A systematic review of software architecture visualization techniques

ContextGiven the increased interest in using visualization techniques (VTs) to help communicate and understand software architecture (SA) of large scale complex systems, several VTs and tools have been reported to represent architectural elements (such as architecture design, architectural patterns, and architectural design decisions). However, there is no attempt to systematically review and classify the VTs and associated tools reported for SA, and how they have been assessed and applied.ObjectiveThis work aimed at systematically reviewing the literature on software architecture visualization to develop a classification of VTs in SA, analyze the level of reported evidence and the use of different VTs for representing SA in different application domains, and identify the gaps for future research in the area.MethodWe used systematic literature review (SLR) method of the evidence-based software engineering (EBSE) for reviewing the literature on VTs for SA. We used both manual and automatic search strategies for searching the relevant papers published between 1 February 1999 and 1 July 2011.ResultsWe selected 53 papers from the initially retrieved 23,056 articles for data extraction, analysis, and synthesis based on pre-defined inclusion and exclusion criteria. The results from the data analysis enabled us to classify the identified VTs into four types based on the usage popularity: graph-based, notation-based, matrix-based, and metaphor-based VTs. The VTs in SA are mostly used for architecture recovery and architectural evolution activities. We have also identified ten purposes of using VTs in SA. Our results also revealed that VTs in SA have been applied to a wide range of application domains, among which “graphics software” and “distributed system” have received the most attention.ConclusionSA visualization has gained significant importance in understanding and evolving software-intensive systems. However, only a few VTs have been employed in industrial practice. This review has enabled us to identify the following areas for further research and improvement: (i) it is necessary to perform more research on applying visualization techniques in architectural analysis, architectural synthesis, architectural implementation, and architecture reuse activities; (ii) it is essential to pay more attention to use more objective evaluation methods (e.g., controlled experiment) for providing more convincing evidence to support the promised benefits of using VTs in SA; (iii) it is important to conduct industrial surveys for investigating how software architecture practitioners actually employ VTs in architecting process and what are the issues that hinder and prevent them from adopting VTs in SA.     

A systematic review of systematic review process research in software engineering

ContextMany researchers adopting systematic reviews (SRs) have also published papers discussing problems with the SR methodology and suggestions for improving it. Since guidelines for SRs in software engineering (SE) were last updated in 2007, we believe it is time to investigate whether the guidelines need to be amended in the light of recent research.ObjectiveTo identify, evaluate and synthesize research published by software engineering researchers concerning their experiences of performing SRs and their proposals for improving the SR process.MethodWe undertook a systematic review of papers reporting experiences of undertaking SRs and/or discussing techniques that could be used to improve the SR process. Studies were classified with respect to the stage in the SR process they addressed, whether they related to education or problems faced by novices and whether they proposed the use of textual analysis tools.ResultsWe identified 68 papers reporting 63 unique studies published in SE conferences and journals between 2005 and mid-2012. The most common criticisms of SRs were that they take a long time, that SE digital libraries are not appropriate for broad literature searches and that assessing the quality of empirical studies of different types is difficult.ConclusionWe recommend removing advice to use structured questions to construct search strings and including advice to use a quasi-gold standard based on a limited manual search to assist the construction of search stings and evaluation of the search process. Textual analysis tools are likely to be useful for inclusion/exclusion decisions and search string construction but require more stringent evaluation. SE researchers would benefit from tools to manage the SR process but existing tools need independent validation. Quality assessment of studies using a variety of empirical methods remains a major problem.     

Knowledge-based approaches in software documentation: A systematic literature review

ContextSoftware documents are core artifacts produced and consumed in documentation activity in the software lifecycle. Meanwhile, knowledge-based approaches have been extensively used in software development for decades, however, the software engineering community lacks a comprehensive understanding on how knowledge-based approaches are used in software documentation, especially documentation of software architecture design.ObjectiveThe objective of this work is to explore how knowledge-based approaches are employed in software documentation, their influences to the quality of software documentation, and the costs and benefits of using these approaches.MethodWe use a systematic literature review method to identify the primary studies on knowledge-based approaches in software documentation, following a pre-defined review protocol.ResultsSixty studies are finally selected, in which twelve quality attributes of software documents, four cost categories, and nine benefit categories of using knowledge-based approaches in software documentation are identified. Architecture understanding is the top benefit of using knowledge-based approaches in software documentation. The cost of retrieving information from documents is the major concern when using knowledge-based approaches in software documentation.ConclusionsThe findings of this review suggest several future research directions that are critical and promising but underexplored in current research and practice: (1) there is a need to use knowledge-based approaches to improve the quality attributes of software documents that receive less attention, especially credibility, conciseness, and unambiguity; (2) using knowledge-based approaches with the knowledge content in software documents which gets less attention in current applications of knowledge-based approaches in software documentation, to further improve the practice of software documentation activity; (3) putting more focus on the application of software documents using the knowledge-based approaches (knowledge reuse, retrieval, reasoning, and sharing) in order to make the most use of software documents; and (4) evaluating the costs and benefits of using knowledge-based approaches in software documentation qualitatively and quantitatively.     

