A Correction to this paper has been published: 10.1007/s10664-020-09924-6

This paper proposes a new framework to measure the fairness of asymmetric level-design in multiplayer games. This work achieves real time prediction of the degree to which asymmetric levels are balanced using deep learning. The proposed framework provides both cost and time savings, by removing the requirement of numerous designed levels and the need to gather player data samples. This advancement with the field is possible through the combination of deep reinforcement learning (made accessible to developers with Unity’s ML-Agents framework), and Procedural Content Generation (PCG). The result of this merger is the acquisition of accelerated training data, which is established using parallel simulations. This paper showcases the proposed approach on a simple two player top-down -shooter game implemented using MoreMountains: Top Down Engine an extension to Unity 3D a popular game engine. Levels are generated using the same PCG approaches found in ’Nuclear Throne’ a popular cross platform Roguelike published by Vlambeer.

Feature Location (FL) aims to locate observable functionalities in source code. Considering its key role in software maintenance, a vast array of automated and semi-automated Feature Location Techniques (FLTs) have been proposed. To compare FLTs, an open, standard set of non-subjective, reproducible "compare-to" FLT techniques (baseline techniques) should be used for evaluation. In order to relate the performance of FLTs compared against different baseline techniques, these compare-to techniques should be evaluated against each other. But evaluation across FLTs is confounded by empirical designs that incorporate different FL goals and evaluation criteria. This paper moves towards standardizing FLT comparability by assessing eight baseline techniques in an empirical design that addresses these confounding factors. These baseline techniques are assessed in twelve case studies to rank their performance. Results of the case studies suggest that different baseline techniques perform differently and that VSM-Lucene and LSI-Matlab performed better than other implementations. By presenting the relative performances of baseline techniques this paper facilitates empirical cross-comparison of existing and future FLTs. Finally, the results suggest that the performance of FLTs partially depends on system/benchmark characteristics, in addition to the FLTs themselves.

In this paper, we discuss the feasibility of using an automated speech-to-speech pipeline to encode voice samples instead of regular voice codecs, in situations that require high data compression with high packet loss scenarios. To analyse the advantages of using a speech-to-text transcription as a voice encoder and a text-to-speech synthesis as a decoder and compare it against standard a PCM A-law codec, we have measured the error rate of user-transcribed sentences based on the Semantically Unpredictable Sentences (SUS) test. Some of the PCM speech samples were also played in a way to simulate poor network conditions, specifically 5% and 10% packet loss. These were added to compare the performance of the speech-to-text method to standard voice codecs. Additionally, we have evaluated how similar the transcribed messages were to the ground truth by measuring the Levenshtein distance between the sentences and also their Double Metaphone phonetic representations. We conclude it may be feasible to use speech-to-text as a codec, as the results of do not show a significant difference between the synthesised voice and the real voice.

Feature location (FL) is the task of finding the source code that implements a specific, user-observable functionality in a software system. It plays a key role in many software maintenance tasks and a wide variety of Feature Location Techniques (FLTs), which rely on source code structure or textual analysis, have been proposed by researchers. As FLTs evolve and more novel FLTs are introduced, it is important to perform comparison studies to investigate “Which are the best FLTs?” However, an initial reading of the literature suggests that performing such comparisons would be an arduous process, based on the large number of techniques to be compared, the heterogeneous nature of the empirical designs, and the lack of transparency in the literature. This article presents a systematic review of 170 FLT articles, published between the years 2000 and 2015. Results of the systematic review indicate that 95% of the articles studied are directed towards novelty, in that they propose a novel FLT. Sixty-nine percent of these novel FLTs are evaluated through standard empirical methods but, of those, only 9% use baseline technique(s) in their evaluations to allow cross comparison with other techniques. The heterogeneity of empirical evaluation is also clearly apparent: altogether, over 60 different FLT evaluation metrics are used across the 170 articles, 272 subject systems have been used, and 235 different benchmarks employed. The review also identifies numerous user input formats as contributing to the heterogeneity. Analysis of the existing research also suggests that only 27% of the FLTs presented might be reproduced from the published material. These findings suggest that comparison across the existing body of FLT evaluations is very difficult. We conclude by providing guidelines for empirical evaluation of FLTs that may ultimately help to standardise empirical research in the field, cognisant of FLTs with different goals, leveraging common practices in existing empirical evaluations and allied with rationalisations. This is seen as a step towards standardising evaluation in the field, thus facilitating comparison across FLTs.

