforms #2 . This result calls into question many years of research by the speaker (translation: "oh dear....."). But we also find that #3 almost always out-performs #1 or #2 (translation: "phew!!"). In fact #3 works so well that we speculate that it could be used as a proxy for determining the actual number of defects remaining to be found, after inspecting Z% of the code. ABOUT THE SPEAKER: Dr. Tim Menzies (tim@menzies.us) has been working on advanced modeling and AI since 1986. He received his PhD from the University of New South Wales, Sydney, Australia and is the author of over 160 refereeed papers. A former research chair for NASA, Dr. Menzies is now a associate professor at the West Virginia University's Lane Department of Computer Science and Electrical Engineering. For more information, visit his web page at http:// menzies.us.

Tags: defect+prediction data+mining

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from: timmenzies 5 months ago

High assurance software requires extensive and expensive assessment. There are many forms of software assessment, ranging from manual inspections to automatic formal methods. These assessment methods differ in their effectiveness and the effort required to apply them. Typically, the more effective methods are more expensive. Hence, project managers often "bias" the assessment resources and apply more effort where they think that extra effort might be most useful. If most of the assessment effort explores project artifacts A,B,C,D, then that leaves a "blind spot" in E,F,G,H,I,.... Blind spots can compromise high assurance software. It is therefore important to discuss the bias introduced by the inspection policy. To but the matter in a nutshell, we need to ask "how blinding is our bias?" This talk contrasts three different kinds of "bias" in selecting what code modules to inspect: 1) manual methods such as "read the biggest thing first/last" 2) traditional data mining methods such as those advocated by author and those deployed in NASA-funded inspection tools. 3) a new data miner called "WHICH" We find that #1 usually outperforms #2 . This result calls into question many years of research by the speaker (translation: "oh dear....."). But we also find that #3 almost always out-performs #1 or #2 (translation: "phew!!"). In fact #3 works so well that we speculate that it could be used as a proxy for determining the actual number of defects remaining to be found, after inspecting Z% of the code. ABOUT THE SPEAKER: Dr. Tim Menzies (tim@menzies.us) has been working on advanced modeling and AI since 1986. He received his PhD from the University of New South Wales, Sydney, Australia and is the author of over 160 refereeed papers. A former research chair for NASA, Dr. Menzies is now a associate professor at the West Virginia University's Lane Department of Computer Science and Electrical Engineering. For more information, visit his web page at http:// menzies.us.

