Can observational techniques help novices overcome the software inspection learning curve? An empirical investigation

When learning a new software engineering technique, there is a learning curve that must be overcome. In particular, when studies are conducted in a classroom setting, researchers need a method for quickly accelerating the experience of novice subjects to allow the results to be more applicable in industrial settings. In this paper, we propose and test a method to enable novices to gain process experience to allow them to more quickly overcome the learning curve. The method we evaluate allows an inspector to gain experience with the inspection process by observing an inspection performed by someone else. The results of the study show that the proposed method for gaining experience appears to be useful in some limited cases, that is, for low experienced subjects who were inspecting a requirements document from a domain in which they had low knowledge. Based on the results of this study, we are able to propose some new related hypotheses to be tested in future studies.     

Personality,emotional intelligence and work preferences in software engineering: An empirical study

ContextThere is an increasing awareness among Software Engineering (SE) researchers and practitioners that more focus is needed on understanding the engineers developing software. Previous studies show significant associations between the personalities of software engineers and their work preferences.ObjectiveVarious studies on personality in SE have found large, small or no effects and there is no consensus on the importance of psychometric measurements in SE. There is also a lack of studies employing other psychometric instruments or using larger datasets. We aim to evaluate our results in a larger sample, with software engineers in an earlier state of their career, using advanced statistics.MethodAn operational replication study where extensive psychometric data from 279 master level students have been collected in a SE program at a Swedish University. Personality data based on the Five-Factor Model, Trait Emotional Intelligence Questionnaire and Self-compassion have been collected. Statistical analysis investigated associations between psychometrics and work preferences and the results were compared to our previous findings from 47 SE professionals.ResultsAnalysis confirms existence of two main clusters of software engineers; one with more “intense” personalities than the other. This corroborates our earlier results on SE professionals. The student data also show similar associations between personalities and work preferences. However, for other associations there are differences due to the different population of subjects. We also found connections between the emotional intelligence and work preferences, while no associations were found for self-compassion.ConclusionThe associations can help managers to predict and adapt projects and tasks to available staff. The results also show that the Emotional Intelligence instrument can be predictive. The research methods and analytical tools we employ can detect subtle associations and reflect differences between different groups and populations and thus can be important tools for future research as well as industrial practice.     

Understanding the effects of requirements volatility in software engineering by using analytical modeling and software process simulation

This paper introduces an executable system dynamics simulation model developed to help project managers comprehend the complex impacts related to requirements volatility on a software development project. The simulator extends previous research and adds research results from an empirical survey, including over 50 new parameters derived from the associated survey data, to a base model. The paper discusses detailed results from two cases that show significant cost, schedule, and quality impacts as a result of requirements volatility. The simulator can be used as an effective tool to demonstrate the complex set of factor relationships and effects related to requirements volatility.     

A comparative study of software tools for user story management

ContextUser stories have become widely accepted in agile software development. Consequently, a great number of software tools that provide, inter alia, support for practices based on user stories have emerged in recent years. These tools may have different features and focus in terms of support for agile requirements engineering (RE) concepts and practices.ObjectiveThe present study aims to provide a deep insight into the current capabilities and future trends of software support for agile RE practices based on user stories.MethodA comparative qualitative study of a set of agile software tools has been conducted according to the following criteria: coverage of the key functional requirements, support for basic agile RE concepts and practices, and user satisfaction with the tool. The criteria for tool selection were: diversity of software tools, high rating on the user-stories community Web site (http://www.userstories.com), and availability for review.ResultsThe results show a generally good coverage of key functional requirements related to management of user stories and epics, high-level release planning and low-level iteration planning. On the other hand, user-role modeling and persona support have not been addressed at all, and it has been found that requirements for acceptance testing support were completely covered by only one tool. More importantly, the study has revealed significant differences in the way different tools support agile RE concepts and practices (if at all). Finally, qualitative analysis of user reviews has demonstrated that practitioners prefer tools that are easy to set up, easy to learn, easy to use, and easy to customize, over more sophisticated but simultaneously more demanding tools.ConclusionAlthough the progress that has been made since the inception of these tools is quite clear, there is still room for improvements in terms of support for various agile RE practices within a specific agile process.     

