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Identifying and Managing Complex Modules in Executable Software Design Models - Empirical Assessment of a Large Telecom Software Product
Ericsson AB.
Ericsson AB.
Linköping University, Department of Computer and Information Science, Software and Systems. Linköping University, Faculty of Science & Engineering.
Göteborgs Universitet.
2014 (English)In: 2014 Joint Conference of the International Workshop on Software Measurement and the International Conference on Software Process and Product Measurement (IWSM-MENSURA), Rotterdam, The Netherlands, October 6-8, 2014 / [ed] Frank Vogelezang & Maya Daneva, Los Alamitos: IEEE Computer Society, 2014, 243-251 p.Conference paper (Refereed)
Abstract [en]

Using design models instead of executable code has shown itself to be an efficient way of increasing abstraction level of software development. However, applying established code-based software engineering methods to design models can be a challenge - due to different abstraction levels, the same metrics as for code are not applicable for the design models. One of practical challenges in using metrics at the model level is applying complexity-prediction formulas developed using code-based metrics to design models. The existing formulas do not apply as they do not take into consideration the behavior part of the models - e.g. State charts. In this paper we address this challenge by conducting a case study at one of the large telecom products at Ericsson with the goal to identify which metrics can predict complex, hard to understand and hard to maintain software modules based on their design models. We use both statistical methods like regression to build prediction formulas and qualitative interviews to codify expert designers' perception of which software modules are complex. The results of this case study show that such measures as the number of non-self-transitions, transition per states or state depth can be combined in order to identify software units that are perceived as complex by expert designers. Our conclusion is that these metrics can be used in other companies to predict complex modules, but the coefficients should be recalculated per product to increase the prediction accuracy.

Place, publisher, year, edition, pages
Los Alamitos: IEEE Computer Society, 2014. 243-251 p.
Keyword [en]
complexity, maintainability, modeling, reliability, software metrics
National Category
Software Engineering
Identifiers
URN: urn:nbn:se:liu:diva-118997DOI: 10.1109/IWSM.Mensura.2014.27ISBN: 978-1-4799-4174-2OAI: oai:DiVA.org:liu-118997DiVA: diva2:817728
Conference
2014 Joint Conference of the International Workshop on Software Measurement and the International Conference on Software Process and Product Measurement (IWSM-MENSURA), Rotterdam, The Netherlands, October 6-8, 2014
Funder
Linköpings universitet
Available from: 2015-06-05 Created: 2015-06-05 Last updated: 2015-06-18

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ReferencesLink to record
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