Esempio n. 1
0
        public void Story_refinement()
        {
            var historicalStoryRefinementsA = new[] { 1, 2, 3 };
            var historicalStoryRefinementsB = new[] { 10, 20, 30 };
            var randomNumbers = new Queue <int>(new[] { 2, 1, 0, 2, 1, 0 });

            var sut = new SoftwareDeliverySimulation(3, maxNumber => randomNumbers.Dequeue());

            var result = sut.SimulateIssuesDerivedFromStories(historicalStoryRefinementsA, historicalStoryRefinementsB);

            Assert.Equal(new[] { 23, 31, 12 }, result);
        }
Esempio n. 2
0
        public void Forecast_10_stories_with_single_issue_forecast()
        {
            DateTime  START_DATE        = new DateTime(2019, 11, 18);
            const int NUMBER_OF_STORIES = 10;

            var issues         = IssueRepository.Import().ToArray();
            var issuesPerStory = issues.IssuesPerStory();

            var sut = new SoftwareDeliverySimulation();
            var issueSimulationresult = sut.SimulateIssuesDerivedFromStories(
                Enumerable.Range(1, NUMBER_OF_STORIES).Select(_ => issuesPerStory).ToArray()
                );
            var issueDistribution = Statistics.Distribution(issueSimulationresult);

            _testOutputHelper.WriteLine("issues from stories forecast");
            var deDE = new CultureInfo("de-DE");

            foreach (var x in issueDistribution.OrderBy(o => o.value))
            {
                _testOutputHelper.WriteLine($"{x.value}\t{x.frequency}\t{x.probability.ToString("0.000", deDE)}\t{x.percentile.ToString("0.0", deDE)}");
            }



            _testOutputHelper.WriteLine("delivery forecast");

            var number_of_issues = issueDistribution.First(x => x.percentile > 80.0).value;

            _testOutputHelper.WriteLine($"Number of issues selected: {number_of_issues}");

            var tp = issues.BusinessDayThroughputs();
            var deliverySimulationresult = sut.SimulateIssueDeliveryBasedOnThroughput(START_DATE, number_of_issues, tp);
            var distribution             = Statistics.Distribution(deliverySimulationresult);

            foreach (var x in distribution.OrderBy(o => o.value))
            {
                _testOutputHelper.WriteLine($"{x.value}\t{x.frequency}\t{x.probability.ToString("0.000", deDE)}\t{x.percentile.ToString("0.0", deDE)}");
            }
        }