On the use of software design models in software development practice: An empirical investigation

Research into software design models in general, and into the UML in particular, focuses on answering the question how design models are used, completely ignoring the question if they are used. There is an assumption in the literature that the UML is the de facto standard, and that use of design models has had a profound and substantial effect on how software is designed by virtue of models giving the ability to do model-checking, code generation, or automated test generation. However for this assumption to be true, there has to be significant use of design models in practice by developers.This paper presents the results of a survey summarizing the answers of 3785 developers answering the simple question on the extent to which design models are used before coding. We relate their use of models with (i) total years of programming experience, (ii) open or closed development, (iii) educational level, (iv) programming language used, and (v) development type.The answer to our question was that design models are not used very extensively in industry, and where they are used, the use is informal and without tool support, and the notation is often not UML. The use of models decreased with an increase in experience and increased with higher level of qualification. Overall we found that models are used primarily as a communication and collaboration mechanism where there is a need to solve problems and/or get a joint understanding of the overall design in a group. We also conclude that models are seldom updated after initially created and are usually drawn on a whiteboard or on paper.     

An empirical study of the effect of complexity, platform, and program type on software development effort of business applications

Several popular cost estimation models like COCOMO and function points use adjustment variables, such as software complexity and platform, to modify original estimates and arrive at final estimates. Using data on 666 programs from 15 software projects, this study empirically tests a research model that studies the influence of three adjustment variables—software complexity, computer platform, and program type (batch or online programs) on software effort. The results confirm that all the three adjustment variables have a significant effect on effort. Further, multiple comparison of means also points to two other results for the data examined. Batch programs involve significantly higher software effort than online programs. Programs rated as complex have significantly higher effort than programs rated as average.     

Selection of third party software in Off-The-Shelf-based software development—An interview study with industrial practitioners

The success of software development using third party components highly depends on the ability to select a suitable component for the intended application. The evidence shows that there is limited knowledge about current industrial OTS selection practices. As a result, there is often a gap between theory and practice, and the proposed methods for supporting selection are rarely adopted in the industrial practice. This paper's goal is to investigate the actual industrial practice of component selection in order to provide an initial empirical basis that allows the reconciliation of research and industrial endeavors. The study consisted of semi-structured interviews with 23 employees from 20 different software-intensive companies that mostly develop web information system applications. It provides qualitative information that help to further understand these practices, and emphasize some aspects that have been overlooked by researchers. For instance, although the literature claims that component repositories are important for locating reusable components; these are hardly used in industrial practice. Instead, other resources that have not received considerable attention are used with this aim. Practices and potential market niches for software-intensive companies have been also identified. The results are valuable from both the research and the industrial perspectives as they provide a basis for formulating well-substantiated hypotheses and more effective improvement strategies.     

An empirical study of the impact of team size on software development effort

In this paper, we investigate the impact of team size on the software development effort. Using field data of over 200 software projects from various industries, we empirically test the impact of team size and other variables—such as software size in function points, ICASE tool and programming language type—on software development effort. Our results indicate that software size in function points significantly impacts the software development effort. The two-way interactions between function points and use of ICASE tool, and function points and language type are significant as well. Additionally, the interactions between team size and programming language type, and team size and use of ICASE tool were all significant.

An instrument for the measurement of customer perceptions of quality management in the software industry: An empirical study in India

