Guenther Ruhe

University of Calgary, Computer Science, Faculty Member

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Papers by Guenther Ruhe

Optimized Resource Allocation for Software Release Planning

IEEE Transactions on Software Engineering, 2009

Release planning for incremental software development assigns features to releases such that tech... more Release planning for incremental software development assigns features to releases such that technical, resource, risk and budget constraints are met. Planning of software releases and allocation of resources cannot be handled in isolation. A feature can be offered as part of a release only if all its necessary tasks are done before the given release date. We assume a given pool of human resources with different degrees of productivity to perform different types of tasks. To address the inherent difficulty of this process, we propose a two-phased optimization approach that combines the strength of two existing solution methods. The industrial applicability of the approach is primarily directed towards mature organizations having systematic development and measurement processes in place. The expected practical benefit of the planning method is to provide release plan solutions that achieve a better overall business value (e.g., expressed by the degree of stakeholder satisfaction) by better allocation of resources. Without ignoring the importance of the human expert in this process, the contributions of the paper are seen in making the overall process more objective and the resulting decisions more transparent.

Cost, benefits and quality of software development documentation: A systematic mapping

Journal of Systems and Software, 2015

Context: Software documentation is an integral part of any software development process. Research... more Context: Software documentation is an integral part of any software development process. Researchers and practitioners have expressed concerns about costs, benefits and quality of software documentation in practice. On the one hand, there is a lack of a comprehensive model to evaluate the quality of documentation. On the other hand, researchers and practitioners need to assess whether documentation cost outweighs its benefit. Objectives: In this study, we aim to summarize the existing literature and provide an overview of the field of software documentation cost, benefit and quality. Method: We use the systematic-mapping methodology to map the existing body of knowledge related to software documentation cost, benefit and quality. To achieve our objectives, 11 Research Questions (RQ) are raised. The primary papers are carefully selected. After applying the inclusion and exclusion criteria, our study pool included a set of 69 papers from 1971-2011. A systematic map is developed and refined iteratively. Results: We present the results of a systematic mapping covering different research aspects related to software documentation cost, benefit and quality (RQ 1-11). Key findings include: (1) Validation research papers are dominating (27 papers), followed by solution proposals (21 papers). (2) Most papers (61 out of 69) do not mention the development life-cycle model explicitly. Agile development is only mentioned in 6 papers. (3) Most papers include only one "System under Study" (SUS) which is mostly academic prototype. The average number of participants in survey-based papers is 106, the highest one having approximately 1,000 participants. (4) In terms of focus of papers, 50 papers focused on documentation quality, followed by 37 papers on benefit, and 12 papers on documentation cost. (5) The quality attributes of documentation that appear in most papers are, in order: completeness, consistency and accessibility. Additionally, improved meta-models for documentation cost, benefit and quality are also presented. Furthermore, we have created an online paper repository of the primary papers analyzed and mapped during this study.

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Release Planning Patterns for the Automotive Domain

Computers

Context: Today’s vehicle development is focusing more and more on handling the vast amount of sof... more Context: Today’s vehicle development is focusing more and more on handling the vast amount of software and hardware inside the vehicle. The resulting planning and development of the software especially confronts original equipment manufacturers (OEMs) with major challenges that have to be mastered. This makes effective and efficient release planning that provides the development scope in the required quality even more important. In addition, the OEMs have to deal with boundary conditions given by the OEM itself and the standards as well as legislation the software and hardware have to conform to. Release planning is a key activity for successfully developing vehicles. Objective: The aim of this work is to introduce release planning patterns to simplify the release planning of software and hardware installed in a vehicle. Method: We followed a pattern identification process that was conducted at Dr. Ing. h. c. F. Porsche AG. Results: We introduce eight release planning patterns, whic...

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2.1 Release Planning for Evolving Systems......................................................................................... 4

Failure Prediction in Crowdsourced Software Development

2017 24th Asia-Pacific Software Engineering Conference (APSEC), 2017

Background: Despite the increasingly reported benefits of software crowdsourcing, one of the majo... more Background: Despite the increasingly reported benefits of software crowdsourcing, one of the major practical concerns is the limited visibility and control over task progress. Aim: This paper reports an empirical study to develop a framework for failure prediction in software crowdsourcing. Method: This process begins with identifying 13 influencing factors in software crowdsourcing failures, across four categories including task characteristics, technology popularity, competition network, and workers reliability. Presenting an algorithm to construct worker competition network and extract its network metrics features. The proposed framework was evaluated on 4,872 software crowdsourcing tasks, extracted from TopCoder platform, using five machine learners, compared with in-house TopCoder predictor. Results: 1) Workers reliability, links in the description, number of registered workers, number of required technologies, and task-workers network modularity are the most influencing factors for predicting crowdsourcing failure; 2) The top-three learners for task failure are Naïve Bayes, Random Forest, and StackingC, with precision above 98.8%, recall above 81.2%, and F-measure above 91.2%; and 3) The proposed best learners significantly outperform the two baseline models in our evaluation. Conclusions: The performance of the proposed framework is better than those of the two baseline models. This paper offers practical recommendations for managing task failure risks.