Tags: defect+prediction data+mining

]]> Wed, 06 Feb 2008 04:42:54 GMT http://www.slideshare.net/timmenzies/learning-near-optimum-inspection-policies timmenzies@slideshare.net(timmenzies) Learning near optimum inspection policies timmenzies High assurance software requires extensive and expensive assessment. There are many forms of software assessment, ranging from manual inspections to automatic formal methods. These assessment methods differ in their effectiveness and the effort required to apply them. Typically, the more effective methods are more expensive. Hence, project managers often "bias" the assessment resources and apply more effort where they think that extra effort might be most useful. If most of the assessment effort explores project artifacts A,B,C,D, then that leaves a "blind spot" in E,F,G,H,I,.... Blind spots can compromise high assurance software. It is therefore important to discuss the bias introduced by the inspection policy. To but the matter in a nutshell, we need to ask "how blinding is our bias?" This talk contrasts three different kinds of "bias" in selecting what code modules to inspect: 1) manual methods such as "read the biggest thing first/last" 2) traditional data mining methods such as those advocated by author and those deployed in NASA-funded inspection tools. 3) a new data miner called "WHICH" We find that #1 usually outperforms #2 . This result calls into question many years of research by the speaker (translation: "oh dear....."). But we also find that #3 almost always out-performs #1 or #2 (translation: "phew!!"). In fact #3 works so well that we speculate that it could be used as a proxy for determining the actual number of defects remaining to be found, after inspecting Z% of the code. ABOUT THE SPEAKER: Dr. Tim Menzies (tim@menzies.us) has been working on advanced modeling and AI since 1986. He received his PhD from the University of New South Wales, Sydney, Australia and is the author of over 160 refereeed papers. A former research chair for NASA, Dr. Menzies is now a associate professor at the West Virginia University's Lane Department of Computer Science and Electrical Engineering. For more information, visit his web page at http:// menzies.us. <div class='snap_preview'><img src="http://cdn.slideshare.net/learning-near-optimum-inspection-policies-1202272974393051-2-thumbnail-2?1202272974" alt ="" style="border:1px solid #C3E6D8;float:right;" /> <p>from: <a href="http://www.slideshare.net/timmenzies">timmenzies</a> 5 months ago</p><p>High assurance software requires extensive and expensive assessment. There are many forms of software assessment, ranging from manual inspections to automatic formal methods. These assessment methods differ in their effectiveness and the effort required to apply them. Typically, the more effective methods are more expensive. Hence, project managers often "bias" the assessment resources and apply more effort where they think that extra effort might be most useful. If most of the assessment effort explores project artifacts A,B,C,D, then that leaves a "blind spot" in E,F,G,H,I,.... Blind spots can compromise high assurance software. It is therefore important to discuss the bias introduced by the inspection policy. To but the matter in a nutshell, we need to ask "how blinding is our bias?" This talk contrasts three different kinds of "bias" in selecting what code modules to inspect: 1) manual methods such as "read the biggest thing first/last" 2) traditional data mining methods such as those advocated by author and those deployed in NASA-funded inspection tools. 3) a new data miner called "WHICH" We find that #1 usually outperforms #2 . This result calls into question many years of research by the speaker (translation: "oh dear....."). But we also find that #3 almost always out-performs #1 or #2 (translation: "phew!!"). In fact #3 works so well that we speculate that it could be used as a proxy for determining the actual number of defects remaining to be found, after inspecting Z% of the code. ABOUT THE SPEAKER: Dr. Tim Menzies (tim@menzies.us) has been working on advanced modeling and AI since 1986. He received his PhD from the University of New South Wales, Sydney, Australia and is the author of over 160 refereeed papers. A former research chair for NASA, Dr. Menzies is now a associate professor at the West Virginia University's Lane Department of Computer Science and Electrical Engineering. For more information, visit his web page at http:// menzies.us.</p><p>Tags: <a href="/tag/defect-prediction" style="" title="" class="" target="" id="" >defect+prediction</a> <a href="/tag/data-mining" style="" title="" class="" target="" id="" >data+mining</a> </p></div> defect+prediction,data+mining, Learning near optimum inspection policies
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]]> 540 0 http://cdn.slideshare.net/learning-near-optimum-inspection-policies-1202272974393051-2-thumbnail-2?1202272974 A Hybrid Approach to Expert and Model Based Effort Estimation http://www.slideshare.net/timmenzies/a-hybrid-approach-to-expert-and-model-based-effort-estimation

from: timmenzies 7 months ago

Masters thesis, CSEE, WVU

Tags: effort estimation cocomo feature subset

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from: timmenzies 7 months ago