Most of the available literature on quality management is based on management’s perception; few studies examine critical issues of quality management from the customer’s perspective, especially in the software industry. In order to gain an insight into what customers expect from a product/service, an analysis of quality management from customer’s point of view is essential. Such an understanding would help the managers to adopt strategies that can enhance the satisfaction level of their customers. The present study highlights the critical factors of quality management in the software industry from the customer’s perspective. Six critical factors are identified: and an instrument, comprising these factors, is developed and validated so as to measure the customer’s perception of quality management in the software industry. George Issac is an Assistant Professor in Mar Athanasius College of Engineering, Kothamangalam, India. He holds a B.Sc (Engg.) degree in Mechanical Engineering from Kerala University, and M.Tech and Ph.D degrees in Management from IIT Madras. His research areas are TQM and Organizational Behavior. He has published articles in the area of quality management in journals such as Total Quality Management and Business Excellence, and Quality Management Journal of American Society for Quality. Chandrasekharan Rajendran is a Professor of Operations Management in the Indian Institute of Technology Madras. His research interests are in TQM, Scheduling and Simulation. He has published several articles in international journals. He has publications in the area of TQM in journals such as Total Quality Management, International Journal of Production Research, International Journal of Service Industry Management, International Journal of Bank Marketing, and Journal of Services Marketing. He serves as referee for many journals. He is a recipient of the Alexander von Humboldt Fellowship of Germany. R.N. Anantharaman is a Professor of Management in the Indian Institute of Technology, Madras. His research interests are in TQM, Organizational Behavior and Industrial Psychology. He has published several articles in international journals. He has published research articles in the area of TQM, HRM Practices, Change Management, etc., in Journals such as Total Quality Management, International Journal of Production Research, International Journal of Bank Marketing, International Journal of Service Industry Management, Journal of Services Marketing, International Journal of Human Resource Management, and Journal of Transnational Management Development.     

An empirical study on students’ ability to comprehend design patterns

Design patterns have become a widely acknowledged software engineering practice and therefore have been incorporated in the curricula of most computer science departments. This paper presents an observational study on students’ ability to understand and apply design patterns. Within the context of a postgraduate software engineering course, students had to deliver two versions of a software system; one without and one with design patterns. The former served as a poorly designed system suffering from architectural problems, while the latter served as an improved system where design problems had been solved by appropriate patterns. The experiment allowed the quantitative evaluation of students’ preference to patterns. Moreover, it was possible to assess students’ ability in relating design problems with patterns and interpreting the impact of patterns on software metrics. The overall goal was to empirically identify ways in which a course on design patterns could be improved.     

The mechanisms of project management of software development

The changing environments of software development such as component-based, distributed and outsourced software development require matching changes by project managers to monitor, control and coordinate their projects. While the objectives of project management may be well established, the mechanisms with which those objectives are achieved are less well known. An empirical study was undertaken to investigate which mechanisms were used by practising project managers to monitor, control and coordinate software development projects.First, the types of mechanisms are discussed so that the mechanisms can be classified usefully. Then, the design of the empirical study is described. The data were collected through structured interview, which provided both quantitative and qualitative data. The data are analysed for each mechanism separately and the findings presented. The study found that project managers use multiple mechanisms to achieve project management objectives and use the same mechanism to serve multiple objectives. Further research is suggested to investigate project management from the opposite orientation, that is, which objectives are served by specific project management mechanisms.     

An experiment on linguistic tool support for consolidation of requirements from multiple sources in market-driven product development

This paper presents an experiment with a linguistic support tool for consolidation of requirements sets. The experiment is designed based on the requirements management process at a large market-driven software development company that develops generic solutions to satisfy many different customers. New requirements and requests for information are continuously issued, which must be analyzed and responded to. The new requirements should first be consolidated with the old to avoid reanalysis of previously elicited requirements and to complement existing requirements with new information. In the presented experiment, a new open-source tool is evaluated in a laboratory setting. The tool uses linguistic engineering techniques to calculate similarities between requirements and presents a ranked list of suggested similar requirements, between which links may be assigned. It is hypothesized that the proposed technique for finding and linking similar requirements makes the consolidation more efficient. The results show that subjects that are given the support provided by the tool are significantly more efficient and more correct in consolidating two requirements sets, than are subjects that do not get the support. The results suggest that the proposed techniques may give valuable support and save time in an industrial requirements consolidation process.     

