Practical guidelines for measurement-based process improvement

Briand, Lionel C.; Differding, Christiane; Rombach, H. Dieter

doi:10.1002/(sici)1099-1670(199612)2:4<253::aid-spip53>3.0.co;2-g

Cited by 148 publications

(75 citation statements)

References 22 publications

(17 reference statements)

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“…CVS 1 ), mail archives from mailing list managers (e.g. Mailman 2 , Majordomo 3 , fml 4 ), and issue tracking records from (bug) issue tracking systems (e.g. GNATS 5 , Bugzilla 6 ).…”

Section: Empirical Project Monitor (Epm)mentioning

confidence: 99%

See 1 more Smart Citation

Empirical project monitor: a tool for mining multiple project data

Ohira¹,

Yokomori²,

Sakai³

et al. 2004

"International Workshop on Mining Software Repositories (MSR 2004)" W17S Workshop - 26th International Conference on Software E

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“…CVS 1 ), mail archives from mailing list managers (e.g. Mailman 2 , Majordomo 3 , fml 4 ), and issue tracking records from (bug) issue tracking systems (e.g. GNATS 5 , Bugzilla 6 ).…”

Section: Empirical Project Monitor (Epm)mentioning

confidence: 99%

“…Many software measurement methods have been proposed to better understand, monitor, control, and predict software processes and products [4]. For instance, the GoalQuestion-Metric (GQM) paradigm [2] provides a sophisticated measurement technique.…”

Section: Introductionmentioning

confidence: 99%

Empirical project monitor: a tool for mining multiple project data

Ohira¹,

Yokomori²,

Sakai³

et al. 2004

"International Workshop on Mining Software Repositories (MSR 2004)" W17S Workshop - 26th International Conference on Software E

View full text Add to dashboard Cite

show abstract

“…According to Briand et al [5], it is important to assess a software development process model to define the study objects of a measuring program, and, consequently, the necessary metrics to be collected. In the literature, artifactbased models are proposed to assist on the managing of projects, specially, distributed teams-based projects.…”

Section: Introductionmentioning

confidence: 99%

A Method to Build Bayesian Networks based on Artifacts and Metrics to Assess Agile Projects

Willamy¹,

Nunes²,

Perkusich

et al. 2016

International Conferences on Software Engineering and Knowledge Engineering

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Managing software development projects is a complex task because it requires organizing and monitoring several activities. Recently, in order to assist on software projects management, artifact-based models were proposed in the literature. However, the current solutions do not present means to monitor projects health and assist on decisions making. Due to the recent popularization of agile methods, they are the units of study of this research. In this work, we present a method to build artifact and measurementbased models to assess agile projects health. We applied the method to build a generic model based on industrys best practice. We defined the models artifacts and metrics based on findings of a literature review and the assistance of an expert. For each models artifact, we applied the Goal-Question-Metric paradigm to define the metrics. Afterwards, from the GQM meta-model, we constructed a Bayesian network. We validated the model with simulated scenarios. Given the successful results, we concluded that the method and model are promising.

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“…In order to assess quality characteristics (both general characteristics and key characteristics for SPL), software measures 1 are a good means to understand, monitor, control, predict, and test software development and maintenance projects [10]. Over the last few years, a great number of measures for evaluating the quality of SPLs have been proposed.…”

Section: Introductionmentioning

confidence: 99%

A systematic review of quality attributes and measures for software product lines

2011

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It is widely accepted that software measures provide an appropriate mechanism for understanding, monitoring, controlling and predicting the quality of software development projects. In Software Product Lines (SPL), quality is even more important than in a single software product since, owing to systematic reuse, a fault or an inadequate design decision could be propagated to several products in the family. Over the last few years, a great number of quality attributes and measures for assessing the quality of SPL have been reported in literature. However, no studies summarizing the current knowledge about them exist. This paper presents a systematic literature review with the objective of identifying and interpreting all the available studies from 1996 to date that present quality attributes and/or measures for SPL. These attributes and measures have been classified using a set of criteria that includes the life cycle phase in which the measures are applied; the corresponding quality characteristics; their support for specific SPL characteristics (e.g., variability, compositionality); the procedure used to validate the measures, etc. We found 165 measures related to 98 different quality attributes. The results of the review indicated that 92% of the measures evaluate attributes that are related to maintainability. In addition, 67% of the measures are used during the design phase of Domain Engineering, and 56% are applied to evaluate the product line architecture. However, only 25% of them have been empirically validated.In conclusion, the results provide a global vision of the state of the research within this area in order to help researchers in detecting weaknesses, directing research efforts, and identifying new research lines. In particular, there is a need for new measures with which to evaluate both the quality of the artifacts produced during the entire SPL life cycle and other quality characteristics. There is also a need for more validation (both theoretical and empirical) of existing measures. In addition, our results may be useful as a reference guide for practitioners to assist them in the selection or the adaptation of existing measures for evaluating their software product lines.

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Practical guidelines for measurement-based process improvement

Cited by 148 publications

References 22 publications

Empirical project monitor: a tool for mining multiple project data

Empirical project monitor: a tool for mining multiple project data

A Method to Build Bayesian Networks based on Artifacts and Metrics to Assess Agile Projects

A systematic review of quality attributes and measures for software product lines

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