Masters thesis, CSEE, WVU

Tags: effort estimation cocomo feature subset

]]> Wed, 05 Dec 2007 02:32:45 GMT http://www.slideshare.net/timmenzies/a-hybrid-approach-to-expert-and-model-based-effort-estimation timmenzies@slideshare.net(timmenzies) A Hybrid Approach to Expert and Model Based Effort Estimation timmenzies Masters thesis, CSEE, WVU <div class='snap_preview'><img src="http://cdn.slideshare.net/a-hybrid-approach-to-expert-and-model-based-effort-estimation-1196821964486266-4-thumbnail-2?1196821965" alt ="" style="border:1px solid #C3E6D8;float:right;" /> <p>from: <a href="http://www.slideshare.net/timmenzies">timmenzies</a> 7 months ago</p><p>Masters thesis, CSEE, WVU</p><p>Tags: <a href="/tag/effort" style="" title="" class="" target="" id="" >effort</a> <a href="/tag/estimation" style="" title="" class="" target="" id="" >estimation</a> <a href="/tag/cocomo" style="" title="" class="" target="" id="" >cocomo</a> <a href="/tag/feature" style="" title="" class="" target="" id="" >feature</a> <a href="/tag/subset" style="" title="" class="" target="" id="" >subset</a> </p></div> effort,estimation,cocomo,feature,subset, A Hybrid Approach to Expert and Model Based Effort Estimation
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]]> 631 0 http://cdn.slideshare.net/a-hybrid-approach-to-expert-and-model-based-effort-estimation-1196821964486266-4-thumbnail-2?1196821965 Open source: can you ignore it? http://www.slideshare.net/timmenzies/open-source-can-you-ignore-it

from: timmenzies 8 months ago

Tim Menzies

Tags: open+source presentation future history technology

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from: timmenzies 8 months ago

Tim Menzies

Tags: open+source presentation future history technology

]]> Sun, 11 Nov 2007 02:28:53 GMT http://www.slideshare.net/timmenzies/open-source-can-you-ignore-it timmenzies@slideshare.net(timmenzies) Open source: can you ignore it? timmenzies Tim Menzies <div class='snap_preview'><img src="http://cdn.slideshare.net/open-source-can-you-ignore-it-1194748132755315-3-thumbnail-2?1194748133" alt ="" style="border:1px solid #C3E6D8;float:right;" /> <p>from: <a href="http://www.slideshare.net/timmenzies">timmenzies</a> 8 months ago</p><p>Tim Menzies</p><p>Tags: <a href="/tag/open-source" style="" title="" class="" target="" id="" >open+source</a> <a href="/tag/presentation" style="" title="" class="" target="" id="" >presentation</a> <a href="/tag/future" style="" title="" class="" target="" id="" >future</a> <a href="/tag/history" style="" title="" class="" target="" id="" >history</a> <a href="/tag/technology" style="" title="" class="" target="" id="" >technology</a> </p></div> open+source,presentation,future,history,technology, Open source: can you ignore it?
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]]> 2613 5 http://cdn.slideshare.net/open-source-can-you-ignore-it-1194748132755315-3-thumbnail-2?1194748133 The business case for automated software engineering http://www.slideshare.net/timmenzies/the-business-case-for-automated-software-engineering

from: timmenzies 8 months ago

An ASE 2007 talk. Tim Menzies (WVU) Oussama Elrawas, Dan Baker (WVU) Jairus Hihn, Martin Feather (JPL) Ray Madachy, Barry Boehm (USC)

Tags: cocomo coqualmo simulated+annealing cocomo coqualmo

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from: timmenzies 8 months ago

An ASE 2007 talk. Tim Menzies (WVU) Oussama Elrawas, Dan Baker (WVU) Jairus Hihn, Martin Feather (JPL) Ray Madachy, Barry Boehm (USC)

