Case Studies in Industry: What We Have Learnt

Case study research has become an important research methodology for exploring phenomena in their natural contexts. Case studies have earned a distinct role in the empirical analysis of software engineering phenomena which are difficult to capture in isolation. Such phenomena often appear in the context of methods and development processes for which it is difficult to run large, controlled experiments as they usually have to reduce the scale in several respects and, hence, are detached from the reality of industrial software development. The other side of the medal is that the realistic socio-economic environments where we conduct case studies -- with real-life cases and realistic conditions -- also pose a plethora of practical challenges to planning and conducting case studies. In this experience report, we discuss such practical challenges and the lessons we learnt in conducting case studies in industry. Our goal is to help especially inexperienced researchers facing their first case studies in industry by increasing their awareness for typical obstacles they might face and practical ways to deal with those obstacles.Comment: Proceedings of the 4th International Workshop on Conducting Empirical Studies in Industry, co-located with ICSE, 201

Look Who's Talking: Bipartite Networks as Representations of a Topic Model of New Zealand Parliamentary Speeches

Quantitative methods to measure the participation to parliamentary debate and discourse of elected Members of Parliament (MPs) and the parties they belong to are lacking. This is an exploratory study in which we propose the development of a new approach for a quantitative analysis of such participation. We utilize the New Zealand government's digital Hansard database to construct a topic model of parliamentary speeches consisting of nearly 40 million words in the period 2003-2016. A Latent Dirichlet Allocation topic model is implemented in order to reveal the thematic structure of our set of documents. This generative statistical model enables the detection of major themes or topics that are publicly discussed in the New Zealand parliament, as well as permitting their classification by MP. Information on topic proportions is subsequently analyzed using a combination of statistical methods. We observe patterns arising from time-series analysis of topic frequencies which can be related to specific social, economic and legislative events. We then construct a bipartite network representation, linking MPs to topics, for each of four parliamentary terms in this time frame. We build projected networks (onto the set of nodes represented by MPs) and proceed to the study of the dynamical changes of their topology, including community structure. By performing this longitudinal network analysis, we can observe the evolution of the New Zealand parliamentary topic network and its main parties in the period studied.Comment: 28 pages, 12 figures, 3 table

What to Fix? Distinguishing between design and non-design rules in automated tools

Technical debt---design shortcuts taken to optimize for delivery speed---is a critical part of long-term software costs. Consequently, automatically detecting technical debt is a high priority for software practitioners. Software quality tool vendors have responded to this need by positioning their tools to detect and manage technical debt. While these tools bundle a number of rules, it is hard for users to understand which rules identify design issues, as opposed to syntactic quality. This is important, since previous studies have revealed the most significant technical debt is related to design issues. Other research has focused on comparing these tools on open source projects, but these comparisons have not looked at whether the rules were relevant to design. We conducted an empirical study using a structured categorization approach, and manually classify 466 software quality rules from three industry tools---CAST, SonarQube, and NDepend. We found that most of these rules were easily labeled as either not design (55%) or design (19%). The remainder (26%) resulted in disagreements among the labelers. Our results are a first step in formalizing a definition of a design rule, in order to support automatic detection.Comment: Long version of accepted short paper at International Conference on Software Architecture 2017 (Gothenburg, SE

Software release planning

One of the most critical activities in software product development is the decisional process that assigns features to subsequent releases under technical, resource, risk, and budget constraints. This decision-centric process is referred to as software release planning (SRP). This briefing will expose a state of the art on SRP. A survey of the most relevant approaches will be presented. Emphasis will be made on their applicability (concerning e.g. type of development process - being more predictive versus more adaptive, type of system - commercial, open source product or mobile app), tool support and degree of validation in industry. One of these approaches, EVOLVE, will be analysed in detail.Peer ReviewedPostprint (author's final draft

Risk assessment in open source systems

Adopting Open Source Software (OSS) components offers many advantages to organizations but also introduces risks related to the intrinsic fluidity of the OSS development projects. Choosing the right components is a critical decision, as it could contribute to the success of any adoption process. Making the right decision requires to evaluate the technical capabilities of the components and also related strategic aspects, including possible impacts on high level objectives. This can be achieved through a portfolio of risk assessment and mitigation methods. In this briefing we introduce the basic concepts related to OSS ecosystems and to risk representation and reasoning. We illustrate how risk management activities in OSS can benefit from the large amount of data available from OSS repositories and how they can be connected to business goals for strategic decision-making. The concepts are illustrated with a software platform developed in the context of the EU FP7 project RISCOSS.Peer ReviewedPostprint (author's final draft

Pemodelan Topik pada Judul Berita Online Detikcom Menggunakan Latent Dirichlet Allocation

Detikcom is a very popular news portal today. The news on the portal continues to grow time to time, causing the existing news data to pile up. As a result, this is necessary to utilize this large amount of data. One of the ways that can be used is to extract topics from news text data through topic modeling using the Latent dirichlet allocation (LDA) method. This method is very popular because it can perform analysis on very large documents. This research aims to find certain patterns in a document by generating several different topics so that it does not specifically divide documents into a particular topic. This research has three topics obtained, with a coherence score is 0,7586. The first topic discusses conflicts and crises within a country, the second topic discusses issues related to humanitarian, and the third topic discusses the issues of corruption committed by state officials

In Quest for Proper Mediums for Technology Transfer in Software Engineering

Successful transfer of the results of research projects into practice is of great interest to all project participants. It can be assumed that different transfer mediums fulfill technology transfer (TT) with different levels of success and that they are impaired by different kinds of barriers. The goal of this study is to gain a better understanding about the different mediums used for TT in software engineering, and to identify barriers weakening the success of the application of such mediums. We conducted an exploratory study implemented by a survey in the context of a German research project with a broad range of used mediums. The main reported barriers were low expectations of usefulness, no awareness of existence, lack of resources, or inadequateness in terms of outdated material or being in an immature state. We interpreted our results as symptoms of a lack of a dissemination plan in the project. Further work will be needed to explore the implications for the transfer of research results (knowledge and techniques) to practice.Comment: Proceedings of the International Conference on Empirical Software Engineering and Measurement, 201

Data-driven requirements engineering in agile projects: The Q-Rapids approach

Requirements identification, specification and management are key activities in the software development process. In the last years, many approaches to these activities have emerged, based on the exploitation of huge amounts of data gathered from software repositories and system usage. The Q-Rapids project proposes the collection and analysis of such data and its consolidation into a set of strategic indicators as product quality, time to market and team productivity. These indicators are visualized through a dashboard designed to support decision-makers. In this paper, we present the ongoing research undertaken in this project. We use the concept of blocking situation to exemplify the Q-Rapids approach.Peer ReviewedPostprint (author's final draft