Software process anti-pattern detection in project data

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F19%3A43957538" target="_blank" >RIV/49777513:23520/19:43957538 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1145/3361149.3361169" target="_blank" >http://dx.doi.org/10.1145/3361149.3361169</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1145/3361149.3361169" target="_blank" >10.1145/3361149.3361169</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Software process anti-pattern detection in project data

Popis výsledku v původním jazyce

There is a significant amount of guidance on Project Management (PM) including software development methodologies, best practices and anti-patterns (APs). There is, however, a lack of automated way of applying this knowledge by analyzing readily available data from tools aiding in software PM, such as Application Lifecycle Management (ALM) tools. We propose a method of detecting process and PM anti-patterns in project data which can be used to warn software development teams about a potential threat to the project, or to conduct more general studies on the impact of AP occurrence on project success and product quality. We previously published a concept for the data mining and analysis toolset distinct from other research approaches and related work. Based on this toolset, we devised a formalized basis for our detection method in the form of standardized AP description template and a model for pattern operationalization over project data extracted from ALM tools. The main contribution of this paper is the general method for AP operationalization taking the description template as a starting point, discussed together with its potential limitations. We performed an initial validation of the method on data from student projects, using an AP we encountered in practice called “Collective Procrastination” which we also describe in this paper together with its detailed formal operationalization.

Název v anglickém jazyce

Software process anti-pattern detection in project data

Popis výsledku anglicky

There is a significant amount of guidance on Project Management (PM) including software development methodologies, best practices and anti-patterns (APs). There is, however, a lack of automated way of applying this knowledge by analyzing readily available data from tools aiding in software PM, such as Application Lifecycle Management (ALM) tools. We propose a method of detecting process and PM anti-patterns in project data which can be used to warn software development teams about a potential threat to the project, or to conduct more general studies on the impact of AP occurrence on project success and product quality. We previously published a concept for the data mining and analysis toolset distinct from other research approaches and related work. Based on this toolset, we devised a formalized basis for our detection method in the form of standardized AP description template and a model for pattern operationalization over project data extracted from ALM tools. The main contribution of this paper is the general method for AP operationalization taking the description template as a starting point, discussed together with its potential limitations. We performed an initial validation of the method on data from student projects, using an AP we encountered in practice called “Collective Procrastination” which we also describe in this paper together with its detailed formal operationalization.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/EF17_048%2F0007267" target="_blank" >EF17_048/0007267: VaV inteligentních komponent pokročilých technologií pro plzeňskou metropolitní oblast</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2019

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

EuroPLop &apos;19: Proceedings of the 24th European Conference on Pattern Languages of Programs

ISBN

978-1-4503-6206-1

ISSN

—

e-ISSN

—

Počet stran výsledku

12

Strana od-do

1-12

Název nakladatele

Association for Computing Machinery (ACM)

Místo vydání

New York

Místo konání akce

Irsee, Německo

Datum konání akce

3. 7. 2019

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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