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

Performance and strategy:simultaneous equations analysis of long-lived firms

A simultaneous equations model of performance, strategy and size is tested using fieldwork evidence on long-lived firms in Scotland. Estimation is by I3SLS, with correction for sample selection bias. The contributions of this paper are that it: (a) grounds estimation on fieldwork evidence; (b) calibrates performance and competitive strategy; (c) tests and models endogeneity; and (d) computes robust trade-off elasticities between firm size and performance. It shows how this trade-off provides the entrepreneur with two strong incentives: (i) to seek greater efficiency typically by an increase in the human capital of the ‘core’ workforce; (ii) to achieve higher levels of performance by adopting more diverse competitive strategies

Technical Debt in Software Development : Examining Premises and Overcoming Implementation for Efficient Management

Software development is a unique field of engineering: all software constructs retain their modifiability — arguably, at least — until client release, no single project stakeholder has exhaustive knowledge about the project, and even this portion of the knowledge is generally acquired only at project completion. These characteristics imply that the field of software development is subject to design decisions that are known to be sub-optimal—either deliberately emphasizing interests of particular stakeholders or indeliberately harming the project due to lack of exhaustive knowledge. Technical debt is a concept that accounts for these decisions and their effects. The concept’s intention is to capture, track, and manage the decisions and their products: the affected software constructs. Reviewing the previous, it is vital for software development projects to acknowledge technical debt both as an enabler and as a hindrance. This thesis looks into facilitating efficient technical debt management for varying software development projects. In the thesis, examination of technical debt’s role in software development produces the premises on to which a management implementation approach is introduced. The thesis begins with a revision of motivations. Basing on prior research in the fields of technical debt management and software engineering in general, the five motivations establish the premises for technical debt in software development. These include notions of subjectivity in technical debt estimation, update frequency demands posed on technical debt information, and technical debt’s polymorphism. Three research questions are derived from the motivations. They ask for tooling support for technical debt management, capturing and modelling technical debt propagation, and characterizing software development environments and their technical debt instances. The questions imply consecutive completion as the first pursued tool would benefit from—possibly automatically assessable—propagation models, and finally the tool’s introduction to software development organizations could be assisted by tailoring it based on the software development environment and the technical debt instance characterizations. The thesis has seven included publications. In introducing them, the thesis maps their backgrounds to the motivations and their outcomes to the research questions. Amongst the outcomes are the DebtFlag tool for technical debt management, the procedures for retrospectively capturing technical debt from software repositories, a procedure for technical debt propagation model creation from these retrospectives, and a multi-national survey characterizing software development environments and their technical debt instances. The thesis concludes that the tooling support, the technical debt propagation modelling, and the software environment and technical debt instance characterization describe an implementation approach to further efficient technical debt management. Simultaneously, future work is implied as all previously described efforts need to be continued and extended. Challenges also remain in the introduced approach. An example of this is the combinatorial explosion of technology-development-context-combinations that