Testing scientific software: A systematic literature review

ContextScientific software plays an important role in critical decision making, for example making weather predictions based on climate models, and computation of evidence for research publications. Recently, scientists have had to retract publications due to errors caused by software faults. Systematic testing can identify such faults in code.ObjectiveThis study aims to identify specific challenges, proposed solutions, and unsolved problems faced when testing scientific software.MethodWe conducted a systematic literature survey to identify and analyze relevant literature. We identified 62 studies that provided relevant information about testing scientific software.ResultsWe found that challenges faced when testing scientific software fall into two main categories: (1) testing challenges that occur due to characteristics of scientific software such as oracle problems and (2) testing challenges that occur due to cultural differences between scientists and the software engineering community such as viewing the code and the model that it implements as inseparable entities. In addition, we identified methods to potentially overcome these challenges and their limitations. Finally we describe unsolved challenges and how software engineering researchers and practitioners can help to overcome them.ConclusionsScientific software presents special challenges for testing. Specifically, cultural differences between scientist developers and software engineers, along with the characteristics of the scientific software make testing more difficult. Existing techniques such as code clone detection can help to improve the testing process. Software engineers should consider special challenges posed by scientific software such as oracle problems when developing testing techniques.     

Software architecture awareness in long-term software product evolution

Software architecture has been established in software engineering for almost 40 years. When developing and evolving software products, architecture is expected to be even more relevant compared to contract development. However, the research results seem not to have influenced the development practice around software products very much. The architecture often only exists implicitly in discussions that accompany the development. Nonetheless many of the software products have been used for over 10, or even 20 years. How do development teams manage to accommodate changing needs and at the same time maintain the quality of the product? In order to answer this question, grounded theory study based on 15 semi-structured interviews was conducted in order to find out about the wide spectrum of architecture practices in software product developing organisations. Our results indicate that a chief architect or central developer acts as a ‘walking architecture’ devising changes and discussing local designs while at the same time updating his own knowledge about problematic aspects that need to be addressed. Architecture documentation and representations might not be used, especially if they replace the feedback from on-going developments into the ‘architecturing’ practices. Referring to results from Computer Supported Cooperative Work, we discuss how explicating the existing architecture needs to be complemented by social protocols to support the communication and knowledge sharing processes of the ‘walking architecture’.     

A systematic review of machine learning techniques for software fault prediction

BackgroundSoftware fault prediction is the process of developing models that can be used by the software practitioners in the early phases of software development life cycle for detecting faulty constructs such as modules or classes. There are various machine learning techniques used in the past for predicting faults.MethodIn this study we perform a systematic review of studies from January 1991 to October 2013 in the literature that use the machine learning techniques for software fault prediction. We assess the performance capability of the machine learning techniques in existing research for software fault prediction. We also compare the performance of the machine learning techniques with the statistical techniques and other machine learning techniques. Further the strengths and weaknesses of machine learning techniques are summarized.ResultsIn this paper we have identified 64 primary studies and seven categories of the machine learning techniques. The results prove the prediction capability of the machine learning techniques for classifying module/class as fault prone or not fault prone. The models using the machine learning techniques for estimating software fault proneness outperform the traditional statistical models.ConclusionBased on the results obtained from the systematic review, we conclude that the machine learning techniques have the ability for predicting software fault proneness and can be used by software practitioners and researchers. However, the application of the machine learning techniques in software fault prediction is still limited and more number of studies should be carried out in order to obtain well formed and generalizable results. We provide future guidelines to practitioners and researchers based on the results obtained in this work.     