Abstract Design abstractions such as components, modules, subsystems or packages are often not made explicit in the implementation of legacy systems. Indeed, often the abstractions that are made explicit turn out to be inappropriate for future evolution agendas. This can make the maintenance, evolution and refactoring of these systems difficult. In this publication, we carry out a fine‐grained evaluation of Reflexion Modelling as a technique for encapsulating user‐targeted components. This process is a prelude to component recovery, reuse and refactoring. The evaluation takes the form of twoin vivocase studies, where two professional software developers encapsulate components in a large, commercial software system. The studies demonstrate the validity of this approach and offer several best‐use guidelines. Specifically, they argue that users benefit from having a strong mental model of the system in advance of Reflexion Modelling, even if that model is flawed, and that users should expend effort exploring the expected relationships present in Reflexion Models. Copyright © 2008 John Wiley & Sons, Ltd.

Concept assignment approaches assist software engineers to comprehend software by localising problem domain concepts to source code elements. This paper presents an implementation of a concept assignment approach we call cognitive assignment which combines cognitive mapping of expert software engineers and Bayesian classification to help engineers tasked with understanding unfamiliar systems to localise a concepts implementation in the systems source

Fluid documents enable the interactive incorporation of related material into a primary document. Visual cues within primary material indicate that related content is available and user interaction reveals related content in context. Fluid documents reduce the need for explicit navigation, maintain context when considering related material and support synthesization of disjoint yet related information. Source code documents are an excellent medium for the application of fluid document technology. The definition of software in the form of text based documents manifests a highly linked and fragmented information space requiring considerable navigation between elements during code examination and comprehension. In this paper we present fluid source code views, the application of fluid document technology to source code documents

INFORM is a framework that provides J2EE application developers with an indication of how their code will perform whilst they are writing it. At present, software developers, especially those who are new to a development team, have little or no knowledge of how their changes to existing code will impact the response times of an application. For example, if a developer inappropriately utilises a high performance overhead service as part of their solution, their changes could have drastic negative consequences in terms of the QoS of the component. The goal of the INFORM framework is to collate performance information obtained from simulated workloads, model it and make it easily accessible to developers within their development environment, helping them to make better performance decisions whilst they are coding.

It is the view of many computer scientists that the standard of empirical software engineering research leaves scope for improvement. However, there is also an increasing awareness in the software engineering community that empirical studies are a vital aspect in the process of improving methods and tools, for software development and maintenance. This paper presents a review of the empirical work carried out to date in the area of program comprehension and illustrates that most of the evidence from these studies derives from lab-based experiments, thus implying a degree of artificial control. The paper argues that, in order to address the methodological shortfalls of the experimental paradigm, more qualitative methods need to be applied to accompany and support these quantitative studies, thus broadening the sources of data and increasing the 'body of evidence'.

Understanding the intricacies behind concurrency within object-oriented programming languages has always been a challenge for undergraduate students. While the lecture is a relatively passive learning experience for the student, the use of software visualisation offers the chance to examine the concepts covered in the lecture in an interactive, visual environment. Students can add further dimensions and greater depth to their understanding previously hindered by the pedagogy of this passive environment. Elucidate makes use of the JDI architecture in the Java language to create its own environment that allows students to execute any program within it. Elucidate utilises several information workspaces, each presenting a different perspective about the information, thus facilitating a students ability to employ it in a manner that best allows them to construct their own understanding. Students are able to navigate around multiple views, and through various levels of abstraction, revealing the inner workings and sequence of events in what would otherwise be a black-box program.

The adoption of concurrent programming techniques into mainstream system development has brought with it a problem in software comprehension. Stepping through the code is no longer adequate to ensure a student's understanding of how a concurrent program will execute. Elucidate attempts to rectify this inadequacy by giving the student the ability to dynamically explore the various threads of execution and event order of an executing concurrent program. The student can gain an understanding of the threads of control and how they relate to classes, object instantiation, destruction and method invocation. Elucidate adds a layer of abstraction that is capable of clearly exhibiting to the student many of the underlying problems associated with concurrent programming.