technical debt propagation modelling needs to consider. All combinations have to be managed if exhaustive modelling is desired. There is, however, a great deal of motivation to pursue these efforts when one re-notes that technical debt is a permanent component of software development that, when correctly managed, is a development efficiency mechanism comparable to a financial loan investment.Ohjelmistokehitys on uniikki tekniikan ala: kaikki ohjelmistorakenteet säilyttävät muokattavuutensa — otaksuttavasti ainakin — asiakasjulkaisuun asti. Yhdenkään projektiosakkaan tietämys ei kata koko projektia ja merkittävä osa tästäkin tiedosta karttuu vasta projektin suorittamisen aikana. Nämä ominaisuudet antavat ymmärtää, että ohjelmistokehitysala on sellaisten suunnitelupäätösten kohde, joiden tiedetään olevan epätäydellisiä—joko tarkoituksella tiettyjen projektiosakkaiden intressejä painottavia tai tahattomasti projektia vahingoittavia puutteelliseen tietoon perustuvia. Tekninen velka on konsepti, joka huomioi nämä päätökset sekä niiden vaikutukset. Konseptin tarkoitus on havaita, seurata ja hallita näitä päätöksiä sekä tuloksena syntyviä teknisen velan vaikutuksen alla olevia ohjelmistorakenteita. Edellisen kuvauksen valossa ohjelmistokehitysprojekteille on erityisen tärkeää huomioida tekninen velka sekä mahdollistajana että hidasteena. Tämän vuoksi kyseinen väitöskirja perehtyy tehokkaan teknisen velan hallinnan fasilitointiin moninaisille ohjelmistokehitysprojekteille. Väitöskirjassa tarkastellaan teknisen velan roolia osana ohjelmistokehitystä. Tarkastelu tuottaa joukon premissejä, joihin perustuen esitellään lähestymistapa teknisen velan hallinnan toteuttamiselle. Viisi väitöskirjan alussa esitettyä motivaatiota kiinnittävät ne premissit,joille ratkaisu esitetään. Motivaatiot rakennetaan olemassa olevaan teknisen velan sekä ohjelmistotekniikan tutkimustietoon perustuen. Näihin lukeutuvat muun muassa subjektiivisuus teknisen velan estimoinnissa, teknisen velan informaatiolle nähdyt päivitystaajuusvaatimukset sekä teknisen velan polymorfismi. Havainnoista johdetaan kolme tutkimuskysymystä. Ne tavoittelevat työkalutukea teknisen velan hallinnalle, velan propagoitumisen havainnointia sekä mallinnusta kuin myös ohjelmistotuotantoympäristöjen ja niiden velka instanssien kuvaamista. Tutkimuskysymykset implikoivat peräkkäistä suoritusta: tavoiteltu työkalu hyötyy—mahdollisesti automaattisesti arvoitavista—teknisen velan propagaatiomalleista. Valmiin työkalun käyttöönottoa voidaan taas edistää jos kuvaukset kehitysympäristöistä sekä niiden velkainstansseista ovat käytettävissä työkalun räätälöintiin. Väitöskirjaaan sisältyy seitsemän julkaisua. Väitöskirja esittelee ne kiinnittämällä julkaisujen taustatyön aikaisemmin mainittuihin motivaatioihin sekä niiden tulokset edellisiin tutkimuskysymyksiin. Tuloksista huomioidaan esimerkiksi DebtFlag-työkalu teknisen velan hallintaan, retrospektiivinen prosessi teknisen velan kartoittamiselle versionhallintajärjestelmistä, prosessi teknisen velan mallien rakentamiselle näistä kartoituksista ja monikansallinen kyselytutkimus ohjelmistokehitysympäristöjen sekä näiden teknisen velan instanssien luonnehtimiseksi. Väitöskirjan yhteenvetona huomioidaan, että teknisen velan hallinnan työkalutuki, teknisen velan propagaatiomallinnus ja ohjelmistokehitysympäristöjen sekä niiden teknisen velan instanssien luonnehdinta muodostavat toteutustavan, jolla teknisen velan tehokasta hallintaa voidaan kehittää. Samalla implikoidaan jatkotoimia, sillä kaikkia edellä kuvattuja työn osia tulee jatkaa ja laajentaa. Toteutustavalle nähdään myös haasteita. Eräs näistä on kombinatorinen räjähdys teknologia- ja kehityskontekstikombinaatioille. Kaikki kombinaatiot tulee huomioida mikäli teknisen velan propagaatiomallinnuksesta halutaan kattavaa. Motivaatio väitöskirjassa esitetyn työn jatkamiselle on huomattavaa ja sitä kasvattaa entuudestaan edellä tehty huomio siitä, että tekninen velka on pysyvä komponentti ohjelmistokehityksessä, joka oikein hallittuna on kehitystehokkuutta edistävänä komponenttina verrattavissa finanssialan lainainvestointiin.Siirretty Doriast

Hitting the Bullseye: The Influence of Technical Debt on the Accuracy of Effort Estimation in Agile Projects