Controlling software architecture erosion: A survey

Software architectures capture the most significant properties and design constraints of software systems. Thus, modifications to a system that violate its architectural principles can degrade system performance and shorten its useful lifetime. As the potential frequency and scale of software adaptations increase to meet rapidly changing requirements and business conditions, controlling such architecture erosion becomes an important concern for software architects and developers. This paper presents a survey of techniques and technologies that have been proposed over the years either to prevent architecture erosion or to detect and restore architectures that have been eroded. These approaches, which include tools, techniques and processes, are primarily classified into three generic categories that attempt to minimise, prevent and repair architecture erosion. Within these broad categories, each approach is further broken down reflecting the high-level strategies adopted to tackle erosion. These are: process-oriented architecture conformance, architecture evolution management, architecture design enforcement, architecture to implementation linkage, self-adaptation and architecture restoration techniques consisting of recovery, discovery and reconciliation. Some of these strategies contain sub-categories under which survey results are presented.We discuss the merits and weaknesses of each strategy and argue that no single strategy can address the problem of erosion. Further, we explore the possibility of combining strategies and present a case for further work in developing a holistic framework for controlling architecture erosion.     

Software evolution visualization: A systematic mapping study

BackgroundSoftware evolution is an important topic in software engineering. It generally deals with large amounts of data, as one must look at whole project histories as opposed to their current snapshot. Software visualization is the field of software engineering that aims to help people to understand software through the use of visual resources. It can be effectively used to analyze and understand the large amount of data produced during software evolution.ObjectiveThis study investigates Software Evolution Visualization (SEV) approaches, collecting evidence about how SEV research is structured, synthesizing current evidence on the goals of the proposed approaches and identifying key challenges for its use in practice.MethodsA mapping study was conducted to analyze how the SEV area is structured. Selected primary studies were classified and analyzed with respect to nine research questions.ResultsSEV has been used for many different purposes, especially for change comprehension, change prediction and contribution analysis. The analysis identified gaps in the studies with respect to their goals, strategies and approaches. It also pointed out to a widespread lack of empirical studies in the area.ConclusionResearchers have proposed many SEV approaches during the past years, but some have failed to clearly state their goals, tie them back to concrete problems, or formally validate their usefulness. The identified gaps indicate that there still are many opportunities to be explored in the area.     

A systematic literature review on the industrial use of software process simulation

ContextSoftware process simulation modelling (SPSM) captures the dynamic behaviour and uncertainty in the software process. Existing literature has conflicting claims about its practical usefulness: SPSM is useful and has an industrial impact; SPSM is useful and has no industrial impact yet; SPSM is not useful and has little potential for industry.ObjectiveTo assess the conflicting standpoints on the usefulness of SPSM.MethodA systematic literature review was performed to identify, assess and aggregate empirical evidence on the usefulness of SPSM.ResultsIn the primary studies, to date, the persistent trend is that of proof-of-concept applications of software process simulation for various purposes (e.g. estimation, training, process improvement, etc.). They score poorly on the stated quality criteria. Also only a few studies report some initial evaluation of the simulation models for the intended purposes.ConclusionThere is a lack of conclusive evidence to substantiate the claimed usefulness of SPSM for any of the intended purposes. A few studies that report the cost of applying simulation do not support the claim that it is an inexpensive method. Furthermore, there is a paramount need for improvement in conducting and reporting simulation studies with an emphasis on evaluation against the intended purpose.     

Using CMMI together with agile software development: A systematic review

BackgroundThe search for adherence to maturity levels by using lightweight processes that require low levels of effort is regarded as a challenge for software development organizations.ObjectiveThis study seeks to evaluate, synthesize, and present results on the use of the Capability Maturity Model Integration (CMMI) in combination with agile software development, and thereafter to give an overview of the topics researched, which includes a discussion of their benefits and limitations, the strength of the findings, and the implications for research and practice.MethodsThe method applied was a Systematic Literature Review on studies published up to (and including) 2011.ResultsThe search strategy identified 3193 results, of which 81 included studies on the use of CMMI together with agile methodologies. The benefits found were grouped into two main categories: those related to the organization in general and those related to the development process, and were organized into subcategories, according to the area to which they refer. The limitations were also grouped into these categories. Using the criteria defined, the strength of the evidence found was considered low. The implications of the results for research and practice are discussed.ConclusionAgile methodologies can be used by companies to reduce efforts in getting to levels 2 and 3 of CMMI, there even being reports of applying agile practices that led to achieving level 5. However, agile methodologies alone, according to the studies, were not sufficient to obtain a rating at a given level, it being necessary to resort to additional practices to do so.     

