Software Engineering

International Summer Schools, ISSSE 2009-2011, Salerno, Italy. Revised Tutorial Lectures

herausgegeben von: Andrea De Lucia, Filomena Ferrucci

Verlag: Springer Berlin Heidelberg

Buchreihe : Lecture Notes in Computer Science

Enthalten in: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

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Über dieses Buch

Software engineering is widely recognized as one of the most exciting, stimulating, and profitable research areas, with a significant practical impact on the software industry. Thus, training future generations of software engineering researchers and bridging the gap between academia and industry are vital to the field. The International Summer School on Software Engineering (ISSSE), which started in 2003, aims to contribute both to training future researchers and to facilitating the exchange of knowledge between academia and industry. This volume consists of chapters originating from a number of tutorial lectures given in 2009, 2010, and 2011 at the International Summer School on Software Engineering, ISSSE, held in Salerno, Italy. The volume has been organized into three parts, focusing on software measurement and empirical software engineering, software analysis, and software management. The topics covered include software architectures, software product lines, model driven software engineering, mechatronic systems, aspect oriented software development, agile development processes, empirical software engineering, software maintenance, impact analysis, traceability management, software testing, and search-based software engineering.

Inhaltsverzeichnis

Frontmatter

Software Measurement and Empirical Software Engineering

Fundamental Aspects of Software Measurement

Abstract

Empirical studies are increasingly being used in Software Engineering research and practice. These studies rely on information obtained by measuring software artifacts and processes, and provide both measures and models based on measures as results. This paper illustrates a number of fundamental aspects of Software Measurement in the definition of measures that make sense, so they can be used appropriately. Specifically, we describe the foundations of measurement established by Measurement Theory and show how they can be used in Software Measurement for both internal and external software attributes. We also describe Axiomatic Approaches that have been defined in Software Measurement to capture the properties that measures for various software attributes are required to have. Finally, we show how Measurement Theory and Axiomatic Approaches can be used in an organized process for the definition and validation of measures used for building prediction models.

Sandro Morasca

Combining Evidence and Meta-analysis in Software Engineering

Abstract

Recently there has been a welcome move to realign software engineering as an evidence-based practice. Many research groups are actively conducting empirical research e.g. to compare different fault prediction models or the value of various architectural patterns. However, this brings some challenges. First, for a particular question, how can we locate all the relevant evidence (primary studies) and make sense of them in an unbiased way. Second, what if some of these primary studies are inconsistent? In which case how do we determine the ‘true’ answer? To address these challenges, software engineers are looking to other disciplines where the systematic review is normal practice (i.e. systematic, objective, transparent means of locating, evaluating and synthesising evidence to reach some evidence-based answer to a particular question). This chapter examines the history of empirical software engineering, overviews different meta-analysis methods and then describe the process of systematic reviews and conclude with some future directions and challenges for researchers.

Martin Shepperd

Predicting Bugs in Large Industrial Software Systems

Abstract

This chapter is a survey of close to ten years of software fault prediction research performed by our group. We describe our initial motivation, the variables used to make predictions, provide a description of our standard model based on Negative Binomial Regression, and summarize the results of using this model to make predictions for nine large industrial software systems. The systems range in size from hundreds of thousands to millions of lines of code. All have been in the field for multiple years and many releases, and continue to be maintained and enhanced, usually at 3 month intervals.

Effectiveness of the fault predictions is assessed using two different metrics. We compare the effectiveness of the standard model to augmented models that include variables related to developer counts, to inter-file calling structure, and to information about specific developers who modified the code.

We also evaluate alternate prediction models based on different training algorithms, including Recursive Partitioning, Bayesian Additive Regression Trees, and Random Forests.

Thomas J. Ostrand, Elaine J. Weyuker

Software Analysis

Natural Language-Based Software Analyses and Tools for Software Maintenance

Abstract

Significant portions of software life cycle resources are devoted to program maintenance, which motivates the development of automated techniques and tools to support the tedious, error-prone tasks. Natural language clues from programmers’ naming in literals, identifiers, and comments can be leveraged to improve the effectiveness of many software tools. For example, they can be used to increase the accuracy of software search tools, improve the ability of program navigation tools to recommend related methods, and raise the accuracy of other program analyses by providing access to natural language information. This chapter focuses on how to capture, model, and apply the programmers’ conceptual knowledge expressed in both linguistic information as well as programming language structure and semantics. We call this kind of analysis Natural Language Program Analysis (NLPA) since it combines natural language processing techniques with program analysis to extract information for analysis of the source program.

Lori Pollock, K. Vijay-Shanker, Emily Hill, Giriprasad Sridhara, David Shepherd

Text Retrieval Approaches for Concept Location in Source Code

Abstract

Concept location in source code is an essential activity during software change. It starts with a change request and results in a place in the source code where the change is to be implemented. As a program comprehension activity, it is also part of other software evolution tasks, such as, bug localization, recovery of traceability links between software artifacts, retrieving software components for reuse, etc. While concept location is primarily a human activity, tool support is necessary given the large amount of information encoded in source code. Many such tools rely on text retrieval techniques and help developers perform concept location much like document retrieval on web. This paper presents and discusses the applications of text retrieval to support concept location, in the context of software change.

Andrian Marcus, Sonia Haiduc

Discovering Services

Abstract

This tutorial paper presents an overview of existing approaches for service discovery and describes a service discovery framework that can support both static and dynamic service discovery. The framework and its extensions have been developed within the EU 6^th Framework projects SeCSE and Gredia and the EU 7^th Framework Network of Excellence S-Cube.

Andrea Zisman

Software Management

People-Centered Software Development: An Overview of Agile Methodologies

Abstract

This chapter gives an overview of agile software development processes and techniques. The first part of the chapter covers the major agile project management techniques with a focus on project planning. Iteration planning and interaction design approaches are given special focus. The second part of the chapter covers agile quality assurance with a focus on test-driven development and the state space of testing. Current problems in agile testing, including measuring test quality and testing applications with large state spaces, are discussed.

Frank Maurer, Theodore D. Hellmann

Open Source Practices in Software Product Line Engineering

Abstract

This chapter presents a short introduction to software product line engineering. It describes experiences of introducing software product line engineering in industry followed by a discussion on some problems in product line engineering originating from the distributed organisation that is involved in many cases. It addresses how solutions originating from open source software development may be used to solve the mentioned problems, and it describes some cases where open source practices have shown to be very useful.

Frank van der Linden

Backmatter

Titel: Software Engineering
herausgegeben von: Andrea De Lucia
Filomena Ferrucci
Verlag: Springer Berlin Heidelberg
Electronic ISBN: 978-3-642-36054-1
Print ISBN: 978-3-642-36053-4
DOI: https://doi.org/10.1007/978-3-642-36054-1