Tags: cocomo coqualmo simulated+annealing cocomo coqualmo

]]> Sat, 10 Nov 2007 20:54:16 GMT http://www.slideshare.net/timmenzies/the-business-case-for-automated-software-engineering timmenzies@slideshare.net(timmenzies) The business case for automated software engineering timmenzies An ASE 2007 talk. Tim Menzies (WVU) Oussama Elrawas, Dan Baker (WVU) Jairus Hihn, Martin Feather (JPL) Ray Madachy, Barry Boehm (USC) <div class='snap_preview'><img src="http://cdn.slideshare.net/the-business-case-for-automated-software-engineering-1194728053795142-2-thumbnail-2?1194728056" alt ="" style="border:1px solid #C3E6D8;float:right;" /> <p>from: <a href="http://www.slideshare.net/timmenzies">timmenzies</a> 8 months ago</p><p>An ASE 2007 talk. Tim Menzies (WVU) Oussama Elrawas, Dan Baker (WVU) Jairus Hihn, Martin Feather (JPL) Ray Madachy, Barry Boehm (USC) </p><p>Tags: <a href="/tag/cocomo" style="" title="" class="" target="" id="" >cocomo</a> <a href="/tag/coqualmo" style="" title="" class="" target="" id="" >coqualmo</a> <a href="/tag/simulated-annealing" style="" title="" class="" target="" id="" >simulated+annealing</a> <a href="/tag/cocomo" style="" title="" class="" target="" id="" >cocomo</a> <a href="/tag/coqualmo" style="" title="" class="" target="" id="" >coqualmo</a> </p></div> cocomo,coqualmo,simulated+annealing,cocomo,coqualmo, The business case for automated software engineering
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]]> 708 0 http://cdn.slideshare.net/the-business-case-for-automated-software-engineering-1194728053795142-2-thumbnail-2?1194728056 Nighthawk: A Two-Level Genetic-Random Unit Test Data Generator http://www.slideshare.net/timmenzies/nighthawk-a-twolevel-geneticrandom-unit-test-data-generator

from: timmenzies 8 months ago

A talk to ASE 2007 by Jamie Andrews, Felix C. H. Li Department of Computer Science University of Western Ontario; and Tim Menzies Lane Department of Computer Science West Virginia University

Tags: unit+tests genetic+algorithms genetic+algorithms unit+tests

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from: timmenzies 8 months ago

A talk to ASE 2007 by Jamie Andrews, Felix C. H. Li Department of Computer Science University of Western Ontario; and Tim Menzies Lane Department of Computer Science West Virginia University

Tags: unit+tests genetic+algorithms genetic+algorithms unit+tests

]]> Sat, 10 Nov 2007 20:28:02 GMT http://www.slideshare.net/timmenzies/nighthawk-a-twolevel-geneticrandom-unit-test-data-generator timmenzies@slideshare.net(timmenzies) Nighthawk: A Two-Level Genetic-Random Unit Test Data Generator timmenzies A talk to ASE 2007 by Jamie Andrews, Felix C. H. Li Department of Computer Science University of Western Ontario; and Tim Menzies Lane Department of Computer Science West Virginia University <div class='snap_preview'><img src="http://cdn.slideshare.net/nighthawk-a-twolevel-geneticrandom-unit-test-data-generator-1194726479628114-3-thumbnail-2?1194726482" alt ="" style="border:1px solid #C3E6D8;float:right;" /> <p>from: <a href="http://www.slideshare.net/timmenzies">timmenzies</a> 8 months ago</p><p>A talk to ASE 2007 by Jamie Andrews, Felix C. H. Li Department of Computer Science University of Western Ontario; and Tim Menzies Lane Department of Computer Science West Virginia University</p><p>Tags: <a href="/tag/unit-tests" style="" title="" class="" target="" id="" >unit+tests</a> <a href="/tag/genetic-algorithms" style="" title="" class="" target="" id="" >genetic+algorithms</a> <a href="/tag/genetic-algorithms" style="" title="" class="" target="" id="" >genetic+algorithms</a> <a href="/tag/unit-tests" style="" title="" class="" target="" id="" >unit+tests</a> </p></div> unit+tests,genetic+algorithms,genetic+algorithms,unit+tests, Nighthawk: A Two-Level Genetic-Random Unit Test Data Generator
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]]> 649 0 http://cdn.slideshare.net/nighthawk-a-twolevel-geneticrandom-unit-test-data-generator-1194726479628114-3-thumbnail-2?1194726482 If you fix everything you lose fixes for everything else http://www.slideshare.net/timmenzies/if-you-fix-everything-you-lose-fixes-for-everything-else

from: timmenzies 8 months ago

International Workshop on Living with Uncertainty, IEEE ASE 2007, Atlanta, Georgia, Nov 5, 2007