Analogy-based software development effort estimation: A systematic mapping and review

ContextAnalogy-based Software development Effort Estimation (ASEE) techniques have gained considerable attention from the software engineering community. However, existing systematic map and review studies on software development effort prediction have not investigated in depth several issues of ASEE techniques, to the exception of comparisons with other types of estimation techniques.ObjectiveThe objective of this research is twofold: (1) to classify ASEE studies which primary goal is to propose new or modified ASEE techniques according to five criteria: research approach, contribution type, techniques used in combination with ASEE methods, and ASEE steps, as well as identifying publication channels and trends and (2) to analyze these studies from five perspectives: estimation accuracy, accuracy comparison, estimation context, impact of the techniques used in combination with ASEE methods, and ASEE tools.MethodWe performed a systematic mapping of studies for which the primary goal is to develop or to improve ASEE techniques published in the period 1990–2012, and reviewed them based on an automated search of four electronic databases.ResultsIn total, we identified 65 studies published between 1990 and 2012, and classified them based on our predefined classification criteria. The mapping study revealed that most researchers focus on addressing problems related to the first step of an ASEE process, that is, feature and case subset selection. The results of our detailed analysis show that ASEE methods outperform the eight techniques with which they were compared, and tend to yield acceptable results especially when combining ASEE techniques with Fuzzy Logic (FL) or Genetic Algorithms (GA).ConclusionBased on the findings of this study, the use of other techniques such FL and GA in combination with an ASEE method is promising to generate more accurate estimates. However, the use of ASEE techniques by practitioners is still limited: developing more ASEE tools may facilitate the application of these techniques and then lead to increasing the use of ASEE techniques in industry.     

Software process modeling languages: A systematic literature review

ContextOrganizations working in software development are aware that processes are very important assets as well as they are very conscious of the need to deploy well-defined processes with the goal of improving software product development and, particularly, quality. Software process modeling languages are an important support for describing and managing software processes in software-intensive organizations.ObjectiveThis paper seeks to identify what software process modeling languages have been defined in last decade, the relationships and dependencies among them and, starting from the current state, to define directions for future research.MethodA systematic literature review was developed. 1929 papers were retrieved by a manual search in 9 databases and 46 primary studies were finally included.ResultsSince 2000 more than 40 languages have been first reported, each of which with a concrete purpose. We show that different base technologies have been used to define software process modeling languages. We provide a scheme where each language is registered together with the year it was created, the base technology used to define it and whether it is considered a starting point for later languages. This scheme is used to illustrate the trend in software process modeling languages. Finally, we present directions for future research.ConclusionThis review presents the different software process modeling languages that have been developed in the last ten years, showing the relevant fact that model-based SPMLs (Software Process Modeling Languages) are being considered as a current trend. Each one of these languages has been designed with a particular motivation, to solve problems which had been detected. However, there are still several problems to face, which have become evident in this review. This let us provide researchers with some guidelines for future research on this topic.     

Combining service-orientation and software product line engineering: A systematic mapping study

ContextService-Orientation (SO) is a rapidly emerging paradigm for the design and development of adaptive and dynamic software systems. Software Product Line Engineering (SPLE) has also gained attention as a promising and successful software reuse development paradigm over the last decade and proven to provide effective solutions to deal with managing the growing complexity of software systems.ObjectiveThis study aims at characterizing and identifying the existing research on employing and leveraging SO and SPLE.MethodWe conducted a systematic mapping study to identify and analyze related literature. We identified 81 primary studies, dated from 2000–2011 and classified them with respect to research focus, types of research and contribution.ResultThe mapping synthesizes the available evidence about combining the synergy points and integration of SO and SPLE. The analysis shows that the majority of studies focus on service variability modeling and adaptive systems by employing SPLE principles and approaches.In particular, SPLE approaches, especially feature-oriented approaches for variability modeling, have been applied to the design and development of service-oriented systems. While SO is employed in software product line contexts for the realization of product lines to reconcile the flexibility, scalability and dynamism in product derivations thereby creating dynamic software product lines.ConclusionOur study summarizes and characterizes the SO and SPLE topics researchers have investigated over the past decade and identifies promising research directions as due to the synergy generated by integrating methods and techniques from these two areas.     

Analysis of architecture evaluation data

The output of 18 software architecture evaluations is analyzed. The goal of the analysis is to find patterns in the important quality attributes and risk themes identified in the evaluations. The major results are

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A categorization of risk themes.

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The observation that twice as many risk themes are risks of “omission” as are risks of “commission”.

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A failure to find a relationship between the business and mission goals of a system and the risk themes from an evaluation of that system.

