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Software Metrics: A Rigorous and Practical Approach

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TLDR
The Second Edition of Software Metrics provides an up-to-date, coherent, and rigorous framework for controlling, managing, and predicting software development processes.
Abstract
From the Publisher: The Second Edition of Software Metrics provides an up-to-date, coherent, and rigorous framework for controlling, managing, and predicting software development processes. With an emphasis on real-world applications, Fenton and Pfleeger apply basic ideas in measurement theory to quantify software development resources, processes, and products. The book offers an accessible and comprehensive introduction to software metrics, now an essential component of software engineering for both classroom and industry. Software Metrics features extensive case studies from Hewlett Packard, IBM, the U.S. Department of Defense, Motorola, and others, in addition to worked examples and exercises. The Second Edition includes up-to-date material on process maturity and measurement, goal-question-metric, planning a metrics program, measurement in practice, experimentation, empirical studies, ISO9216, and metric tools.

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Dissertation

Automated support for process assessment in Test-Driven Development

TL;DR: This dissertation claims that an analysis of past software changes can indicate TDD process violations, and proposes process compliance indices (PCIs) to interpret the analysis results in order to focus a manual process assessment effort.

How Many Tests are Enough

TL;DR: While the above tools have all proved useful in their test domains, they may not be universally applicable: * Certain optimizations require expensive pre-processing, such as [33].
Proceedings ArticleDOI

Specification and Construction of Control Flow Semantics

TL;DR: A translation from CFSL to graph production systems (GPS) for flow graph construction is presented, that is, any CFSL specification, say for a language L, gives rise to a GPS that constructs from any L-program the corresponding flow graph.
Proceedings ArticleDOI

Towards Cross Project Vulnerability Prediction in Open Source Web Applications

TL;DR: This work presents an empirical study aiming at clarifying how useful cross project prediction techniques in predicting software vulnerabilities are, and employs the classification provided by different machine learning techniques to improve the detection of vulnerable components.