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Mini-Track: Analytical Software Project Management

Software project management deals with software projects and the challenges of human-based develo... more Software project management deals with software projects and the challenges of human-based development (as opposed to the more deterministic processes in traditional projects). The higher flexibility in software development approaches puts new demands on the capabilities of software project management. Weaknesses in planning, organizing, staffing, directing, and controlling are hard to be counterbalanced by more efficiency in technical development work. As Fred Brooks stated “. . . today’s major problems with software development are not technical problems, but management problems” (Brooks 1987). The principal nature of the challenges in software project management has not changed dramatically in the last 25 years. However, software-intensive systems of the twenty-first century increasingly vary in their content, size, complexity, and their degree of interaction with other systems. The technological and communication infrastructure to develop these systems is hard to compare with th...

Anatomy of functionality deletion

Proceedings of the 15th International Conference on Mining Software Repositories, 2018

One of Lehman's laws of software evolution is that the functionality of programs has to incre... more One of Lehman's laws of software evolution is that the functionality of programs has to increase over time to maintain user satisfaction. In the domain of mobile apps, though, too much functionality can easily impact usability, resource consumption, and maintenance effort. Hence, does the law of continuous growth apply there? This paper shows that in mobile apps, deletion of functionality is actually common, challenging Lehman's law. We analyzed user driven requests for deletions which were found in 213,866 commits from 1,519 open source Android mobile apps from a total of 14,238 releases. We applied hybrid (open and closed) card sorting and created taxonomies for nature and causes of deletions. We found that functionality deletions are mostly motivated by unneeded functionality, poor user experience, and compatibility issues. We also performed a survey with 106 mobile app developers. We found that 78.3% of developers consider deletion of functionality to be equally or more important than the addition of new functionality. Developers confirmed that they plan for deletions. This implies the need to re-think the process of planning for the next release, overcoming the simplistic assumptions to exclusively look at adding functionality to maximize the value of upcoming releases. Our work is the first to study the phenomenon of functionality deletion and opens the door to a wider perspective on software evolution.

Task Interruptions in Requirements Engineering: Reality Versus Perceptions!

2017 IEEE 25th International Requirements Engineering Conference (RE), 2017

Task switching and interruptions are a daily reality in software development projects: developers... more Task switching and interruptions are a daily reality in software development projects: developers switch between Requirements Engineering (RE), coding, testing, daily meetings, and other tasks. Task switching may increase productivity through increased information flow and effective time management. However, it might also cause a cognitive load to reorient the primary task, which accounts for the decrease in developers' productivity and increases in errors. This cognitive load is even greater in cases of cognitively demanding tasks as the ones typical for RE activities. In this paper, to compare the reality of task switching in RE with the perception of developers, we conducted two studies: (i) a case study analysis on 5,076 recorded tasks of 19 developers and (ii) a survey of 25 developers. The results of our retrospective analysis show that in 98% of cases that the disruptiveness of RE interruptions is statistically different from other software development tasks, RE related tasks are more vulnerable to interruptions compared to other task types. Moreover, we found that context switching, the priority of the interrupting task, and the interruption source and timing are key factors that impact RE interruptions. We also provided a set of RE task switching patterns along with recommendations for both practitioners and researchers. While the results of our retrospective analysis show that self-interruptions are more disruptive than external interruptions, developers have different perceptions about the disruptiveness of various sources of interruptions.

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Asymmetric Release Planning: Compromising Satisfaction against Dissatisfaction

IEEE Transactions on Software Engineering, 2019

Maximizing satisfaction from offering features as part of the upcoming release(s) is different fr... more Maximizing satisfaction from offering features as part of the upcoming release(s) is different from minimizing dissatisfaction gained from not offering features. This asymmetric behavior has never been utilized for product release planning. We study Asymmetric Release Planning (ARP) by accommodating asymmetric feature evaluation. We formulated and solved ARP as a bicriteria optimization problem. In its essence, it is the search for optimized trade-offs between maximum stakeholder satisfaction and minimum dissatisfaction. Different techniques including a continuous variant of Kano analysis are available to predict the impact on satisfaction and dissatisfaction with a product release from offering or not offering a feature. As a proof of concept, we validated the proposed solution approach called Satisfaction-Dissatisfaction Optimizer (SDO) via a real-world case study project. From running three replications with varying effort capacities, we demonstrate that SDO generates optimized trade-off solutions being (i) of a different value profile and different structure, (ii) superior to the application of random search and heuristics in terms of quality and completeness, and (iii) superior to the usage of manually generated solutions generated from managers of the case study company. A survey with 20 stakeholders evaluated the applicability and usefulness of the generated results.

