TiwanaKeil04

1. Amrit Tiwana & Mark Keil
2. The One-Minute Risk Assessment Tool
3. Commun ACM V47n11(Nov 2004)pp73-77
4. =POLL PROJECT FAILURE
5. Who=MANAGERS 60 ORGANIZATIONS 720 project evaluations.
6. Success= 3*methodology fits + 1.9* customers involved+1.7*formal project management +1.5* similar to previous projects +1.1*simple + 0.9*requirements stable
7. Managers have little control over complexity and requirements stability,

Glass04c

1. Robert W Glass
2. Is This a Revolutionary Idea, or Not?
3. Commun ACM V47n11(Nov 2004)pp23-25
4. =ADVERT Dromey IDEA REQUIREMENTS as COMPONENTS

Denning04c

1. Peter J Denning
2. Network Laws
3. Commun ACM V47n11(Nov 2004)pp15-20
4. =SURVEY MATHEMATICS NETWORKS RANDOM GRAPHS POWER LAWS SMALL WORLDS
5. Clique: highly connected subset with few connections outside the clique.
6. Hubs: nodes with many links.
7. Broker: the only connection between a pair of cliques.
8. Bridge: connected to several cliques
9. In many real networks the Pr[k links at a node] = (1/k)**p, "power law".
10. Accounted for by new nodes being created at random and connecting to nodes with larger numbers of links.
11. Hubs are key for securing and using a network.
12. Command a network by communicating intent and delegating decision making.

Hazewinkel04

1. Michiel Hazewinkel
2. Mathematical Knowledge Management is Needed
3. Keynote speech at the November, 2003 MKM meeting at Herriott-Watt, Edinburgh, UK
4. =ESSAY MATHEMATICS
5. MKM::="Mathematical Knowledge Management", Handling the vast amount of published mathematics.
6. In the 1970's 200,000 theorems where being published per year!
7. MSCS::="Mathematical Subject Classification Scheme", tree structure with 5500 leaves

YingEtal04

1. Annie T T Ying & Gail C Murphy & Raymond Ng & Mark C Chu-Carroll
2. Predicting Source Code Changes by Mining Change History
3. IEEE Trans Software Engineering V30n9(Sep 2004)pp574-586
4. =EXPERIMENT MINING EVOLUTION CHANGES Eclipse Mozilla SCM Java CVS C++
5. Using data mining to find common patterns of changes to a file, given a developer wishes to change a set files S then the system recommends looking at a larger set R of files that will all need changing.
6. Used frequent pattern mining: count number of times a set changes occurred together in the data base. Use an FP-Tree.
7. Produced obvious, interesting and even surprising recommendations.
8. A chi-square correlated set mining algorithm failed!

Krutchen03

1. Phillippe Krutchen
2. The Rational Unified Process: an Introduction
3. Addison-Wesley Longman Boston MA 2003 ISBN 0321197704 CR 0411-1339
4. =UNREAD RUP PROCESS UML

Reijers03

1. Hajo A Reijers
2. Design and control of Workflow Processes
3. Springer-Verlag New York, Secaucus NJ 2003 ISBN 3540011862 CR 0411-1321
4. =UNREAD WORKFLOW SWN PETRI BPR PBWD

ClementsEtal02

1. Paul Clements & David Garlan & Len Bass & Judith Stafford & Robert Nord & James Ivers & Reed Little
2. Documenting Software Architectures: Views and beyond
3. Pearson Education, Upper Saddle River NJ 2002 ISBN 0201703726 CR 0411-1291
4. =UNREAD ARCHITECTURE VIEWS STYLES UML
5. Notes

Skowronski04

1. Victor Skowronski
2. Do Agile Methods Marginalize Problem Solvers?
3. IEEE Computer Magazine V37n10(Oct 2004)pp120+118-119
4. =ESSAY PROBLEM SOLVING vs AGILE
5. Agile environment may block the preparation; incubation; illumination;verification cycle.
6. No time to incubate when producing code?
7. Problem solvers tend to be thing-oriented and without people-skills.
8. Perhaps it would be best to note use agile methods when their are several unsolved problems in a project!
   
9. (dick) |- Note: no data presented. Not even anecdotal. Should stir up some discussion!

SmithS04

1. Sean Smith
2. Magic Boxes and Botts: Security in Hardware
3. IEEE Computer Magazine V37n10(Oct 2004)pp106-
4. =HISTORY SECURE CHIPS TPM TCPA TCG
5. Notes

HarelRumpe04

1. David Harel & Bernhard Rumpe
2. Meaningful Modeling: What's the Semantics of "Semantics"
3. IEEE Computer Magazine V37n10(Oct 2004)pp64-72
4. =ESSAY GRAPHIC LANGUAGES SYNTAX vs SEMANTICS DENOTATIONAL STATECHARTS UML
5. Semantics needs a domain and a special function that maps correct syntax into this domain. These in turn need notations.
6. Notes

Anon04

1. Anon
2. Managing Complexity
3. The Economist (Nov27-Dec3 2004)pp71-73
4. =SURVEY PROJECT RISKS COSTS FAILURE :. TOOLS ITERATION AGILE OPEN SOURCE IBM IRS MS BORLAND BGI BTO

SaiedianRaguraman04

1. Hossein Saiedian & Srikrishnan Raguraman
2. Using UML-based Rate monotone analysis to predict schedulability
3. IEEE Computer Magazine V37n10(Oct 2004)pp56-63
4. =ADVERT UML PROFILE RMA QUALITIES TIMING
5. cf [AlvarezDiazLlopisPimentalTroya04]