{"id":20071293,"url":"https://github.com/cptanalatriste/techdebt-game-model","last_synced_at":"2026-06-07T04:31:48.796Z","repository":{"id":145889448,"uuid":"145003426","full_name":"cptanalatriste/techdebt-game-model","owner":"cptanalatriste","description":"A game-theoretic model of technical debt.","archived":false,"fork":false,"pushed_at":"2020-09-08T06:51:49.000Z","size":386,"stargazers_count":3,"open_issues_count":0,"forks_count":1,"subscribers_count":2,"default_branch":"master","last_synced_at":"2025-01-12T23:48:14.898Z","etag":null,"topics":["game-theory","simulation","technical-debt"],"latest_commit_sha":null,"homepage":"https://www.sciencedirect.com/science/article/pii/S0164121219301980","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/cptanalatriste.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null}},"created_at":"2018-08-16T15:01:15.000Z","updated_at":"2023-09-08T22:38:25.000Z","dependencies_parsed_at":"2023-09-24T16:56:42.615Z","dependency_job_id":null,"html_url":"https://github.com/cptanalatriste/techdebt-game-model","commit_stats":{"total_commits":35,"total_committers":1,"mean_commits":35.0,"dds":0.0,"last_synced_commit":"edfbaf7611c87044c096b9a2f89dc594b35da563"},"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cptanalatriste%2Ftechdebt-game-model","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cptanalatriste%2Ftechdebt-game-model/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cptanalatriste%2Ftechdebt-game-model/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cptanalatriste%2Ftechdebt-game-model/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/cptanalatriste","download_url":"https://codeload.github.com/cptanalatriste/techdebt-game-model/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":241502792,"owners_count":19972956,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["game-theory","simulation","technical-debt"],"created_at":"2024-11-13T14:28:31.173Z","updated_at":"2026-06-07T04:31:48.738Z","avatar_url":"https://github.com/cptanalatriste.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Equilibrium Analysis for Technical Debt\n\n*For an in-depht discussion of our empirical game-theoretic model, you can read our paper in the Journal of Systems and Software: https://www.sciencedirect.com/science/article/pii/S0164121219301980*\n\nThis model can generate the payoff values for a payoff matrix representing technical debt. After triggering the script `payoffbuilder.py`, the payoff information per strategy profile will be stored in the file `payoff_table_builder.log`.\nThis values can be later ported to a game solver like [Gambit](http://www.gambit-project.org/) to obtain its Nash Equilibrium.\n\nSome relevant parameters of `payoffbuilder.py` are:\n\n* `simulation_episodes` at line 44 controls the number of simulation iterations to execute.\nThe payoff values generated by the script is the average number of fixes per developer over these \niterations.\n* `sloppy_rework_factor` at line 48 controls the increased probability that a kludge commit will later generate rework, like a bug or a change request due to code review.\n\nThe payoff values are generated via simulation. Simulation-specific parameters are exposed via the script `trainingdriver.py`. \nSome of them are:\n\n* `SCENARIO_TIME_UNITS` at line 13 is the time units simulated during an iteration.\n* `SCENARIO_AVG_RESOLUTION_TIME` at line 14 is the average resolution time of a programming task.\n* `SCENARIO_PROB_REWORK` at line 15 is the base probability of rework for the project.\n\n\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcptanalatriste%2Ftechdebt-game-model","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcptanalatriste%2Ftechdebt-game-model","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcptanalatriste%2Ftechdebt-game-model/lists"}