Tags: abduction cocomo stochastic uncertainty collars

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from: timmenzies 8 months ago

International Workshop on Living with Uncertainty, IEEE ASE 2007, Atlanta, Georgia, Nov 5, 2007

Tags: abduction cocomo stochastic uncertainty collars

]]> Tue, 06 Nov 2007 03:46:26 GMT http://www.slideshare.net/timmenzies/if-you-fix-everything-you-lose-fixes-for-everything-else timmenzies@slideshare.net(timmenzies) If you fix everything you lose fixes for everything else timmenzies International Workshop on Living with Uncertainty, IEEE ASE 2007, Atlanta, Georgia, Nov 5, 2007 <div class='snap_preview'><img src="http://cdn.slideshare.net/if-you-fix-everything-you-lose-fixes-for-everything-else-1194320784655079-5-thumbnail-2?1194320786" alt ="" style="border:1px solid #C3E6D8;float:right;" /> <p>from: <a href="http://www.slideshare.net/timmenzies">timmenzies</a> 8 months ago</p><p>International Workshop on Living with Uncertainty, IEEE ASE 2007, Atlanta, Georgia, Nov 5, 2007 </p><p>Tags: <a href="/tag/abduction" style="" title="" class="" target="" id="" >abduction</a> <a href="/tag/cocomo" style="" title="" class="" target="" id="" >cocomo</a> <a href="/tag/stochastic" style="" title="" class="" target="" id="" >stochastic</a> <a href="/tag/uncertainty" style="" title="" class="" target="" id="" >uncertainty</a> <a href="/tag/collars" style="" title="" class="" target="" id="" >collars</a> </p></div> abduction,cocomo,stochastic,uncertainty,collars, If you fix everything you lose fixes for everything else
view presentation (tags: abduction cocomo stochastic uncertainty)
]]> 420 0 http://cdn.slideshare.net/if-you-fix-everything-you-lose-fixes-for-everything-else-1194320784655079-5-thumbnail-2?1194320786 Multi-implications of multi-dimensional authoring; or, “everything you wanted to know about geek herding, but were afraid to ask” http://www.slideshare.net/timmenzies/multiimplications-of-multidimensional-authoring-or-everything-you-wanted-to-know-about-geek-herding-but-were-afraid-to-ask

from: timmenzies 8 months ago

SLS '07 Portland, Maine

Tags: None

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from: timmenzies 8 months ago

SLS '07 Portland, Maine

Tags: None

]]> Sat, 03 Nov 2007 17:23:50 GMT http://www.slideshare.net/timmenzies/multiimplications-of-multidimensional-authoring-or-everything-you-wanted-to-know-about-geek-herding-but-were-afraid-to-ask timmenzies@slideshare.net(timmenzies) Multi-implications of multi-dimensional authoring; or, “everything you wanted to know about geek herding, but were afraid to ask” timmenzies SLS '07 Portland, Maine <div class='snap_preview'><img src="http://cdn.slideshare.net/multiimplications-of-multidimensional-authoring-or-everything-you-wanted-to-know-about-geek-herding-but-were-afraid-to-ask-1194110629287575-5-thumbnail-2?1194110630" alt ="" style="border:1px solid #C3E6D8;float:right;" /> <p>from: <a href="http://www.slideshare.net/timmenzies">timmenzies</a> 8 months ago</p><p>SLS '07 Portland, Maine</p><p>Tags: None</p></div> Multi-implications of multi-dimensional authoring; or, “everything you wanted to know about geek herding, but were afraid to ask”
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]]> 338 0 http://cdn.slideshare.net/multiimplications-of-multidimensional-authoring-or-everything-you-wanted-to-know-about-geek-herding-but-were-afraid-to-ask-1194110629287575-5-thumbnail-2?1194110630 2cee Master Cocomo20071 http://www.slideshare.net/timmenzies/2cee-master-cocomo20071

from: timmenzies 9 months ago

21st century effort estimation methods from JPL. Jairus Hihn (JPL), Tim Menzies (WVU), Karen Lum (JPL), Dan Baker (WVU)

