POM4

List of changes in POM4 compared to POM3:

* Replaced Requirements with User Stories
* Added Sprints
* Changed Execution
* Models time of completion (Velocity)
* No product Backlog as mentioned earlier--Not relevant


Sample output:

[Cost, Score, completion, idle, velocity]

[2409.671458440433, 0.8841628909936482, 0.29411764705882354, 0.7058823529411764, 28.1]
[2308.2960550738408, 0.7867703286312365, 0.3660130718954248, 0.6339869281045751, 28.791666666666668]
[2570.022284498054, 0.8192890455541242, 0.3492063492063492, 0.6507936507936508, 28.15]
[1776.6221769857425, 0.8934120231082071, 0.06578947368421052, 0.9305555555555556, 18.25]
[2663.5466581317396, 0.8377502677420756, 0.20610687022900764, 0.7923076923076923, 24.583333333333332]
[2873.7679677836973, 0.8005907722786698, 0.30708661417322836, 0.6929133858267716, 28.0625]
[2974.0503086683807, 0.9211912145791122, 0.13821138211382114, 0.8571428571428572, 21.375]
[2254.083309388589, 0.8483742963781609, 0.22875816993464052, 0.7712418300653595, 27.125]
[2252.9218006369865, 0.8187803230043464, 0.10588235294117647, 0.8881987577639752, 24.125]
[1970.4420192421026, 0.8980781700913005, 0.10382513661202186, 0.8716216216216216, 28.083333333333332]
[2239.8372694910295, 0.7732764195049752, 0.4065040650406504, 0.5934959349593496, 28.041666666666668]
[2490.8178434146753, 0.8548533334449776, 0.30158730158730157, 0.6984126984126984, 27.6875]
[2090.459851323212, 0.906146585636779, 0.09595959595959595, 0.8983957219251337, 28.875]
[2487.32661497613, 0.8025235096809521, 0.310126582278481, 0.689873417721519, 28.541666666666668]
[1999.257417423182, 0.7881805570666411, 0.15263157894736842, 0.8473684210526315, 28.166666666666668]
[2659.3639169614175, 0.8136230090693194, 0.44715447154471544, 0.5528455284552846, 31.416666666666668]
[2518.5831627767234, 0.7714916788706024, 0.3984375, 0.6015625, 28.458333333333332]
[2653.9829039013243, 0.7942550808491925, 0.3898305084745763, 0.6101694915254237, 27.916666666666668]
[2520.328542653908, 0.8374772551439275, 0.29545454545454547, 0.7045454545454546, 28.4375]
[2544.763860934486, 0.8723176429348501, 0.11711711711711711, 0.8828828828828829, 26.0]
[2628.456723197506, 0.8203655792518135, 0.39316239316239315, 0.6068376068376069, 28.8]
[2573.503127321302, 0.7884237959629854, 0.3142857142857143, 0.6857142857142857, 26.55]
[1961.7933461746904, 0.8152854455707702, 0.27350427350427353, 0.7264957264957265, 27.875]
[2316.8948214132224, 0.8217888256150522, 0.21951219512195122, 0.7804878048780488, 28.583333333333332]
[2480.6806520346904, 0.8747529690927919, 0.16923076923076924, 0.8211382113821138, 26.583333333333332]
[2659.449863697794, 0.9241150906277656, 0.10285714285714286, 0.8971428571428571, 21.75]
[2670.630413055988, 0.8185772070791713, 0.44660194174757284, 0.5533980582524272, 26.833333333333332]
[2261.9032345883297, 0.880074563709406, 0.3673469387755102, 0.6326530612244898, 26.5]
[2803.9527726963315, 0.8112949960654825, 0.4020618556701031, 0.5760869565217391, 24.4]
[1789.2637140962051, 0.9134638787851941, 0.1320754716981132, 0.8571428571428572, 26.25]
[2551.9635529278703, 0.8700612111658858, 0.2184873949579832, 0.7777777777777778, 27.583333333333332]
[2715.4994139204637, 0.8218098445599464, 0.19718309859154928, 0.8028169014084507, 25.8125]
[2792.223819921654, 0.8980444641536334, 0.25510204081632654, 0.7448979591836735, 28.583333333333332]
[2484.5482551716327, 0.8902994085435698, 0.2127659574468085, 0.7872340425531915, 25.333333333333332]
[2723.6434810973956, 0.7986069896029132, 0.3389830508474576, 0.6610169491525424, 29.125]
[2927.417113886656, 0.8386515663739715, 0.3037037037037037, 0.6962962962962963, 28.9375]
[2295.532964721932, 0.8358459503202905, 0.20437956204379562, 0.7956204379562044, 28.25]
[2312.3109954731426, 0.7936932169797876, 0.3, 0.7, 27.625]
[2043.7151661914083, 0.8710077212863819, 0.1721311475409836, 0.7835051546391752, 23.25]
[2331.391170948724, 0.7928084070500105, 0.296875, 0.703125, 31.25]
[3078.8501033528346, 0.8888925374805372, 0.2549019607843137, 0.7450980392156863, 24.166666666666668]
[3100.958248463834, 0.7515307494535662, 0.23893805309734514, 0.7610619469026548, 26.9375]
[2199.850852366886, 0.8303671112167473, 0.21022727272727273, 0.7897727272727273, 26.875]
[2232.2895282162535, 0.904199293106172, 0.10559006211180125, 0.8944099378881988, 27.25]
[2795.6273106821627, 0.8801933995960874, 0.18115942028985507, 0.8188405797101449, 23.0]
[3066.9233408587424, 0.8898168997188672, 0.16822429906542055, 0.8317757009345794, 23.75]
[2887.73100680117, 0.9125038606759316, 0.12149532710280374, 0.8785046728971962, 22.25]
[2848.9219718849586, 0.9314492852738758, 0.11564625850340136, 0.8721804511278195, 25.75]
[2423.8773329190794, 0.8759079531570052, 0.20353982300884957, 0.7964601769911505, 23.083333333333332]
[2125.342000582769, 0.8306157810083096, 0.23270440251572327, 0.7672955974842768, 26.6875]



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> SPRINT LENGTH is considered as 30 days as given in the "ScrumBut" paper

> Time estimates are randomly assigned in the range(0,30) and are changed randomly based on team dynamism and culture.

> Velocity represents average time of completion for each sprint.

______________________________________________________________

Currently analyzing JMOO_V0 and hooking POM4 to JMOO. ETA: 2-3 days

POM4

Scrum'med POM3? Or Generic POM based model with more agile support?

Requirements

*1. Input and output remains same as POM3. More outputs--velocity/burndown charts?Or Need any changes?

*2. Instead of pom3_requirements--Add user stories. Each user story has..

   -Number of teams.

   -Estimate size.(s)

   -Priority.

   -Cost.

   -Value.

   =Generate them at random and (min<Sum(s)<max)--min,max predefined

   ?Heap or not?

   ?Implementing changes on the go?

3. Teams in pom3 remains the same. If any, Make Changes in pom3_teams according to (2)

*4. Maintain product backlog at all times.

    -Divide user stories into sprints and assign sprint to each team.

    -If team completes one sprint, assign one more. loop it.

    -Manage release backlog? Set of sprints at random as "release backlog".

    -End of each sprint update release backlog and calculate velocity.

5. Have to figure a way to score? Use pareto frontier as base as in POM3? Any other idea?