Data from configuration management tools as sources for software process mining

Process mining has proven to be a valuable approach that provides new and objective insights into processes within organizations. Based on sets of well-structured data, the underlying ‘actual’ processes can be extracted and process models can be constructed automatically, i.e., the process model can be ‘mined’. Successful process mining depends on the availability of well-structured and suitable data. This paper investigates the potential of software configuration management (SCM) and SCM- tools for software process mining. In a validation section, data collected by a SCM tool in practice are used to apply process-mining techniques on a particular software process, i.e., a Change Control Board (CCB) process in a large industrial company. Application of process mining techniques revealed that although people tend to believe that formally specified and well-documented processes are followed, the ‘actual’ process in practice is different. Control-flow discovery revealed that in the CCB process in most of the cases, i.e., 70%, an important CCB task ‘Analysis’ was skipped

Branden als EGM-maatregel

Periodiek branden is een traditionele gebruiks- of beheermethode die in het verleden op meerdere plaatsen werd toegepast. Dit gebeurde met name in heideterreinen en soms in duingraslanden, om de vegetatie te verjongen en de opslag van struiken en bomen tegen te gaan. geleidelijk is de beheersmethode uit het zicht verdwenen. In dit rapport zijn de ervaringen met periodiek branden en de kennis die er in binnenland en buitenland is over de effecten op de beschikbaarheid van nutriënten, vegetatie en fauna op een rij gezet. Het rapport geeft aan in welke situaties branden een aantrekkelijke effectgerichte maatregel kan zijn. In dit onderzoek (in het kader van OBN) werkten samen: Stichting Bargerveen, Bware en Alterr

Integrating computer log files for process mining: a genetic algorithm inspired technique

Process mining techniques are applied to single computer log files. But many processes are supported by different software tools and are by consequence recorded into multiple log files. Therefore it would be interesting to find a way to automatically combine such a set of log files for one process. In this paper we describe a technique for merging log files based on a genetic algorithm. We show with a generated test case that this technique works and we give an extended overview of which research is needed to optimise and validate this technique

Learning Hybrid Process Models From Events: Process Discovery Without Faking Confidence

Process discovery techniques return process models that are either formal (precisely describing the possible behaviors) or informal (merely a "picture" not allowing for any form of formal reasoning). Formal models are able to classify traces (i.e., sequences of events) as fitting or non-fitting. Most process mining approaches described in the literature produce such models. This is in stark contrast with the over 25 available commercial process mining tools that only discover informal process models that remain deliberately vague on the precise set of possible traces. There are two main reasons why vendors resort to such models: scalability and simplicity. In this paper, we propose to combine the best of both worlds: discovering hybrid process models that have formal and informal elements. As a proof of concept we present a discovery technique based on hybrid Petri nets. These models allow for formal reasoning, but also reveal information that cannot be captured in mainstream formal models. A novel discovery algorithm returning hybrid Petri nets has been implemented in ProM and has been applied to several real-life event logs. The results clearly demonstrate the advantages of remaining "vague" when there is not enough "evidence" in the data or standard modeling constructs do not "fit". Moreover, the approach is scalable enough to be incorporated in industrial-strength process mining tools.Comment: 25 pages, 12 figure

Methodological issues in cross-cultural research

Regardless of whether the research goal is to establish cultural universals or to identify and explain cross-cultural differences, researchers need measures that are comparable across different cultures when conducting cross-cultural studies. In this chapter, we describe two major strategies for enhancing cross-cultural comparability. First, we discuss a priori methods to ensure the comparability of data in cross-cultural surveys. In particular, we review findings on cross-cultural differences based on the psychology of survey response and provide suggestions on how to deal with these cultural differences in the survey design stage. Second, we discuss post hoc methods to ascertain data comparability and enable comparisons in the presence of threats to equivalence

Fosfaattoevoeging heide

Contains fulltext : 163301.pdf (publisher's version ) (Open Access

Steenmeel in droge bossen

Op grote schaal treedt op de hogere zandgronden verminderde vitaliteit van bomen en zelfs sterfte van eiken op. Dit komt vooral door droogte en verzuring. Het gebruik van steenmeel in droge bossen zou een oplossing kunnen zijn voor de nadelige effecten van verzuring. In een driejarig OBN-onderzoek is een literatuurstudie gedaan en zijn experimenten uitgevoerd in Het Nationale Park De Hoge Veluwe en in het Mastbos (Breda). In deze veldwerkplaats zijn de resultaten gepresenteerd van dit onderzoek naar het effect van steenmeel op de vitaliteit, groei en vegetatie van eiken, op de bodem- en de bladchemie en op het bodemleven in eikenbossen. Het toepassen van steenmeel lijkt veelbelovend na drie jaar experimenteren, maar meer onderzoek is gewenst. Aan een Plan van Aanpak voor de toediening van steenmeel in de praktijk wordt gewerkt. In het Nationale Park De Hoge Veluwe zijn de experimenten en andere eikenpercelen in de praktijk bekeken en bediscussieerd