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from: timmenzies 9 months ago

21st century effort estimation methods from JPL. Jairus Hihn (JPL), Tim Menzies (WVU), Karen Lum (JPL), Dan Baker (WVU)

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]]> Thu, 25 Oct 2007 18:58:24 GMT http://www.slideshare.net/timmenzies/2cee-master-cocomo20071 timmenzies@slideshare.net(timmenzies) 2cee Master Cocomo20071 timmenzies 21st century effort estimation methods from JPL. Jairus Hihn (JPL), Tim Menzies (WVU), Karen Lum (JPL), Dan Baker (WVU) <div class='snap_preview'><img src="http://cdn.slideshare.net/2cee-master-cocomo20071-1193338701341626-3-thumbnail-2?1193338704" alt ="" style="border:1px solid #C3E6D8;float:right;" /> <p>from: <a href="http://www.slideshare.net/timmenzies">timmenzies</a> 9 months ago</p><p>21st century effort estimation methods from JPL. Jairus Hihn (JPL), Tim Menzies (WVU), Karen Lum (JPL), Dan Baker (WVU)</p><p>Tags: None</p></div> 2cee Master Cocomo20071
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]]> 305 0 http://cdn.slideshare.net/2cee-master-cocomo20071-1193338701341626-3-thumbnail-2?1193338704 Star Master Cocomo07 http://www.slideshare.net/timmenzies/star-master-cocomo07

from: timmenzies 9 months ago

How to avoid local tuning. Tim Menzies (WVU) Jairus Hihn (JPL) Oussama Elrawas (WVU) Karen Lum (JPL) Dan Baker

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from: timmenzies 9 months ago

How to avoid local tuning. Tim Menzies (WVU) Jairus Hihn (JPL) Oussama Elrawas (WVU) Karen Lum (JPL) Dan Baker

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]]> Thu, 25 Oct 2007 18:58:22 GMT http://www.slideshare.net/timmenzies/star-master-cocomo07 timmenzies@slideshare.net(timmenzies) Star Master Cocomo07 timmenzies How to avoid local tuning. Tim Menzies (WVU) Jairus Hihn (JPL) Oussama Elrawas (WVU) Karen Lum (JPL) Dan Baker <div class='snap_preview'><img src="http://cdn.slideshare.net/star-master-cocomo07-1193338701336772-2-thumbnail-2?1193338702" alt ="" style="border:1px solid #C3E6D8;float:right;" /> <p>from: <a href="http://www.slideshare.net/timmenzies">timmenzies</a> 9 months ago</p><p>How to avoid local tuning. Tim Menzies (WVU) Jairus Hihn (JPL) Oussama Elrawas (WVU) Karen Lum (JPL) Dan Baker </p><p>Tags: None</p></div> Star Master Cocomo07
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]]> 400 0 http://cdn.slideshare.net/star-master-cocomo07-1193338701336772-2-thumbnail-2?1193338702 Sas 07 Costing http://www.slideshare.net/timmenzies/sas-07-costing

from: timmenzies 10 months ago

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]]> Sun, 30 Sep 2007 00:16:01 GMT http://www.slideshare.net/timmenzies/sas-07-costing timmenzies@slideshare.net(timmenzies) Sas 07 Costing timmenzies <div class='snap_preview'><img src="http://cdn.slideshare.net/sas-07-costing4485-thumbnail-2?1191111361" alt ="" style="border:1px solid #C3E6D8;float:right;" /> <p>from: <a href="http://www.slideshare.net/timmenzies">timmenzies</a> 10 months ago</p><p></p><p>Tags: None</p></div> Sas 07 Costing
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]]> 104 0 http://cdn.slideshare.net/sas-07-costing4485-thumbnail-2?1191111361 Sas 07 Anomalies http://www.slideshare.net/timmenzies/sas-07-anomalies