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What are Practitioners Asking about Requirements Engineering? An Exploratory Analysis of Social Q&A Sites

2016 IEEE 24th International Requirements Engineering Conference Workshops (REW), 2016

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A guest editorial: special section on search-based software engineering

Empirical Software Engineering, 2016

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DEVis: A tool for visualizing software document evolution

2013 First IEEE Working Conference on Software Visualization (VISSOFT), 2013

During the software development process many technical documents are produced. Such documents and... more During the software development process many technical documents are produced. Such documents and their evolution history contain rich information about the development process. Analyzing these document changes may reveal regularities and anomalies which are helpful to understand the software system and its development process. In this paper, we propose DEVis, an interactive visualization tool to visualize the software documentation evolution and aid the tasks of analyzing software development process. We initially evaluated our tool using the knowledge task-based framework and discuss the challenging aspects and lessons learned during the development of DEVis.

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Minitrack Introduction

Proceedings of the 39th Annual Hawaii International Conference on System Sciences (HICSS'06), 2006

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COTS Evaluation Supported by Knowledge Bases

Lecture Notes in Computer Science, 2004

Selection of Commercial-off-The-Shelf (COTS) software products is a knowledge-intensive process. ... more Selection of Commercial-off-The-Shelf (COTS) software products is a knowledge-intensive process. In this paper, we show how knowledge bases can be used to facilitate the COTS selection process. We propose a conceptual model to support decision makers during the evaluation procedures. We then describe how this model is implemented using agent technologies supported by two knowledge bases (KB): the COTS KB and the methods KB. The model relies on group-decision making and facilitated stakeholder negotiations during the selection process. It employs hybrid techniques, such as Bayesian Belief Networks and Game Theory, to address different challenges throughout the process. In addition, the paper also describes how the COTS knowledge base can be used at three levels of usage: global (over the internet), limited (between limited number of organizations) and local (within a single organization).

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Guest Editors' Introduction: Knowledge Discovery from Empirical Software Engineering Data

International Journal of Software Engineering and Knowledge Engineering, 1999

Finding new phenomena, validating existing hypotheses, or enhancing our existing knowledge is one... more Finding new phenomena, validating existing hypotheses, or enhancing our existing knowledge is one of the most desirable end-products of computing for all application domains. The final objective of Knowledge Discovery in Software Engineering is to package discovered knowledge in the form of updated and refined models and other forms of structured knowledge gained from prior projects and save it in repository for future projects. The knowledge acquired through empirical studies is a very important company asset, ...

Goal-oriented learning in experimental software engineering by using rough sets

. Rough set theory is a foundation for a series of analysis methods which has beensuccessfully ap... more . Rough set theory is a foundation for a series of analysis methods which has beensuccessfully applied in many real-life problems of various areas. Main focus of the approach isto explain experimental data by establishing cause-effect relationships. We have applied the approachin the context of experimental software engineering to support analysis and interpretation ofmeasurement data within interactive feedback sessions. Measurement

A hybrid method for advance decision support in strategic product release planning

Laboratory for Software Engineering Decision Support, SEDS-TR, Mar 1, 2010

Abstract—DECIDERelease is a hybrid method that combines simulation-based robustness analysis and ... more Abstract—DECIDERelease is a hybrid method that combines simulation-based robustness analysis and multi-criteria decision analysis with existing strategic release planning approach EVOLVE*. The purpose of DECIDERelease is to qualify decision-making by pro-actively exploring the robustness of the operational plans of upcoming releases. Based on this analysis, the strategic release plan that is the most robust against assumed changes in planning parameters at operational level can be selected. In this technical report we ...

Toward Data-Driven Requirements Engineering

IEEE Software, 2016

Nowadays, users can easily submit their feedback about software products in app stores, social me... more Nowadays, users can easily submit their feedback about software products in app stores, social media, or user groups. Moreover, software vendors are collecting massive amounts of implicit feedback in the form of usage data, error logs, and sensor data. Outlining these trends, we envision a paradigm shift towards data-driven user-centered identification, prioritization, and management of software requirements. Future software and requirements engineering should be able to adopt the requirements of user masses when deciding on what to develop and when to release. We discuss how practitioners could systematically use explicit and implicit user data in an aggregated form to support their decisions about requirements-towards a data-driven requirements engineering by the masses and for the masses.

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The Art and Science of Software Release Planning

IEEE Software, 2005

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NaPiRE Data Set 2014Naming the Pain in Requirements Engineering Survey Data 2014/15

Data from the NaPiRE run 2013 in 10 countries. The data set includes: (1) codebooks and instrumen... more Data from the NaPiRE run 2013 in 10 countries. The data set includes: (1) codebooks and instrumentation, (2) complete data export, and the results of the (3) manual coding sheets. Further data, analysis scripts, or explanations upon request. Further information on the overall project can be taken from the website www.re-survey.org<br>Survey Data on practices and problems in Requirements Engineering

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