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A failure to find a correlation between the domain of a system being evaluated and the important quality attributes for that system.

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A wide diversity of names used for various quality attributes.

The results of this investigation have application to practitioners by suggesting activities on which developers should put greater focus. They also have application to researchers by suggesting further areas of investigation.     

Software architecture review by association

During the process of software design, software architects have their reasons to choose certain software components to address particular software requirements and constraints. However, existing software architecture review techniques often rely on the design reviewers’ knowledge and experience, and perhaps using some checklists, to identify design gaps and issues, without questioning the reasoning behind the decisions made by the architects. In this paper, we approach design reviews from a design reasoning perspective. We propose to use an association-based review procedure to identify design issues by first associating all the relevant design concerns, problems and solutions systematically; and then verifying if the causal relationships between these design elements are valid. Using this procedure, we discovered new design issues in all three industrial cases, despite their internal architecture reviews and one of the three systems being operational. With the newly found design issues, we derive eight general design reasoning failure scenarios.     

Scientific research ontology to support systematic review in software engineering

The term systematic review is used to refer to a specific methodology of research, developed in order to gather and evaluate the available evidence pertaining to a focused topic. It represents a secondary study that depends on primary study results to be accomplished. Several primary studies have been conducted in the field of Software Engineering in the last years, determining an increasing improvement in methodology. However, in most cases software is built with technologies and processes for which developers have insufficient evidence to confirm their suitability, limits, qualities, costs, and inherent risks. Conducting systematic reviews in Software Engineering consists in a major methodological tool to scientifically improve the validity of assertions that can be made in the field and, as a consequence, the reliability degree of the methods that are employed for developing software technologies and supporting software processes. This paper aims at discussing the significance of experimental studies, particularly systematic reviews, and their use in supporting software processes. A template designed to support systematic reviews in Software Engineering is presented, and the development of ontologies to describe knowledge regarding such experimental studies is also introduced.     

Using software evolution to focus architectural recovery

Ideally, a software project commences with requirements gathering and specification, reaches its major milestone with system implementation and delivery, and then continues, possibly indefinitely, into an operation and maintenance phase. The software system's architecture is in many ways the linchpin of this process: it is supposed to be an effective reification of the system's technical requirements and to be faithfully reflected in the system's implementation. Furthermore, the architecture is meant to guide system evolution, while also being updated in the process. However, in reality developers frequently deviate from the architecture, causing architectural erosion, a phenomenon in which the initial, “as documented' architecture of an application is (arbitrarily) modified to the point where its key properties no longer hold. Architectural recovery is a process frequently used to cope with architectural erosion whereby the current, “as implemented” architecture of a software system is extracted from the system's implementation. In this paper we propose a light-weight approach to architectural recovery, called Focus, which has three unique facets. First, Focus uses a system's evolution requirements to isolate and incrementally recover only the fragment of the system's architecture affected by the evolution. In this manner, Focus allows engineers to direct their primary attention to the part of the system that is immediately impacted by the desired change; subsequent changes will incrementally uncover additional parts of the system's architecture. Secondly, in addition to software components, which are the usual target of existing recovery approaches, Focus also recovers the key architectural notions of software connector and architectural style. Finally, Focus does not only recover a system's architecture, but may in fact rearchitect the system. We have applied and evaluated Focus in the context of several off-the-shelf applications and architectural styles to date. We discuss its key strengths and point out several open issues that will frame our future work.     

A systematic literature review of software requirements prioritization research

ContextDuring requirements engineering, prioritization is performed to grade or rank requirements in their order of importance and subsequent implementation releases. It is a major step taken in making crucial decisions so as to increase the economic value of a system.ObjectiveThe purpose of this study is to identify and analyze existing prioritization techniques in the context of the formulated research questions.MethodSearch terms with relevant keywords were used to identify primary studies that relate requirements prioritization classified under journal articles, conference papers, workshops, symposiums, book chapters and IEEE bulletins.Results73 Primary studies were selected from the search processes. Out of these studies; 13 were journal articles, 35 were conference papers and 8 were workshop papers. Furthermore, contributions from symposiums as well as IEEE bulletins were 2 each while the total number of book chapters amounted to 13.ConclusionPrioritization has been significantly discussed in the requirements engineering domain. However, it was generally discovered that, existing prioritization techniques suffer from a number of limitations which includes: lack of scalability, methods of dealing with rank updates during requirements evolution, coordination among stakeholders and requirements dependency issues. Also, the applicability of existing techniques in complex and real setting has not been reported yet.