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]]> Sun, 30 Sep 2007 00:15:54 GMT http://www.slideshare.net/timmenzies/sas-07-anomalies timmenzies@slideshare.net(timmenzies) Sas 07 Anomalies timmenzies <div class='snap_preview'><img src="http://cdn.slideshare.net/sas-07-anomalies2035-thumbnail-2?1191111354" alt ="" style="border:1px solid #C3E6D8;float:right;" /> <p>from: <a href="http://www.slideshare.net/timmenzies">timmenzies</a> 10 months ago</p><p></p><p>Tags: None</p></div> Sas 07 Anomalies
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]]> 88 0 http://cdn.slideshare.net/sas-07-anomalies2035-thumbnail-2?1191111354 Data mining, truth, justice, the American Way, and the Giant Spaghetti Monster http://www.slideshare.net/timmenzies/data-mining-truth-justice-the-american-way-and-the-giant-spaghetti-monster

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]]> Sat, 22 Sep 2007 14:37:07 GMT http://www.slideshare.net/timmenzies/data-mining-truth-justice-the-american-way-and-the-giant-spaghetti-monster timmenzies@slideshare.net(timmenzies) Data mining, truth, justice, the American Way, and the Giant Spaghetti Monster timmenzies <div class='snap_preview'><img src="http://cdn.slideshare.net/data-mining-truth-justice-the-american-way-and-the-giant-spaghetti-monster471-thumbnail-2?1190471827" alt ="" style="border:1px solid #C3E6D8;float:right;" /> <p>from: <a href="http://www.slideshare.net/timmenzies">timmenzies</a> 10 months ago</p><p></p><p>Tags: None</p></div> Data mining, truth, justice, the American Way, and the Giant Spaghetti Monster
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]]> 405 0 http://cdn.slideshare.net/data-mining-truth-justice-the-american-way-and-the-giant-spaghetti-monster471-thumbnail-2?1190471827 Robustness testing http://www.slideshare.net/timmenzies/robustness-testing

from: timmenzies 11 months ago

NASA interns exploring robustness testing

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from: timmenzies 11 months ago

NASA interns exploring robustness testing

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]]> Mon, 13 Aug 2007 15:55:20 GMT http://www.slideshare.net/timmenzies/robustness-testing timmenzies@slideshare.net(timmenzies) Robustness testing timmenzies NASA interns exploring robustness testing <div class='snap_preview'><img src="http://cdn.slideshare.net/robustness-testing1251-thumbnail-2?1187020520" alt ="" style="border:1px solid #C3E6D8;float:right;" /> <p>from: <a href="http://www.slideshare.net/timmenzies">timmenzies</a> 11 months ago</p><p>NASA interns exploring robustness testing</p><p>Tags: None</p></div> Robustness testing
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]]> 154 0 http://cdn.slideshare.net/robustness-testing1251-thumbnail-2?1187020520 SpecTRM http://www.slideshare.net/timmenzies/spectrm

from: timmenzies 11 months ago

NASA interns exploring SpecTRM

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from: timmenzies 11 months ago

NASA interns exploring SpecTRM

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]]> Mon, 13 Aug 2007 15:49:24 GMT http://www.slideshare.net/timmenzies/spectrm timmenzies@slideshare.net(timmenzies) SpecTRM timmenzies NASA interns exploring SpecTRM <div class='snap_preview'><img src="http://cdn.slideshare.net/spectrm2572-thumbnail-2?1187020164" alt ="" style="border:1px solid #C3E6D8;float:right;" /> <p>from: <a href="http://www.slideshare.net/timmenzies">timmenzies</a> 11 months ago</p><p>NASA interns exploring SpecTRM</p><p>Tags: None</p></div> SpecTRM
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