As firms rapidly develop solutions in order to increase revenue and market share, software development decisions considered to be temporary shortcuts and/or compromises may be implemented. These shortcuts represent “technical debt,” a metaphor which succinctly describes a software solution that should be “paid in full” or remediated in the future. Software architects and developers intend to resolve the “debt” in future product releases, but practitioners recognize that the challenge of always innovating may indefinitely postpone this remediation effort. Further, the accumulation of technical debt may have long term impact on the product’s maintainability by the software development teams and, consequently, impact the effort estimate delivered to management for forecasting product delivery timelines and product revenue expectations. While there are multiple publications that have studied effort estimation in traditional and agile software development strategies, there is limited research which considers technical debt during the estimation effort. As a result, the purpose of this dissertation is to design and propose a research model intended to determine whether or not the consideration of technical debt during the effort estimation process will improve the accuracy of the effort estimate in an agile project

Investigation on Self-Admitted Technical Debt in Open-Source Blockchain Projects

Technical debt refers to decisions made during the design and development of software that postpone the resolution of technical problems or the enhancement of the software's features to a later date. If not properly managed, technical debt can put long-term software quality and maintainability at risk. Self-admitted technical debt is defined as the addition of specific comments to source code as a result of conscious and deliberate decisions to accumulate technical debt. In this paper, we will look at the presence of self-admitted technical debt in open-source blockchain projects, which are characterized by the use of a relatively novel technology and the need to generate trust. The self-admitted technical debt was analyzed using NLP techniques for the classification of comments extracted from the source code of ten projects chosen based on capitalization and popularity. The analysis of self-admitted technical debt in blockchain projects was compared with the results of previous non-blockchain open-source project analyses. The findings show that self-admitted design technical debt outnumbers requirement technical debt in blockchain projects. The analysis discovered that some projects had a low percentage of self-admitted technical debt in the comments but a high percentage of source code files with debt. In addition, self-admitted technical debt is on average more prevalent in blockchain projects and more equally distributed than in reference Java projects.If not managed, the relatively high presence of detected technical debt in blockchain projects could represent a threat to the needed trust between the blockchain system and the users. Blockchain projects development teams could benefit from self-admitted technical debt detection for targeted technical debt management

Can banks circumvent minimum capital requirements? The case of mortgage portfolios under Basel II

The recent mortgage crisis has resulted in several bank failures as the number of mortgage defaults increased. The current Basel I capital framework does not require banks to hold sufficient amounts of capital to support their mortgage lending activities. The new Basel II capital rules are intended to correct this problem. However, Basel II models could become too complex and too costly to implement, often resulting in a trade-off between complexity and model accuracy. In addition, the variation of the model, particularly how mortgage portfolios are segmented, could have a significant impact on the default and loss estimated and, thus, could affect the amount of capital that banks are required to hold. This paper finds that the calculated Basel II capital varies considerably across the default prediction model and segmentation schemes, thus providing banks with an incentive to choose an approach that results in the least required capital for them. The authors also find that a more granular segmentation model produces smaller required capital, regardless of the economic environment. In addition, while borrowers' credit risk factors are consistently superior, economic factors have also played a role in mortgage default during the financial crisis.Capital ; Banks and banking ; Basel capital accord

CGE-Microsimulation Modelling: A Survey

This paper reviews the recent work on the application of the CGE-microsimulation models. The discussion focuses on the various linking methodologies and how they can impact our results.Computable General Equilibrium (CGE) Model; Microsimulation; Poverty; Inequality;

Why India choked when Lehman broke.

India has an elaborate system of capital controls which impede capital mobility and particularly short-term debt. Yet, when the global money market fell into turmoil after the bankruptcy of Lehman Brothers on 13/14 September 2008, the Indian money market immediately experienced considerable stress, and the operating procedures of monetary policy broke down. We suggest that Indian multinationals were using the global money market and were short of dollars on 15 September. They borrowed in India and took capital out of the country. We make three predictions that follow from this hypothesis, and nd that the evidence matches these predictions. This suggests an important role for Indian multinationals in India's evolution towards de facto convertibility.