Investigations about replication of empirical studies in software engineering: A systematic mapping study

ContextTwo recent mapping studies which were intended to verify the current state of replication of empirical studies in Software Engineering (SE) identified two sets of studies: empirical studies actually reporting replications (published between 1994 and 2012) and a second group of studies that are concerned with definitions, classifications, processes, guidelines, and other research topics or themes about replication work in empirical software engineering research (published between 1996 and 2012).ObjectiveIn this current article, our goal is to analyze and discuss the contents of the second set of studies about replications to increase our understanding of the current state of the work on replication in empirical software engineering research.MethodWe applied the systematic literature review method to build a systematic mapping study, in which the primary studies were collected by two previous mapping studies covering the period 1996–2012 complemented by manual and automatic search procedures that collected articles published in 2013.ResultsWe analyzed 37 papers reporting studies about replication published in the last 17 years. These papers explore different topics related to concepts and classifications, presented guidelines, and discuss theoretical issues that are relevant for our understanding of replication in our field. We also investigated how these 37 papers have been cited in the 135 replication papers published between 1994 and 2012.ConclusionsReplication in SE still lacks a set of standardized concepts and terminology, which has a negative impact on the replication work in our field. To improve this situation, it is important that the SE research community engage on an effort to create and evaluate taxonomy, frameworks, guidelines, and methodologies to fully support the development of replications.     

An exploratory study of architectural effects on requirements decisions

The question of the “manner in which an existing software architecture affects requirements decision-making” is considered important in the research community; however, to our knowledge, this issue has not been scientifically explored. We do not know, for example, the characteristics of such architectural effects. This paper describes an exploratory study on this question. Specific types of architectural effects on requirements decisions are identified, as are different aspects of the architecture together with the extent of their effects. This paper gives quantitative measures and qualitative interpretation of the findings. The understanding gained from this study has several implications in the areas of: project planning and risk management, requirements engineering (RE) and software architecture (SA) technology, architecture evolution, tighter integration of RE and SA processes, and middleware in architectures. Furthermore, we describe several new hypotheses that have emerged from this study, that provide grounds for future empirical work. This study involved six RE teams (of university students), whose task was to elicit new requirements for upgrading a pre-existing banking software infrastructure. The data collected was based on a new meta-model for requirements decisions, which is a bi-product of this study.     

An empirical analysis of the impact of software development problem factors on software maintainability

Many problem factors in the software development phase affect the maintainability of the delivered software systems. Therefore, understanding software development problem factors can help in not only reducing the incidence of project failure but can also ensure software maintainability. This study focuses on those software development problem factors which may possibly affect software maintainability. Twenty-five problem factors were classified into five dimensions; a questionnaire was designed and 137 software projects were surveyed. A K-means cluster analysis was performed to classify the projects into three groups of low, medium and high maintainability projects. For projects which had a higher level of severity of problem factors, the influence on software maintainability becomes more obvious. The influence of software process improvement (SPI) on project problems and the associated software maintainability was also examined in this study. Results suggest that SPI can help reduce the level of severity of the documentation quality and process management problems, and is only likely to enhance software maintainability to a medium level. Finally, the top 10 list of higher-severity software development problem factors was identified, and implications were discussed.     

An experimental evaluation of a higher-ordered-typed-functional specification-based test-generation technique

HOTTest is a model based test automation technique of software systems based on models of the system described using HaskellDB. HaskellDB is an embedded domain specific language derived from Haskell. HOTTest enforces a systematic abstraction process and exploits system invariants for automatically producing test cases for domain specific requirements. Use of functional languages for system modeling is a new concept and hence HOTTest is subject to concerns of usability, like any other new technique. Also, the syntax and the declarative style of Haskell based languages make them difficult to learn. Similar concerns can be raised for HOTTest as it shares the same syntax with Haskell. In this paper we describe an experiment designed to study the usability of HOTTest and to compare it with existing model based test design techniques. The results show that HOTTest is more usable than the traditional technique and demonstrate that the test suites produced by HOTTest are more effective and efficient than those generated using the traditional model based test design technique. Editor: James Miller     

An investigation of use case quality in a large safety-critical software development project

Use case modelling is a much-used technique for eliciting and documenting functional requirements. The quality of the use cases may have an important impact on the development project and on the resulting software product. This paper presents an empirical study of the changes that were made to the use case models in a large software project during the analysis phase. The results show (a) which were the most difficult aspects of use case modelling in this project and (b) how the quality of the functional requirements, in particular correctness, completeness, and clarity, was improved through the use case modelling process.