Malcolm Munro

Bio: Malcolm Munro is an academic researcher from Durham University. The author has contributed to research in topics: Software maintenance & Software construction. The author has an hindex of 31, co-authored 169 publications receiving 3544 citations. Previous affiliations of Malcolm Munro include King's College London & University of Sunderland.

Service-based software: the future for flexible software

Abstract: For the past 40 years, the techniques, processes and methods of software development have been dominated by supply-side issues, giving rise to a software industry oriented towards developers rather than users. To achieve the levels of functionality, flexibility and time-to-market required by users, a radical shift is required in the development of software, with a more demand-centric view, leading to software which will be delivered as a service within the framework of an open marketplace. Already, there are some signs that this approach is being adopted by industry, but in a very limited way. We summarise research and a research method which has resulted in a long-term strategic view of software engineering innovation. Based on this foundation, we describe more recent work, which has resulted in an innovative demand-side model for the future of software. We propose a service architecture in which components may be bound instantly, just at the time they are needed, and then the binding may be discarded. A major benefit of this approach is that it leads to highly flexible and agile software that should be able to meet rapidly changing business needs.

Understanding service-oriented software

Abstract: Many hail service-oriented software as the next revolution in software development. Web services' capabilities are constantly expanding from simple message passing toward the construction of full-fledged applications such as those envisaged by the UK's Pennine Group in their Software as a Service (SaaS) framework. These new, service-oriented approaches appear to many to solve the significant issue of software inflexibility that arises during maintenance and evolution. While they address sonic aspects of the problem, however, understanding the software still poses some difficulty. This shift toward service orientation compels us to consider its implications for software understanding, which is potentially the primary cost in software engineering. Using an example of on-the-fly software services construction, we discuss the problems software engineers still face when working with service-oriented software. We also introduce some new issues that they must consider, including how to address service provision difficulties and failures.

Understanding function behaviors through program slicing

Abstract: We present conditioned slicing as a general slicing framework for program comprehension. A conditioned slice consists of a subset of program statements which preserves the behavior of the original program with respect to a set of program executions. The set of initial states of the program that characterize these executions is specified in terms of a first order logic formula on the input variables of the program. Conditioned slicing allows a better decomposition of the program giving the maintainer the possibility to analyze code fragments with respect to different perspectives. We also show how slices produced with traditional slicing methods can be reduced to conditioned slices. Conditioned slices can be identified by using symbolic execution techniques and dependence graphs.

An early impact analysis technique for software maintenance

Abstract: The accurate estimation of the resources required to implement a change in software is a difficult task. A method for doing this should include the analysis of the impact of the change on the existing system. A number of techniques for analysing the impact of a change on the source code have been described in the literature. While these techniques provide a good example of how to apply ripple effect analysis to source code, a weakness in these approaches is that they can be difficult to apply in the risk assessment phase of a project. This is because the source code is often not very well understood at this phase, and change proposals are written at a much higher level of abstraction than the code. It is therefore often the case that in practice subjective impact analysis methods are used for risk assessment and project investment appraisal. The underestimated resources for dealing with the ripple effects of a change can result in project schedules becoming so tight that only the minimal quality is achieved. This paper surveys existing ripple analysis techniques and then presents a new technique for the early detection of ripple effects based on a simple graph-theoretic model of documentation and the themes within the documentation. The objective is to investigate the basis of a technique for analysing and measuring the impact of a change on the entire system that includes not only the source code but the specification and design documentation of a system, and an early phase in the maintenance process.

Virtual but visible software

Abstract: The problem of trying to view and comprehend large amounts of data is a well-known one. A specialised version of this problem, that of visualising program code (often known as software visualisation) has suffered from the field refusing to embrace new ideas and technologies. The paper presents an application of virtual reality to this problem and highlights areas of importance from virtual reality that have been used to good effect when creating graphical abstractions of Java source code. A summary of the achievements of this approach and the relationship to the virtual reality features believed to be most beneficial is provided.

The C programming language

Abstract: This ebook is the first authorized digital version of Kernighan and Ritchie's 1988 classic, The C Programming Language (2nd Ed.). One of the best-selling programming books published in the last fifty years, "K&R" has been called everything from the "bible" to "a landmark in computer science" and it has influenced generations of programmers. Available now for all leading ebook platforms, this concise and beautifully written text is a "must-have" reference for every serious programmers digital library. As modestly described by the authors in the Preface to the First Edition, this "is not an introductory programming manual; it assumes some familiarity with basic programming concepts like variables, assignment statements, loops, and functions. Nonetheless, a novice programmer should be able to read along and pick up the language, although access to a more knowledgeable colleague will help."

Search‐based software test data generation: a survey

Abstract: The use of metaheuristic search techniques for the automatic generation of test data has been a burgeoning interest for many researchers in recent years. Previous attempts to automate the test generation process have been limited, having been constrained by the size and complexity of software, and the basic fact that in general, test data generation is an undecidable problem. Metaheuristic search techniques oer much promise in regard to these problems. Metaheuristic search techniques are highlevel frameworks, which utilise heuristics to seek solutions for combinatorial problems at a reasonable computational cost. To date, metaheuristic search techniques have been applied to automate test data generation for structural and functional testing; the testing of grey-box properties, for example safety constraints; and also non-functional properties, such as worst-case execution time. This paper surveys some of the work undertaken in this eld, discussing possible new future directions of research for each of its dieren t individual areas.

Dynamically discovering likely program invariants to support program evolution

Abstract: Explicitly stated program invariants can help programmers by identifying program properties that must be preserved when modifying code. In practice, however, these invariants are usually implicit. An alternative to expecting programmers to fully annotate code with invariants is to automatically infer likely invariants from the program itself. This research focuses on dynamic techniques for discovering invariants from execution traces. This article reports three results. First, it describes techniques for dynamically discovering invariants, along with an implementation, named Daikon, that embodies these techniques. Second, it reports on the application of Daikon to two sets of target programs. In programs from Gries's work (1981) on program derivation, the system rediscovered predefined invariants. In a C program lacking explicit invariants, the system discovered invariants that assisted a software evolution task. These experiments demonstrate that, at least for small programs, invariant inference is both accurate and useful. Third, it analyzes scalability issues, such as invariant detection runtime and accuracy, as functions of test suites and program points instrumented.